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Spice v2.0-rc.5 (May 27, 2026)

Β· 30 min read
Jack Eadie
Token Plumber at Spice AI

Spice v2.0-rc.5 is now available! πŸ”₯

v2.0.0-rc.5 is the fifth release candidate for advanced testing of v2.0, building on v2.0.0-rc.4.

This release completes the mTLS implementation across server endpoints and outbound connectors, adds MongoDB Change Streams and durable Kafka offset persistence as new CDC sources, expands DML write-back to PostgreSQL, Snowflake, and Arrow, promotes DuckLake to Beta, introduces user-defined functions, on-demand dataset loading, unified query cancellation, dynamic HTTP request headers and subquery-driven request parameters, provider-aware LLM prompt caching, and a long list of Cayenne performance improvements.

Highlights in this release candidate include:

  • Spice Cayenne β€” CDC throughput, compaction and scan caching, synchronized partition commits, join filter propagation, parallel Vortex writes, lock-free deletion caches
  • Mutual TLS (mTLS) β€” TLS cert hot-reload, public mTLS for HTTP and Flight (channel + identity modes), mTLS client certs for FlightSQL and Spice.ai connectors
  • MongoDB Change Streams β€” native real-time CDC for MongoDB, no Debezium or Kafka required
  • Kafka CDC offsets β€” offsets persisted in sidecar tables for durable, resumable Kafka CDC
  • PostgreSQL DML β€” INSERT, UPDATE, DELETE write-back on PostgreSQL datasets
  • Snowflake DML β€” INSERT, UPDATE, DELETE write-back on Snowflake datasets
  • Arrow Primary Key Upserts β€” native upsert path using primary key matching
  • DuckLake promoted to Beta β€” with INSERT support on catalog tables
  • User-Defined Functions β€” define SQL UDFs in spicepods, plus remote UDFs over HTTP (Spice.ai Enterprise)
  • Spatial SQL UDFs β€” optional geospatial UDFs (ST_*) for geometry workloads
  • On-Demand Dataset Loading β€” datasets can be deferred and loaded on first reference
  • Unified Query Cancellation β€” Ctrl-C and HTTP request cancellation propagate across all execution paths
  • Dynamic HTTP Connector β€” pass-through request headers, subquery-driven params, and JSON schema decomposition
  • HTTP Rate-Control persistence β€” rate-limit state persisted in object storage across restarts
  • refresh_mode: snapshot β€” point-in-time snapshot acceleration with SQLite/Turso WAL flushing
  • Storage-profile accelerator tuning β€” accelerators auto-tune defaults based on local SSD, EBS-class disk, or tmpfs
  • Provider-Aware LLM Prompt Caching β€” automatic prompt caching for OpenAI-compatible providers that support it
  • Responses API β€” support across all model providers with streaming response.output_text.delta, plus Authorization: Bearer header support

What's New in v2.0.0-rc.5​

Cayenne Improvements​

Significant performance work across Spice Cayenne-backed catalogs and accelerators.

  • Ingest throughput: End-to-end improvements to CDC ingest, background compaction, and a new scan-result cache for hot reads; parallel Vortex partition writes; lock-free deletion caches with bloom-prefiltered probes; background retention with CDC pipelining; SQLite metastore pool scaled to 32 for high-concurrency mutation workloads.
  • Data inlining: Small writes are serialized as Arrow IPC and committed directly into the Cayenne metastore (cayenne_inlined_data), bypassing the staged Vortex write path for low-latency ingest. Inline upserts atomically rewrite existing inline rows instead of emitting side delete markers, and inline data remains query-visible via an in-memory union scan with a generation-keyed decode cache. Inline rows are checkpointed to Vortex when row, segment, or byte thresholds are reached. Defaults are refresh-mode aware: inline writes are enabled by default for high-frequency caching, changes, and fast append workloads and disabled for full, snapshot, and slower append.
  • Query planning: Join filter propagation across equi-join keys (gated behind runtime.params.cayenne_filter_propagation), range fallback for large join filters, hot-path clone elimination, and IN-list rewrites for large filter lists.
  • Correctness: Synchronized partition commits across partitions, correct NULL-sentinel handling for nullable partition expressions (e.g. bucket(N, col)), Vortex panic fix on highly compressible data, and live reads through expired protected snapshots.
  • Catalog and platform: Refresh-mode-aware compaction defaults, rejection of non-distributed Cayenne catalog configurations, and a vendored Vortex DataFusion integration for faster iteration on the Cayenne planner.

Mutual TLS (mTLS)​

Spice.ai Enterprise feature. See Enterprise Security.

Spice now supports full mutual TLS for both HTTP and Arrow Flight endpoints.

TLS cert hot-reload (#10727): The Spice runtime watches for SIGHUP and reloads TLS certificates without restarting, enabling cert rotation with zero downtime.

Public mTLS for HTTP and Flight (#10753): Two client_auth_mode values control how the server handles client certificates:

  • request β€” optional mTLS: the server requests a client cert but accepts connections without one (useful for migration windows).
  • required β€” strict mTLS: the server requires a valid client cert signed by the configured CA.

mTLS client certs for FlightSQL and Spice.ai connectors (#10764): Outbound connections from the FlightSQL and Spice.ai data connectors can now present client certificates for mutual authentication with upstream services.

Example configuration:

runtime:
tls:
enabled: true
certificate_file: /etc/spice/tls/server.crt
key_file: /etc/spice/tls/server.key
client_auth_mode: required
client_auth_ca_file: /etc/spice/tls/client-ca.crt

MongoDB Change Streams​

MongoDB datasets configured with refresh_mode: changes now stream changes from MongoDB Change Streams into any local accelerator (#10813), providing real-time CDC without Debezium or Kafka.

Example configuration:

datasets:
- from: mongodb:my_collection
name: my_collection
params:
host: my-cluster.mongodb.net
db: mydb
acceleration:
enabled: true
engine: duckdb
refresh_mode: changes

CDC Improvements​

See Change Data Capture (CDC) for an overview of CDC in Spice.

  • Kafka CDC offset persistence (#10823): Kafka CDC offsets are persisted in sidecar tables for durable, resumable streams. On restart or failover, Spice resumes from the last committed offset.
  • Pipelined CDC ingestion (#10676): Source reads overlap with batch apply, with additional batching, envelope coalescing, and nullability propagation improvements across the apply pipeline.
  • Debezium schema evolution fix (#10144): Schema changes in Debezium-sourced datasets no longer break dataset initialization on reload (fixes #9782).

PostgreSQL DML Support​

The PostgreSQL data connector now supports write-back via INSERT, UPDATE, and DELETE operations (#10446). Combined with the existing read-side federation, PostgreSQL-backed datasets can serve as full read/write tables. The PostgreSQL Catalog connector additionally exposes foreign-key metadata for NSQL and query planning (#10849).

Snowflake DML Support​

The Snowflake data connector now supports write-back via INSERT, UPDATE, and DELETE operations (#10747), complementing its existing read capabilities.

Arrow Primary Key Upserts​

Arrow-accelerated tables now support native upsert operations using primary key matching (#10749), providing efficient update-or-insert semantics for in-memory datasets.

DuckLake Promoted to Beta​

The DuckLake Catalog and Data Connector are promoted to Beta quality (#10743).

DuckLake catalog tables with read_write access now support INSERT operations (#10744), enabling full read/write workflows against DuckLake-backed catalogs. The DuckLake connector also gains a series of correctness fixes for downcast, module registration, schema discovery, and S3 credentials (#10650).

User-Defined Functions​

Spice now supports user-defined functions (UDFs) as a first-class spicepod component (#10571), letting you define reusable SQL functions in the spicepod or invoke remote functions over HTTP. The runtime also gains table user functions with HTTP server gating (#10675).

A security fix closes a remote-UDF SSRF vector (#10757).

Spatial SQL UDFs​

Spice now ships an optional set of geospatial SQL UDFs (ST_*) for geometry workloads (#10833). The functions are gated behind a build feature and can be invoked from any SQL surface.

On-Demand Dataset Loading​

Datasets can now be marked for on-demand loading (#10629). Deferred datasets are registered with a declared schema at startup (#10669) and only fully resolve when first referenced, reducing startup time and memory footprint for spicepods with many seldom-used datasets.

Spicepods also gain columns[].type and columns[].nullable (#10661) with a lenient type parser for declaring schemas inline.

Unified Query Cancellation​

All query execution paths β€” HTTP, Flight, FlightSQL, MCP, and internal β€” now honour a unified cancellation signal (#10390). When a client disconnects, presses Ctrl-C in the REPL, or cancels an in-flight HTTP request, the corresponding query is cancelled end-to-end, freeing resources promptly.

Dynamic HTTP Connector​

The HTTP data connector gains dynamic request headers parameterised from query predicates (#10604), subquery-driven request parameters for fan-out queries (#10636), HTTP response metadata as queryable columns via JSON schema decomposition (#10679), no-limit pagination (#10673), and shared rate-control across HTTP-based connectors using the same backend host (#10648).

HTTP Rate-Control Persistence​

The HTTP rate-control state (per-endpoint throttle counters) is now persisted in object storage (#10697), ensuring rate limits survive restarts and are consistent across replicas. Rate-control metrics now use an origin label rather than the connector name for cleaner aggregation (#10689).

The metrics HTTP endpoint (/metrics) is also independently rate-limited (#10162) to prevent scraping from impacting query serving.

refresh_mode: snapshot​

Spice.ai Enterprise feature. See Acceleration Snapshots.

A new refresh_mode: snapshot provides point-in-time snapshot acceleration (#10651), with SQLite and Turso WAL flushing and a Cayenne metastore slice integration so accelerated readers see a consistent snapshot while writes continue.

Storage-Profile Accelerator Tuning​

Acceleration configs gain a new storage_profile field (#10913) with values auto (default), local_ssd, ebs, and tmpfs. Under auto, the runtime detects whether the acceleration store is backed by local SSD, EBS-class network disk, or tmpfs, and applies storage-aware defaults across DuckDB, partitioned DuckDB, SQLite, Turso, and Cayenne file-mode accelerators. Explicit per-accelerator parameters always override the profile defaults.

Provider-Aware LLM Prompt Caching​

LLM calls automatically use provider-aware prompt caching (#10645) when the configured model provider supports it (e.g., Anthropic, OpenAI). System prompts and tool descriptions are marked for caching so repeated invocations within the cache window reuse the provider-side cached prefix, reducing latency and cost.

A new searchable registry mode for LLM tools (#10647) lets agents discover tools by semantic search rather than enumerating all tools in the system prompt, which scales to large tool inventories.

Responses API Improvements​

The Responses API is now supported across all configured model providers (#10724). Streaming delta events via response.output_text.delta are also supported (#10828). The runtime now also accepts Authorization: Bearer headers in addition to x-api-key, bumps async-openai, and stops populating FunctionToolCall.id so OpenAI-compatible servers can assign the ID themselves (#10911).

Distributed Cluster Improvements​

Spice.ai Enterprise feature. See High Availability.

  • Per-request executor readiness gate (#10860): /v1/ready on schedulers waits for a configurable quorum of executors before returning healthy, enabling proper rolling deployments.
  • Ballista S3 shuffle reads under cluster mode (#10910): The shuffle reader builds its S3 client from the executor pod's environment, matching the writer. Async queries with runtime.params.shuffle_location: s3://... now complete instead of failing with AccessDenied on shuffle fetches.
  • Flattened scheduler config (#10450): runtime.scheduler.partition_management.* fields are flattened directly onto runtime.scheduler and renamed under the canonical "partition assignment" terminology. See Breaking Changes.

Improvements across Caching and Search:

  • Per-principal cache namespacing (#10702): SQL, search, and caching-accelerator caches are now namespaced per authenticated principal, so cached results never cross identity boundaries.
  • DuckDB HNSW vector indexes (#10695, #10674, #10668): DuckDB-accelerated views support HNSW vector indexes for vector search, vector search SQL is rewritten to activate HNSW_INDEX_SCAN, and HNSW indexes are preserved across data refresh.

Security Improvements​

See Authentication and TLS for configuring Spice security.

  • API key timing-position leak and remote-UDF SSRF (#10757): Closed a timing-based position-disclosure leak in API key comparison and blocked SSRF via remote UDF endpoint parameters.
  • Configurable allowed_hosts for MCP (#10638): MCP servers can be restricted to an explicit allowlist of upstream hosts.

SQL, Query, and Developer Experience​

See the SQL Reference for the full SQL surface area.

  • SQL REPL expanded view (#10797): Toggle \x in the REPL for a vertical key-value layout on wide result sets.
  • FlightSQL Substrait plan support (#10761): The Spice runtime now implements CommandStatementSubstraitPlan, enabling clients that submit plans as Substrait-encoded protobuf.
  • MCP auth for streamable HTTP tools (#10927): Streamable HTTP MCP tools support native authentication via mcp_auth_token and mcp_headers, both with full Spice secret expansion.
  • Elasticsearch FTS engine config and index lifecycle (#10672): Direct FTS engine configuration plus index lifecycle and ingestion controls for the Elasticsearch connector.
  • Self-hosted Spice connector (#10546): Connect Spice to another self-hosted Spice runtime as a federated source.

Connector Bug Fixes​

Notable correctness fixes across the Data Connectors: DynamoDB Streams retry on transient errors (#10794) and typed-NULL handling in DML (#10511); ScyllaDB physical filter pushdown disabled to fix incorrect results (#10772); MSSQL TOP N pushdown for non-nullable sort columns (#10621); DuckLake include filter applied (#10738); DuckDB DELETE/UPDATE on full and caching refresh modes (#10632); checked arithmetic for Turso integer-millis and timestamp-to-nanosecond conversions (#10786, #10666); and Flight GetFlightInfo/DoGet schema parity (#10864). See the Changelog for the full list.

Dependency Updates​

Dependency / ComponentVersion
DuckDBv1.5.2
Icebergv0.9.1
Tursov0.6.0
Vortexv0.69.0

Contributors​

Breaking Changes​

Flattened runtime.scheduler configuration (#10450): The nested runtime.scheduler.partition_management block has been flattened and renamed to use the canonical "partition assignment" terminology. Migrate as follows:

# Before
runtime:
scheduler:
partition_management:
interval: 30s
max_assignments_per_cycle: 16
discovery_timeout: 10s

# After
runtime:
scheduler:
partition_assignment_interval: 30s
max_assignments_per_interval: 16
partition_discovery_timeout: 10s

Cookbook Updates​

No new cookbook recipes.

The Spice Cookbook includes 86 recipes to help you get started with Spice quickly and easily.

Upgrading​

To upgrade to v2.0.0-rc.5, use one of the following methods:

CLI:

spice upgrade v2.0.0-rc.5

Homebrew:

brew upgrade spiceai/spiceai/spice

Docker:

Pull the spiceai/spiceai:2.0.0-rc.5 image:

docker pull spiceai/spiceai:2.0.0-rc.5

For available tags, see DockerHub.

Helm:

helm repo update
helm upgrade spiceai spiceai/spiceai --version 2.0.0-rc.5

AWS Marketplace:

Spice is available in the AWS Marketplace.

What's Changed​

Changelog​

  • Enable DML support for PostgreSQL data connector by @phillipleblanc in #10446
  • feat(postgres): support inline PEM sslrootcert by @claudespice in #10578
  • Add foreign key metadata discovery to PostgreSQL Catalog by @sgrebnov in #10849
  • Add Snowflake DML support by @lukekim in #10747
  • Add MongoDB Change Streams support by @lukekim in #10813
  • Add user-defined functions by @lukekim in #10571
  • Add table user functions and gate HTTP servers by @lukekim in #10675
  • feat: add on-demand dataset loading by @phillipleblanc in #10629
  • feat(runtime): declared-schema deferred datasets by @phillipleblanc in #10669
  • feat(spicepod, runtime): add columns[].type / nullable + lenient type parser by @phillipleblanc in #10661
  • Replace external smb crate with internal SMB 3.1.1 client by @phillipleblanc in #10516
  • Add unified query cancellation across all paths by @lukekim in #10390
  • Add dynamic HTTP request headers by @lukekim in #10604
  • feat(http): Support dynamic HTTP connector request params from subqueries by @lukekim in #10636
  • feat(http): pass through HTTP metadata columns with JSON schema decomposition by @lukekim in #10679
  • Add nolimit HTTP pagination max pages by @lukekim in #10673
  • Add shared HTTP rate control for connectors by @lukekim in #10648
  • Use origin label instead of name for HTTP rate control metrics by @lukekim in #10689
  • fix(http): reject OR across different HTTP filter columns by @lukekim in #10625
  • Add provider-aware LLM prompt caching by @lukekim in #10645
  • Add searchable registry mode for LLM tools by @lukekim in #10647
  • feat: refresh_mode: snapshot + SQLite/Turso WAL flush + Cayenne metastore slice by @phillipleblanc in #10651
  • feat: per-principal cache namespacing for SQL/search/caching-accelerator by @lukekim in #10702
  • Add self-hosted Spice connector support by @phillipleblanc in #10546
  • Add Delta Lake Azure tenant parameter by @phillipleblanc in #10671
  • Support OAuth2 client credentials in 'spice cloud login' by @ewgenius in #10586
  • Add configurable allowed_hosts for MCP by @lukekim in #10638
  • fix: make Helm chart probes configurable by @peasee in #10696
  • Strip high-cardinality datasets dim from anonymous telemetry by @lukekim in #10711
  • feat(elasticsearch): direct FTS engine config + index lifecycle and ingestion controls by @lukekim in #10672
  • Add DuckDB HNSW vector index support for accelerated views by @sgrebnov in #10695
  • Rewrite DuckDB vector search SQL to activate HNSW_INDEX_SCAN by @sgrebnov in #10674
  • Fix DuckDB HNSW vector indexes lost after data refresh by @sgrebnov in #10668
  • Fix DuckDB DELETE/UPDATE on full and caching refresh mode datasets by @phillipleblanc in #10632
  • Fix DuckLake connector: downcast, module registration, schema discovery, and S3 credentials by @sgrebnov in #10650
  • Fix federation pushing denied functions inside subqueries to remote engines by @phillipleblanc in #10692
  • fix(caching): honour refresh_on_startup: always in caching mode by @phillipleblanc in #10594
  • fix(iceberg): rebuild storage factory when Hadoop catalog scheme is inferred by @sgrebnov in #10601
  • Pipeline CDC ingestion: overlap source reads with batch apply by @lukekim in #10676
  • fix: add NULL check to CDC primary key extraction by @lukekim in #10684
  • Properly handle nullability during CDC processing by @krinart in #10803
  • Flatten scheduler config and rename partition management β†’ partition assignment by @lukekim in #10450
  • Improve NSQL UX and harden internal LLM tools by @lukekim in #10715
  • Support Responses API across model providers by @lukekim in #10724
  • Update xAI default model and handle Grok model retirements by @Jeadie in #10723
  • Improve cli table layout by @krinart in #10725
  • TLS cert hot-reload (mTLS plan M1) by @phillipleblanc in #10727
  • Fix DuckLake catalog include filter being ignored by @phillipleblanc in #10738
  • Promote DuckLake Catalog and Data Connector to Beta quality by @sgrebnov in #10743
  • feat(ducklake): Support INSERT on catalog tables with read_write access by @sgrebnov in #10744
  • perf(cdc): coalesce envelopes and overlap commits in apply pipeline by @lukekim in #10745
  • feat: Allow full version tags in spicepod version by @peasee in #10748
  • Add Arrow primary key upserts by @lukekim in #10749
  • fix(snapshot): keep refresh_mode snapshot read-only by @phillipleblanc in #10752
  • feat(tls): public mTLS for HTTP and Flight (channel + identity modes) by @phillipleblanc in #10753
  • perf(cayenne): lock-free deletion caches with bloom-prefiltered probe by @lukekim in #10756
  • fix(security): close API key timing-position leak and remote-UDF SSRF by @lukekim in #10757
  • Fix 'wait_until_dependent_tables_are_ready' for catalogs by @phillipleblanc in #10758
  • Fixes for views and resolved tables on 'spice refresh' CLI by @phillipleblanc in #10759
  • Implement FlightSQL CommandStatementSubstraitPlan support by @lukekim in #10761
  • feat(connectors): mTLS client cert support for flightsql and spiceai connectors by @phillipleblanc in #10764
  • Allow arbitrary filenames when specifying spicepod path + kind validation by @krinart in #10777
  • fix: ignore field metadata in schema compatibility check in index_table_scan by @Jeadie in #10778
  • Display pushed-down limits in EXPLAIN TREE output by @lukekim in #10779
  • fix: enable streaming append for Kafka with Cayenne accelerator by @lukekim in #10780
  • fix: bound chunked-index intermediate batch size to prevent OOM by @phillipleblanc in #10783
  • fix: label all columns in spice cloud metrics table output by @claudespice in #10784
  • fix: use checked arithmetic for Turso integer-millis timestamp read path by @claudespice in #10786
  • fix: use checked arithmetic in timestamp-to-nanosecond conversions by @claudespice in #10666
  • Upgrade to DuckDB v1.5.2 by @sgrebnov in #10788
  • Improve CDC ingestion performance by @lukekim in #10789
  • Fix tool_search/tool_invoke spans by @lukekim in #10791
  • Add Cayenne inline mutations and benchmark coverage by @lukekim in #10792
  • Ensure we always resolve table names in distributed mode/metadata by @Jeadie in #10793
  • Remove permanent errors from DynamoDB Streams by @krinart in #10794
  • Add expanded view mode for wide table display in SQL REPL by @lukekim in #10797
  • Fix Cayenne CDC schema mismatch error by @sgrebnov in #10800
  • Executors should create catalog tables on join by @Jeadie in #10807
  • Add compressed file support for listing connectors by @lukekim in #10809
  • Improve Cayenne mutation, scan, and inline memtable scaling by @lukekim in #10811
  • Add range fallback for large join filters by @lukekim in #10816
  • Improve Cayenne join filter pushdown by @lukekim in #10818
  • Synchronize Cayenne partition commits across partitions by @phillipleblanc in #10819
  • fix: Deny nondistributed cayenne catalog by @peasee in #10821
  • Enable parallel Cayenne Vortex writes by @lukekim in #10822
  • Expand Arrow type handling in formatting and Elasticsearch by @lukekim in #10825
  • Add response.output_text.delta to responses API by @krinart in #10828
  • feat(cayenne): add join filter propagation and no-spill Q21 planning by @lukekim in #10840
  • Upgrade Turso to v0.6.0 by @sgrebnov in #10843
  • feat(cli): add spice feedback command to open community Slack by @lukekim in #10856
  • Upgrade iceberg to v0.9.1 by @sgrebnov in #10859
  • feat(cluster): per-request executor readiness gate on /v1/ready by @phillipleblanc in #10860
  • fix: Require dim-side statistics for CayennePropagateFilterAcrossEquiJoinKeys by @sgrebnov in #10863
  • fix: Debezium schema evolution breaks dataset init on reload by @claudespice in #10144
  • fix(mssql): Push topK limit to SQL Server for non-nullable sort columns by @Jeadie in #10621
  • fix(ScyllaDB): disable physical filter pushdown by @sgrebnov in #10772
  • fix: handle typed NULLs and prevent overflow in DynamoDB DML type conversions by @krinart in #10511
  • fix: use InsertOp::Overwrite in DynamoDB bootstrap scan_and_overwrite_accelerator by @krinart in #10639
  • Improve DynamoDB Bootstrap performance by @krinart in #10616
  • fix: preserve field and schema metadata in Vortex type transformation by @lukekim in #10628
  • fix: GH connector - explicitly use AWS LC RS crypto provider for jwt by @phillipleblanc in #10619
  • fix: add snapshot mode guards to delete_from/update and delegate DML in SwappableTableProvider by @phillipleblanc in #10685
  • Persist HTTP rate-control state in object storage by @lukekim in #10697
  • Rate limit metrics HTTP endpoint by @lukekim in #10162
  • feat(geo): add optional spatial SQL UDF support by @lukekim in #10833
  • feat(cayenne): CDC throughput, compaction, scan caching, and benchmarks by @lukekim in #10852
  • fix(cayenne): fix Vortex panic on highly compressible data by @sgrebnov in #10855
  • fix(cayenne): Read live protected snapshots after cleanup grace period by @sgrebnov in #10901
  • fix: Disable Cayenne HashJoin rewriter optimizer by @sgrebnov in #10882
  • Fix GetFlightInfo vs DoGet Flight Schema by @krinart in #10864
  • fix(search): preserve column casing in /v1/search primary key plumbing by @claudespice in #10909
  • fix(object-store): dedupe s3 url style auto-detection log by @phillipleblanc in #10898
  • Improve Spice CLI manifest editing and direct command modes by @lukekim in #10815
  • Persist Kafka CDC offsets in sidecar tables by @lukekim in #10823
  • feat(task-history): record Ballista stages for distributed queries by @phillipleblanc in #10831
  • Add '#[deny(clippy::missing_trait_methods)]' to wrapper/delegation trait impls by @Jeadie in #10795
  • Optimize Cayenne catalog maintenance paths by @lukekim in #10904
  • Centralize DuckDB settings for accelerator by @ewgenius in #10895
  • deps(ballista): bump to 47e2b494 to fix S3 shuffle reads under cluster mode by @phillipleblanc in #10910
  • Authorization header + Bump async-openai + responses_adapter fix by @krinart in #10911
  • Tune accelerators by storage profile by @lukekim in #10913
  • feat: add dataset-level on_schema_change config by @lukekim in #10908
  • Handle NULL sentinel for nullable partition expressions by @Jeadie in #10880
  • fix: Remove Cayenne Catalog from catalog registration by @peasee in #10914
  • Add catalog name to foreign key metadata in postgres catalog by @Jeadie in #10917
  • Cayenne perf: eliminate redundant clones, PK point-lookup fanout fix, IN-list rewrite + microbench coverage by @lukekim in #10916
  • fix(turso-shared): retry on Turso BEGIN CONCURRENT "Write-write conflict" by @lukekim in #10946
  • Vendor Vortex DataFusion for Cayenne by @lukekim in #10933
  • perf(cayenne): background retention + enable CDC pipelining for retention-configured tables by @lukekim in #10936
  • feat(cayenne): scale metastore pool to 32 + vs_duckdb_scaling benches (1β†’128 concurrency, sqlite + turso lanes) by @lukekim in #10943
  • feat(mcp): support auth for streamable HTTP tools by @phillipleblanc in #10927
  • Explicit error if v1/search requests a table without search index by @Jeadie in #10968
  • Fix spicepod loading failure when directory name contains dots by @sgrebnov in #10958
  • Extend append tests with arrow engine configurations by @sgrebnov in #10959
  • Remove dataset on_schema_change Policy from rc.5 release notes by @sgrebnov in #10964
  • Skip tpcds_q78 for Cayenne engine at SF100 by @sgrebnov in #10966
  • fix: Update benchmark snapshots May-20 by @app/github-actions in #10952
  • Fix #10951: UdtfExec invariant Vec lengths must match children count by @phillipleblanc in #10953
  • docs(release): update v2.0.0-rc.5 notes with latest trunk PRs by @lukekim in #10949
  • Remove eval related things for v2.0.0 by @Jeadie in #10945
  • build(deps): bump ubuntu from 24.04 to 26.04 in the docker-dependencies group by @app/dependabot in #10883
  • fix: Add publish = false to chbench-driver by @sgrebnov in #10939

Full Changelog: https://github.com/spiceai/spiceai/compare/v2.0.0-rc.4...v2.0.0-rc.5

Spice v2.0-rc.3 (Apr 21, 2026)

Β· 13 min read
Evgenii Khramkov
Senior Software Engineer at Spice AI

Announcing the release of Spice v2.0-rc.3! ⚑

v2.0.0-rc.3 is the third release candidate for advanced testing of v2.0, building on v2.0.0-rc.2.

Highlights in this release candidate include:

  • HTTP Connector Enhancements with OAuth2 refresh-token authentication, query-parameter pagination, and map-to-array conversion for broader API compatibility
  • Databricks and Unity Catalog Reliability Improvements with resilience controls, improved UC-awareness, permission checks, and structured error reporting
  • Snowflake and ADBC Registration Performance Improvements with better observability during dataset registration
  • OpenTelemetry Exporter Improvements with exporter fixes and support for authenticated metrics export
  • Kafka, GitHub, and HTTP Connector Fixes including Kafka reliability improvements, GitHub GraphQL resilience updates, and HTTP JSON union/reload fixes

What's New in v2.0.0-rc.3​

HTTP Connector Enhancements​

The HTTP connector now supports more authentication and API response patterns, making it easier to integrate with modern REST APIs.

Key improvements:

  • OAuth2 Refresh-Token Authentication: Added support for OAuth2 refresh-token flows for APIs that issue short-lived access tokens.
  • Query-Parameter Pagination: Added pagination support using query parameters for APIs that expose page or cursor controls in the URL.
  • Map-to-Array Conversion: Added response transformation support for APIs that return map-shaped payloads that need to be normalized into arrays.
  • Improved JSON Union Handling: Better handling for heterogeneous JSON payloads during ingestion.
  • More Reliable Reloads: Fixed runtime behavior for HTTP-backed datasets during spicepod reloads.

Example configuration of an HTTP connector using the OAuth2 refresh token flow:

datasets:
- from: https://api.example.com
name: secure_data
params:
file_format: json
allowed_request_paths: '/v1/**'
auth_token_url: https://auth.example.com/oauth/token
http_auth_refresh_token: ${secrets:my_refresh_token}
http_auth_client_id: ${secrets:my_client_id}
http_auth_client_secret: ${secrets:my_client_secret}
auth_scopes: 'read:data offline_access'

Databricks and Unity Catalog Reliability Improvements​

Databricks and Unity Catalog integrations are now more resilient and provide clearer behavior in permission-constrained environments.

Key improvements:

  • Resilience Controls: Added controls to improve reliability when interacting with Databricks services.
  • Unity Catalog Awareness: Improved handling for Unity Catalog-specific behaviors and mixed deployment configurations.
  • Permission Prechecks: Databricks UC permission checks now distinguish explicit denials from ambiguous cases.
  • Structured Error Reporting: Advisory permission failures now surface with more actionable structured errors.
  • Classic SQL Warehouse Compatibility: Improved handling for foreign table scenarios with Classic SQL Warehouse combinations.
  • Task History Instrumentation: Added instrumentation to improve observability for Databricks-related operations.

Snowflake and ADBC Improvements​

Snowflake and ADBC-backed dataset registration is now faster and easier to observe.

Key improvements:

  • Faster Dataset Registration: Improved registration performance for Snowflake and ADBC datasets.
  • Better Observability: Added better instrumentation and visibility into registration workflows.
  • ADBC Alignment: Updated ADBC dependencies and integration points for improved compatibility.
  • Search Schema Fix: Fixed a full-text search schema mismatch issue with the ADBC connector.

OpenTelemetry and Observability Improvements​

Spice improves telemetry export reliability and authenticated metrics delivery for the OpenTelemetry integration.

Key improvements:

  • OTEL Exporter Fixes: Fixed issues in the OpenTelemetry exporter.
  • Authenticated Metrics Export: Added support for authorization headers in the OTEL metrics exporter.
  • Reduced Startup Noise: Suppressed unnecessary AWS SDK noise and improved OTEL-related initialization behavior.
  • Connector Initialization Reliability: Fixed issues that could block connector initialization in telemetry-related code paths.

Dependency and Toolchain Updates​

Dependency / ComponentVersion / Update
Rust toolchainv1.94.1 (from v1.93.1)
DataFusionv52.5.0-rc1
mistral.rs / candlemistral.rs v0.8.x, candle v0.10.1
ADBC Corev0.23

Other Improvements​

  • Improved Query Pushdown: Expanded sort and limit pushdown, including improved pushdown behavior for Oracle and MSSQL connectors.
  • Partitioned Query Planning Improvements: Improved PartitionedTableScanRewrite handling for ORDER BY, partition expressions, and fully qualified table references, while preventing incorrect bucketing partition pushdown to executors.
  • MongoDB SRV Support: Upgraded datafusion-table-providers with MongoDB SRV support.
  • Tantivy Logging: Search logging now defaults to warn unless very verbose logging is enabled.
  • Kafka Connector Fixes: Improved reliability for the Kafka connector behavior.
  • GitHub Connector Resilience: Improved commit fetching for dynamic and slash refs, and reduced GraphQL page sizes on gateway errors for the GitHub connector.
  • GitHub API Efficiency: Lowered default comment fetch sizes to reduce pressure on GitHub GraphQL APIs.
  • Embedding Validation: Added validation for embedding row_id columns during dataset initialization.
  • View Cache Invalidation: Cached plans are now cleared when views are updated.
  • Refresh SQL Dedup Fix: Fixed append refresh deduplication when refresh_sql selects a subset of columns.

Contributors​

Breaking Changes​

No breaking changes.

Cookbook Updates​

No new cookbook recipes.

The Spice Cookbook includes 86 recipes to help you get started with Spice quickly and easily.

Upgrading​

To upgrade to v2.0.0-rc.3, use one of the following methods:

CLI:

spice upgrade v2.0.0-rc.3

Homebrew:

brew upgrade spiceai/spiceai/spice

Docker:

Pull the spiceai/spiceai:2.0.0-rc.3 image:

docker pull spiceai/spiceai:2.0.0-rc.3

For available tags, see DockerHub.

Helm:

helm repo update
helm upgrade spiceai spiceai/spiceai --version 2.0.0-rc.3

AWS Marketplace:

Spice is available in the AWS Marketplace.

What's Changed​

Changelog​

  • fix: Full Text Search schema mismatch with ADBC connector by @lukekim in #10235
  • docs: Update v2.0.0-rc.2 release notes with latest changes by @lukekim in #10238
  • Fix append refresh dedup failure when refresh_sql selects column subset by @sgrebnov in #10225
  • Revert "Properly mark dataset as Ready on Scheduler (#10215)" by @sgrebnov in #10242
  • Fix failing merge conflicts for benchmarks by @krinart in #10247
  • fix(github): fetch commits for dynamic and slash refs by @lukekim in #10233
  • Upgrade DataFusion to v52.5.0-rc1 by @lukekim in #10249
  • Merge develop to trunk (2026-04-09) by @claudespice in #10248
  • fix: Validate embedding row_id columns during dataset init (fixes #8226) by @claudespice in #10208
  • fix: Update tpch benchmark snapshots for federated/glue[csv].yaml by @app/github-actions in #10244
  • feat(databricks): add resilience controls, UC awareness, and task history instrumentation by @lukekim in #10246
  • fix: Make PartitionManager resilient to bare vs fully qualified table references by @sgrebnov in #10257
  • fix: Update tpch benchmark snapshots for accelerated/s3[parquet]-cayenne[file].yaml by @app/github-actions in #10256
  • Merge develop to trunk (2026-04-10) by @claudespice in #10251
  • Improve Snowflake/ADBC dataset registration performance and observability by @lukekim in #10266
  • Fixes for kafka connector by @krinart in #10263
  • fix(runtime): gate otel code tags, suppress aws sdk noise, and unblock connector init by @lukekim in #10260
  • fix(runtime): avoid regionless AWS SDK loads by @lukekim in #10271
  • Add versioned release install workflow coverage by @lukekim in #10276
  • fix(runtime): handle HTTP JSON unions and spicepod reloads by @lukekim in #10277
  • Databricks UC permission prechecks: explicit denial as permanent error, ambiguous cases advisory by @lukekim in #10274
  • Revert component status changes re-introduced by develop merge (#10248) by @sgrebnov in #10293
  • Fix broken CI workflows by @ewgenius in #10294
  • Group dependabot updates by ecosystem by @lukekim in #10296
  • fix(tests): Replace flaky S3 Vectors snapshot tests with structural validation by @lukekim in #10301
  • Update test_github_workflows snapshot by @lukekim in #10304
  • fix(ci): fix Bedrock runner mismatch and snapshot auto-merge failure by @ewgenius in #10306
  • feat(http): Add map-to-array conversion and query-parameter pagination by @lukekim in #10295
  • New crate: datafusion-ddl by @Jeadie in #10205
  • Make Databricks UC permission checks advisory with structured error reporting by @lukekim in #10283
  • build(deps): bump the github-actions-dependencies group with 4 updates by @app/dependabot in #10298
  • fix: Clear cached plans on view updates by @peasee in #10312
  • build(deps): bump the aws-sdk group with 7 updates by @app/dependabot in #10299
  • Code out of runtime. by @Jeadie in #10178
  • fix: Respect function registry denies for accelerated table filter pushdown by @peasee in #10311
  • fix: Don't block heartbeat when all slots acquired by @peasee in #10322
  • fix: strip only outer parens in get_table_partition_expr_from_ctx by @Jeadie in #10323
  • Upgrade datafusion-table-providers with MongoDB SRV support by @lukekim in #10317
  • fix: Avoid pushing down bucketing partition expressions into executors by @peasee in #10324
  • Upgrade datafusion-table-providers to d1b911a5 and bump adbc to 0.23 by @lukekim in #10329
  • fix: Update Search integration test snapshots by @app/github-actions in #10308
  • Handle foreign table + Classic sql warehouse combination gracefully by @krinart in #10318
  • New crate datafusion-flightsql by @Jeadie in #10201
  • Set tantivy=warn unless very verbose logging by @Jeadie in #10338
  • Remove image registry and image name options from spidapter by @ewgenius in #10241
  • build(deps): bump sysinfo from 0.37.2 to 0.38.4 by @app/dependabot in #10291
  • build(deps): bump futures from 0.3.31 to 0.3.32 by @app/dependabot in #10289
  • New crate 'datafusion-dml' by @Jeadie in #10334
  • Jeadie/26 04 16/spice sql by @Jeadie in #10343
  • Add Teraswitch/Pittsburgh apt mirrors + retry config for CI runners by @lukekim in #10349
  • Implement sort pushdown and fix pushdown gaps across providers by @lukekim in #10337
  • Merge develop to trunk (2026-04-16) by @claudespice in #10345
  • Update candle and mistral.rs lock-step pins by @lukekim in #10278
  • docs: fix status badges in README by @lukekim in #10350
  • Migrate secrets to vars by @krinart in #10354
  • Add limit pushdown and improve sort pushdown for Oracle and MSSQL by @sgrebnov in #10351
  • Fix ubuntu mirror configuration by @ewgenius in #10359
  • fix: Increase throughput test default ready_wait from 30s to 300s (fixes #8207) by @claudespice in #10344
  • Add auth headers support to OTEL metrics exporter by @lukekim in #10347
  • fix(github): shrink GraphQL page size on gateway errors; lower comment defaults by @lukekim in #10355
  • Relax apt mirror substitution failure to warning in CI action by @ewgenius in #10361
  • feat(http): Add OAuth2 refresh-token auth to HTTP connector by @lukekim in #10348
  • Upgrade Rust toolchain to 1.94.1 by @lukekim in #10353
  • Handle order by and sort in PartitionedTableScanRewrite by @Jeadie in #9656
  • Fix OTEL Exporter by @krinart in #10363
  • Pin spiceai candle / TEI forks to merged revs; drop local [patch] overrides by @lukekim in #10362

Full Changelog: https://github.com/spiceai/spiceai/compare/v2.0.0-rc.2...v2.0.0-rc.3

Spice v1.10.4 (Jan 5, 2026)

Β· 2 min read
Phillip LeBlanc
Co-Founder and CTO of Spice AI

Announcing the release of Spice v1.10.4! πŸ› οΈ

v1.10.4 is a patch release with fixes for Kafka/Debezium batch commits, ABFSS URL support for Azure Data Lake Storage Gen2, and improved column projection handling for location metadata columns.

What's New in v1.10.4​

Additional Improvements & Bug Fixes​

  • Reliability: Fixed Kafka and Debezium batch commit handling to properly commit offsets across all partitions. Previously, only the last message's offset was committed, which could cause message loss when batches contained messages from multiple partitions.
  • Reliability: Added support for abfss:// URL prefix for Azure Data Lake Storage Gen2, in addition to the existing abfs:// prefix. The abfss scheme indicates secure (TLS) connections to ADLS Gen2.
  • Reliability: Fixed column projection order mismatch when querying datasets with location metadata columns (e.g., SELECT location, day, size FROM dataset). Queries that specified columns in a different order than the schema would fail with "column types must match schema types" errors.
  • Developer Experience: Added detailed diagnostic logging for union projection pushdown optimization failures in cluster mode. When projection pushdown cannot be applied, debug-level logs now provide additional context to help identify the root cause.

Contributors​

Breaking Changes​

No breaking changes.

Cookbook Updates​

No major cookbook updates.

The Spice Cookbook includes 84 recipes to help you get started with Spice quickly and easily.

Upgrading​

To upgrade to v1.10.4, use one of the following methods:

CLI:

spice upgrade

Homebrew:

brew upgrade spiceai/spiceai/spice

Docker:

Pull the spiceai/spiceai:1.10.4 image:

docker pull spiceai/spiceai:1.10.4

For available tags, see DockerHub.

Helm:

helm repo update
helm upgrade spiceai spiceai/spiceai

AWS Marketplace:

πŸŽ‰ Spice is now available in the AWS Marketplace!

What's Changed​

Changelog​

Spice v1.10.2 (Dec 22, 2025)

Β· 5 min read
Sergei Grebnov
Senior Software Engineer at Spice AI

Announcing the release of Spice v1.10.2! πŸ”₯

v1.10.2 introduces Tiered Caching Acceleration with Localpod for multi-layer acceleration architectures, Periodic Acceleration Snapshots with configurable intervals, DynamoDB JSON Nesting for column consolidation, and Kafka/Debezium Batching for faster data ingestion. This release also includes fixes for SQLite accelerator decimal/date handling and real-time status reporting for the /v1/datasets and /v1/models API endpoints.

What's New in v1.10.2​

Tiered Caching with Localpod​

Multi-Layer Acceleration Architecture: The Localpod connector now supports caching refresh mode, enabling tiered acceleration where a persistent cache (e.g., file-mode DuckDB) feeds a fast in-memory cache (e.g., Arrow, memory-mode DuckDB).

Key Features:

  • Automatic Cache Propagation: New cache entries automatically propagate from parent to child accelerators
  • Warm Startup: Child accelerators initialize from existing parent data on startup, eliminating cold-start latency
  • Flexible Tiering: Combine any accelerator engines (DuckDB, SQLite, Cayenne) across tiers

Example spicepod.yaml configuration:

datasets:
# Parent: persistent file-mode cache
- from: https://api.example.com
name: api_cache
acceleration:
enabled: true
refresh_mode: caching
engine: duckdb
mode: file

# Child: fast in-memory cache fed by parent
- from: localpod:api_cache
name: api_cache_memory
acceleration:
enabled: true
refresh_mode: caching
engine: arrow
mode: memory

For more details, refer to the Localpod Data Connector Documentation.

Periodic Acceleration Snapshots​

Configurable Snapshot Intervals: A new snapshots_create_interval parameter enables periodic snapshot creation for accelerated datasets across all refresh modes. This provides better control over snapshot frequency and ensures consistent recovery points for accelerated data.

Example spicepod.yaml configuration:

datasets:
- from: s3://my-bucket/data.parquet
name: my_data
acceleration:
enabled: true
engine: duckdb
mode: file
refresh_mode: caching
snapshots: enabled
params:
snapshots_create_interval: 60s # Write a snapshot every 60 seconds

For more details, refer to the Data Acceleration Documentation.

DynamoDB JSON Nesting​

Consolidate Columns into JSON: The DynamoDB Data Connector now supports consolidating columns into a single JSON column using the json_object: "*" metadata option. This is useful when only a few columns are needed as discrete fields while the rest can be accessed as nested JSON.

Example spicepod.yaml configuration:

datasets:
- from: dynamodb:my_table
name: my_table
columns:
- name: PK
- name: SK
- name: data_json
metadata:
json_object: '*' # Captures all other columns as JSON

Example Output: Given a DynamoDB table with columns PK, SK, name, email, and status, the resulting table schema consolidates all non-specified columns into the data_json column:

PKSKdata_json
pk_1sort_1{"name": "Alice", "email": "alice@example.com", "status": "active"}
pk_2sort_2{"name": "Bob", "email": "bob@example.com", "status": "inactive"}

For more details, refer to the DynamoDB JSON Nesting Documentation.

Kafka/Debezium Batching​

Faster Data Ingestion: Configure message batching for Kafka and Debezium connectors to improve data ingestion throughput. Batching reduces processing overhead by grouping multiple messages together before insertion.

Key Features:

  • Configurable Batch Size: Control the maximum number of records per batch (default: 10,000)
  • Configurable Batch Duration: Set the maximum wait time before flushing a partial batch (default: 1s)

Example spicepod.yaml configuration:

datasets:
- from: debezium:kafka-server.public.my_table
name: my_table
params:
batch_max_size: 10000 # Max records per batch (default: 10000)
batch_max_duration: 1s # Max wait time per batch (default: 1s)

For more details, refer to the Kafka Data Connector Documentation and Debezium Data Connector Documentation.

Additional Improvements & Bug Fixes​

  • Reliability: Fixed SQLite accelerator decimal and date type handling for improved data type accuracy.
  • Reliability: Fixed real-time status reporting for /v1/datasets and /v1/models API endpoints.
  • Reliability: Fixed Kafka warning when security.protocol is set to PLAINTEXT.

Contributors​

Breaking Changes​

No breaking changes.

Cookbook Updates​

New Cayenne Data Accelerator Recipe: New recipe demonstrating how to accelerate a local copy of the taxi trips dataset using Cayenne as the data accelerator engine. See Cayenne Data Accelerator Recipe for details.

New Dataset Partitioning Recipe: New recipe demonstrating how to partition accelerated datasets to improve query performance. See Dataset Partitioning for details.

The Spice Cookbook includes 84 recipes to help you get started with Spice quickly and easily.

Upgrading​

To upgrade to v1.10.2, use one of the following methods:

CLI:

spice upgrade

Homebrew:

brew upgrade spiceai/spiceai/spice

Docker:

Pull the spiceai/spiceai:1.10.2 image:

docker pull spiceai/spiceai:1.10.2

For available tags, see DockerHub.

Helm:

helm repo update
helm upgrade spiceai spiceai/spiceai

AWS Marketplace:

πŸŽ‰ Spice is now available in the AWS Marketplace!

What's Changed​

Changelog​

Spice v1.6.1 (Sep 1, 2025)

Β· 3 min read
Jack Eadie
Token Plumber at Spice AI

Announcing the release of Spice v1.6.1! ⚑

Spice 1.6.1 is a patch release that provides improved Kafka type inference and JSON flattening support, alongside several bug fixes.

What's New in v1.6.1​

Improved Kafka Type Inference: Improve Kafka type inference by configuring the number of Kafka messages sampled during schema inference. Increasing the sample size can improve the robustness and reliability of inferred schemas, especially in cases where data contains optional fields or varying structures.

Example spicepod.yml:

dataset:
- from: kafka:orders_events
name: orders
params:
schema_infer_max_records: 100 # Default 1.

For details, see the Kafka Data Connector Documentation.

Improved Kafka JSON Support: Enable nested JSON Kafka messages to be represented in flattened JSON format for the dataset schema.

Example spicepod.yml:

dataset:
- from: kafka:orders_events
name: orders
params:
flatten_json: true # default false

For example, the object:

{
"order_id": "a1f2c3d4-1111-2222-3333-444455556666",
"customer": {
"id": 101,
"name": "Alice",
"premium": true,
"contact": {
"email": "alice@example.com",
"phone": "555-1234"
}
},
"discount": 5.0,
"shipped": false
}

With flatten_json: true the result is:

+------------------------+-----------+-------------+
| column_name | data_type | is_nullable |
+------------------------+-----------+-------------+
| order_id | Utf8 | YES |
| customer.id | Int64 | YES |
| customer.name | Utf8 | YES |
| customer.premium | Boolean | YES |
| customer.contact.email | Utf8 | YES |
| customer.contact.phone | Utf8 | YES |
| discount | Float64 | YES |
| shipped | Boolean | YES |
+------------------------+-----------+-------------+

With flatten_json: false or ommitted the result is:

+-------------+------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------+-------------+
| column_name | data_type | is_nullable |
+-------------+------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------+-------------+
| order_id | Utf8 | YES |
| customer | Struct([Field { name: "id", data_type: Int64, nullable: true, dict_id: 0, dict_is_ordered: false, metadata: {} }, Field { name: "name", data_type: Utf8, nullable: true, dict_id: 0, dict_is_ordered: false, metadata: {} }, Field { name: "premium", data_type: Boolean, nullable: true, dict_id: 0, dict_is_ordered: false, metadata: {} }, Field { name: "contact", data_type: Struct([Field { name: "email", data_type: Utf8, nullable: true, dict_id: 0, dict_is_ordered: false, metadata: {} }, Field { name: "phone", data_type: Utf8, nullable: true, dict_id: 0, dict_is_ordered: false, metadata: {} }]), nullable: true, dict_id: 0, dict_is_ordered: false, metadata: {} }]) | YES |
| discount | Float64 | YES |
| shipped | Boolean | YES |
+-------------+------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------+-------------+

For details, see the Kafka Data Connector Documentation.

Contributors​

Breaking Changes​

No breaking changes.

Cookbook Updates​

No new cookbook recipes added in this release.

The Spice Cookbook includes 77 recipes to help you get started with Spice quickly and easily.

Upgrading​

To upgrade to v1.6.1, use one of the following methods:

CLI:

spice upgrade

Homebrew:

brew upgrade spiceai/spiceai/spice

Docker:

Pull the spiceai/spiceai:1.6.1 image:

docker pull spiceai/spiceai:1.6.1

For available tags, see DockerHub.

Helm:

helm repo update
helm upgrade spiceai spiceai/spiceai

AWS Marketplace:

πŸŽ‰ Spice is now available in the AWS Marketplace!

What's Changed​

Changelog​

  • Fix metadata field issue by @Advayp in #6957
  • Update datafusion and datafusion-table-providers crates (#6985) by @Jeadie in #6985
  • Add flatten_json param support for Kafka connector (#6976) by @sgrebnov in #6976
  • Add schema_inference_sample_count param support for Kafka connector (#6969) by @sgrebnov in #6969
  • Add integration test for Kafka connector (#6965) by @sgrebnov in #6965
  • Skip dataset health check for IcebergTableProvider datasets by @phillipleblanc in #6995

Spice v1.6.0 (Aug 26, 2025)

Β· 22 min read
Sergei Grebnov
Senior Software Engineer at Spice AI

Announcing the release of Spice v1.6.0! πŸ”₯

Spice 1.6.0 upgrades DataFusion to v48, reducing expressions memory footprint by ~50% for faster planning and lower memory usage, eliminating unnecessary projections in queries, optimizing string functions like ascii and character_length for up to 3x speedup, and accelerating unbounded aggregate window functions by 5.6x. The release adds Kafka and MongoDB connectors for real-time streaming and NoSQL data acceleration, supports OpenAI Responses API for advanced model interactions including OpenAI-hosted tools like web_search and code_interpreter, improves the OpenAI Embeddings Connector with usage tier configuration for higher throughput via increased concurrent requests, introduces Model2Vec embeddings for ultra-low-latency encoding, and improves the Amazon S3 Vectors engine to support multi-column primary keys.

What's New in v1.6.0​

DataFusion v48 Highlights​

Spice.ai is built on the DataFusion query engine. The v48 release brings:

Performance & Size Improvements πŸš€: Expressions memory footprint was reduced by ~50% resulting in faster planning and lower memory usage, with planning times improved by 10-20%. There are now fewer unnecessary projections in queries. The string functions, ascii and character_length were optimized for improved performance, with character_length achieving up to 3x speedup. Queries with unbounded aggregate window functions have improved performance by 5.6 times via avoided unnecessary computation for constant results across partitions. The Expr struct size was reduced from 272 to 144 bytes.

New Features & Enhancements ✨: Support was added for ORDER BY ALL for easy ordering of all columns in a query.

See the Apache DataFusion 48.0.0 Blog for details.

Runtime Highlights​

Amazon S3 Vectors Multi-Column Primary Keys: The Amazon S3 Vectors engine now supports datasets with multi-column primary keys. This enables vector indexes for datasets where more than one column forms the primary key, such as those splitting documents into chunks for retrieval contexts. For multi-column keys, Spice serializes the keys using arrow-json format, storing them as single string keys in the vector index.

Model2Vec Embeddings: Spice now supports model2vec static embeddings with a new model2vec embeddings provider, for sentence transformers up to 500x faster and 15x smaller, enabling scenarios requiring low latency and high-throughput encoding.

embeddings:
- from: model2vec:minishlab/potion-base-8M # HuggingFace model
name: potion
- from: model2vec:path/to/my/local/model # local model
name: local

Learn more in the Model2Dev Embeddings documentation.

Kafka Data Connector: Use from: kafka:<topic> to ingest data directly from Kafka topics for integration with existing Kafka-based event streaming infrastructure, providing real-time data acceleration and query without additional middleware.

Example Spicepod.yml:

- from: kafka:orders_events
name: orders
acceleration:
enabled: true
refresh_mode: append
params:
kafka_bootstrap_servers: server:9092

Learn more in the Kafka Data Connector documentation.

MongoDB Data Connector: Use from: mongodb:<dataset> to access and accelerate data stored in MongoDB, deployed on-premises or in the cloud.

Example spicepod.yml:

datasets:
- from: mongodb:my_dataset
name: my_dataset
params:
mongodb_host: localhost
mongodb_db: my_database
mongodb_user: my_user
mongodb_pass: password

Learn more in the MongoDB Data Connector documentation.

OpenAI Responses API Support: The OpenAI Responses API (/v1/responses) is now supported, which is OpenAI's most advanced interface for generating model responses.

To enable the /v1/responses HTTP endpoint, set the responses_api parameter to enabled:

Example spicepod.yml:

models:
- name: openai_model_using_responses_api
from: openai:gpt-4.1
params:
openai_api_key: ${ secrets:OPENAI_API_KEY }
responses_api: enabled # Enable the /v1/responses endpoint for this model

Example curl request:

curl http://localhost:8090/v1/responses \
-H "Content-Type: application/json" \
-d '{
"model": "gpt-4.1",
"input": "Tell me a three sentence bedtime story about Spice AI."
}'

To use responses in spice chat, use the --responses flag.

Example:

spice chat --responses # Use the `/v1/responses` endpoint for all completions instead of `/v1/chat/completions`

Use OpenAI-hosted tools supported by Open AI's Responses API by specifying the openai_responses_tools parameter:

Example spicepod.yml:

models:
- name: test
from: openai:gpt-4.1
params:
openai_api_key: ${ secrets:SPICE_OPENAI_API_KEY }
tools: sql, list_datasets
responses_api: enabled
openai_responses_tools: web_search, code_interpreter # 'code_interpreter' or 'web_search'

These OpenAI-specific tools are only available from the /v1/responses endpoint. Any other tools specified via the tools parameter are available from both the /v1/chat/completions and /v1/responses endpoints.

Learn more in the OpenAI Model Provider documentation.

OpenAI Embeddings & Models Connectors Usage Tier: The OpenAI Embeddings and Models Connectors now supports specifying account usage tier for embeddings and model requests, improving the performance of generating text embeddings or calling models during dataset load and search by increasing concurrent requests.

Example spicepod.yml:

embeddings:
- from: openai:text-embedding-3-small
name: openai_embed
params:
openai_usage_tier: tier1

By setting the usage tier to the matching usage tier for your OpenAI account, the Embeddings and Models Connector will increase the maximum number of concurrent requests to match the specified tier.

Learn more in the OpenAI Model Provider documentation.

Contributors​

New Contributors​

Breaking Changes​

No breaking changes.

Cookbook Updates​

The Spice Cookbook includes 77 recipes to help you get started with Spice quickly and easily.

Upgrading​

To upgrade to v1.6.0, use one of the following methods:

CLI:

spice upgrade

Homebrew:

brew upgrade spiceai/spiceai/spice

Docker:

Pull the spiceai/spiceai:1.6.0 image:

docker pull spiceai/spiceai:1.6.0

For available tags, see DockerHub.

Helm:

helm repo update
helm upgrade spiceai spiceai/spiceai

AWS Marketplace:

πŸŽ‰ Spice is also now available in the AWS Marketplace!

What's Changed​

Dependencies​

Changelog​

  • Support Streaming with Tool Calls (#6941) by @Advayp in #6941
  • Fix parameterized query planning in DataFusion (#6942) by @Jeadie in #6942
  • Update the UnableToLoadCredentials error with a pointer to docs (#6937) by @phillipleblanc in #6937
  • Fix spicecloud benchmark (#6935) by @krinart in #6935
  • [Debezium] Support for VariableScaleDecimal (#6934) by @krinart in #6934
  • Update to DF 48 (#6665) by @mach-kernel and @kczimm in #6665
  • Mark append-stream and CDC datasets as ready after first message (#6914) by @sgrebnov in #6914
  • Model2Vec embedding model support (#6846) by @mach-kernel in #6846
  • Update snapshot for S3 vector search test (#6920) by @Jeadie in #6920
  • remove [] from queryset in spicepod path for CI (#6919) by @Jeadie in #6919
  • Remove verbose tracing (#6915) by @Jeadie in #6915
  • Refactor how models supporting the Responses API are loaded (#6912) by @Advayp in #6912
  • Write tests for truncate formatting in arrow_tools and fix bug. (#6900) by @Jeadie in #6900
  • Support using the Responses API from spice chat (#6894) by @Advayp in #6894
  • Include GPT-5 into Text-To-SQL and Financebench benchmarks (#6907) by @sgrebnov in #6907
  • Better error message when credentials aren't loaded for S3 Vectors (#6910) by @phillipleblanc in #6910
  • Add tracing and system prompt support for the Responses API (#6893) by @Advayp in #6893
  • Constraint violation check is improved to control behavior when violations occur within a batch (#6897) by @phillipleblanc in #6897
  • fix: Multi-column text search with v1/search (#6905) by @peasee in #6905
  • fix: Correctly project text search primary keys to underlying projection (#6904) by @peasee in #6904
  • fix: Update benchmark snapshots (#6901) by @app/github-actions in #6901
  • In S3vector, do not pushdown on non-filterable columns (#6884) by @Jeadie in #6884
  • Run E2E Test CI macOS build on bigger runners (#6896) by @phillipleblanc in #6896
  • Enable configuration of the Responses API for the Azure model provider (#6891) by @Advayp in #6891
  • fix: Update benchmark snapshots (#6888) by @app/github-actions in #6888
  • Update OpenAPI specification for /v1/responses (#6889) by @Advayp in #6889
  • Add test to ensure tools are injected correctly in the Responses API (#6886) by @Advayp in #6886
  • Enable embeddings for append streams (#6878) by @sgrebnov in #6878
  • Show correct limit for EXPLAIN plans in S3VectorsQueryExec (#6852) by @Jeadie in #6852
  • Responses API support for Azure Open AI (#6879) by @Advayp in #6879
  • fix: Update search test case structure (#6865) by @peasee in #6865
  • Fix mongodb benchmark (#6883) by @phillipleblanc in #6883
  • Support multiple column primary keys for S3 vectors. (#6775) by @Jeadie in #6775
  • Kafka Data Connector: persist consumer between restarts (#6870) by @sgrebnov in #6870
  • Fix newlines in errors added in recent PRs (#6877) by @phillipleblanc in #6877
  • Add override parameter to force support for the Responses API (#6871) by @Advayp in #6871
  • Don't use metadata columns in VectorScanTableProvider (#6854) by @Jeadie in #6854
  • Add non-streaming tool call support (hosted and Spice tools) via the Responses API (#6869) by @Advayp in #6869
  • Update error guideline to remove newlines + remove newlines from error messages. (#6866) by @phillipleblanc in #6866
  • Remove void acceleration engine + optional table behaviors (#6868) by @phillipleblanc in #6868
  • Kafka Data Connector basic support (#6856) by @sgrebnov in #6856
  • Federated+Accelerated TPCH Benchmarks for MongoDB (#6788) by @krinart in #6788
  • Pass embeddings calculated in compute_index to the acceleration (#6792) by @phillipleblanc in #6792
  • Add non-streaming and streaming support for OpenAI Responses API endpoint (#6830) by @Advayp in #6830
  • Use latest version of OpenAI crate to resolve issues with Service Tier deserialization (#6853) by @Advayp in #6853
  • Update openapi.json (#6799) by @app/github-actions in #6799
  • Improve management message (#6850) by @lukekim in #6850
  • fix: Include FTS search column if it is the PK (#6836) by @peasee in #6836
  • Refactor Health Checks (#6848) by @Advayp in #6848
  • Introduce a Responses trait and LLM registry for model providers that support the OpenAI Responses API (#6798) by @Advayp in #6798
  • fix: Update datafusion-table-providers to include constraints (#6837) by @peasee in #6837
  • Bump postcard from 1.1.2 to 1.1.3 (#6841) by @app/dependabot in #6841
  • Bump governor from 0.10.0 to 0.10.1 (#6835) by @app/dependabot in #6835
  • Bump ctor from 0.2.9 to 0.5.0 (#6827) by @app/dependabot in #6827
  • Bump azure_core from 0.26.0 to 0.27.0 (#6826) by @app/dependabot in #6826
  • Bump rstest from 0.25.0 to 0.26.1 (#6825) by @app/dependabot in #6825
  • Use latest commit in our fork of async-openai (#6829) by @Advayp in #6829
  • Bump rustls from 0.23.27 to 0.23.31 (#6824) by @app/dependabot in #6824
  • Bump async-trait from 0.1.88 to 0.1.89 (#6823) by @app/dependabot in #6823
  • Bump hyper from 1.6.0 to 1.7.0 (#6814) by @app/dependabot in #6814
  • Bump serde_json from 1.0.140 to 1.0.142 (#6812) by @app/dependabot in #6812
  • Add s3 vector test retrieving vectors (#6786) by @Jeadie in #6786
  • fix: Allow v1/search with only FTS (#6811) by @peasee in #6811
  • Bump tantivy from 0.24.1 to 0.24.2 (#6806) by @app/dependabot in #6806
  • Bump tokio-util from 0.7.15 to 0.7.16 (#6810) by @app/dependabot in #6810
  • fix: Improve FTS index primary key handling (#6809) by @peasee in #6809
  • Bump logos from 0.15.0 to 0.15.1 (#6808) by @app/dependabot in #6808
  • Bump hf-hub from 0.4.2 to 0.4.3 (#6807) by @app/dependabot in #6807
  • Bump odbc-api from 13.0.1 to 13.1.0 (#6803) by @app/dependabot in #6803
  • fix: Spice search CLI with FTS supports string or slice unmarshalling (#6805) by @peasee in #6805
  • Bump uuid from 1.17.0 to 1.18.0 (#6797) by @app/dependabot in #6797
  • Bump reqwest from 0.12.22 to 0.12.23 (#6796) by @app/dependabot in #6796
  • Bump anyhow from 1.0.98 to 1.0.99 (#6795) by @app/dependabot in #6795
  • Bump clap from 4.5.41 to 4.5.45 (#6794) by @app/dependabot in #6794
  • Respect default MAX_DECODING_MESSAGE_SIZE (100MB) in Flight API (#6802) by @sgrebnov in #6802
  • Fix compilation errors caused by upgrading async-openai (#6793) by @Advayp in #6793
  • Remove outdated vector search benchmark (replaced with testoperator) (#6791) by @sgrebnov in #6791
  • Handle errors in vector ingestion pipeline (#6782) by @phillipleblanc in #6782
  • fix: Explicitly error when chunking is defined for vector engines (#6787) by @peasee in #6787
  • Make VectorScanTableProvider and VectorQueryTableProvider support multi-column primary keys (#6757) by @Jeadie in #6757
  • Use megascience/megascience Q+A dataset for text search testing. (#6702) by @Jeadie in #6702
  • Flight REPL autocomplete (#6589) by @krinart in #6589
  • use ref: github.event.pull_request.head.sha in integration_models.yml (#6780) by @Jeadie in #6780
  • fix: Move search telemetry calls in UDTF to scan (#6778) by @peasee in #6778
  • Fix Hugging Face models and embeddings loading in Docker (#6777) by @ewgenius in #6777
  • feat: Migrate bedrock rate limiter (#6773) by @peasee in #6773
  • Run the PR checks on the DEV runners (#6769) by @phillipleblanc in #6769
  • feat: add OpenAI models rate controller (#6767) by @peasee in #6767
  • Implement MongoDB data connector (#6594) by @krinart in #6594
  • fix: Use head ref for concurrency group (#6770) by @peasee in #6770
  • fix: Run enforce pulls with spice on pull_request_target (#6768) by @peasee in #6768
  • feat: Add OpenAI Embeddings Rate Controller (#6764) by @peasee in #6764
  • Move AWS SDK credential bridge integration test to the existing AWS SDK integration test run (#6766) by @phillipleblanc in #6766
  • Use Spice specific errors instead of OpenAIError in embedding module (#6748) by @kczimm in #6748
  • Use context in Glue Catalog Provider (#6763) by @Advayp in #6763
  • pin cargo-deny to previous version (#6762) by @kczimm in #6762
  • Bump actions/download-artifact from 4 to 5 (#6720) by @app/dependabot in #6720
  • Upgrade dependabot dependencies (#6754) by @phillipleblanc in #6754
  • Set E2E Test CI models build to 90 minute timeout (#6756) by @phillipleblanc in #6756
  • chore: upgrade to Rust 1.87.0 (#6614) by @kczimm in #6614
  • feat: Add initial runtime-rate-limiter crate (#6753) by @peasee in #6753
  • feat: Add more embedding traces, add MiniLM MTEB spicepod (#6742) by @peasee in #6742
  • Update QA analytics for release (#6740) by @Advayp in #6740
  • Always use 'returnData: true' for s3 vector query index (#6741) by @Jeadie in #6741
  • feat: Add Embedding and Search anonymous telemetry (#6737) by @peasee in #6737
  • Add 1.5.2 to SECURITY.md (#6739) by @ewgenius in #6739
  • Combine the Iceberg and Object Store AWS SDK bridges into one crate (#6718) by @Advayp in #6718
  • Updates to v1.5.2 release notes (#6736) by @lukekim in #6736
  • Update end game template - move glue catalog to catalogs section (#6732) by @ewgenius in #6732
  • Update v1.5.2.md (#6735) by @kczimm in #6735
  • Add note about S3 Vectors workaround (#6734) by @phillipleblanc in #6734
  • feat: Avoid joining for VectorScanTableProvider if the index is sufficient (#6714) by @peasee in #6714
  • update changelog (#6729) by @kczimm in #6729
  • remove unneeded autogenerated s3 vector code (#6715) by @Jeadie in #6715
  • fix: Set S3 vectors default limit to 30, add more tracing (#6712) by @peasee in #6712
  • docs: Add Hadoop cookbook to endgame template (#6708) by @peasee in #6708
  • Fix testoperator append mode compilation error (#6706) by @phillipleblanc in #6706
  • test: Add VectorScanTableProvider snapshot tests (#6701) by @peasee in #6701
  • feat: Add Hadoop catalog-mode benchmark (#6684) by @peasee in #6684
  • Move shared AWS crates used in bridges to workspace (#6705) by @Advayp in #6705
  • Use installation id to group connections (#6703) by @Advayp in #6703
  • Add Guardrails for AWS bedrock models (#6692) by @Jeadie in #6692
  • Update bedrock keys for CI. (#6693) by @Jeadie in #6693
  • Update acknowledgements (#6690) by @app/github-actions in #6690
  • ROADMAP updates Aug 1, 2025 (#6667) by @lukekim in #6667
  • Add retry logic for OpenAI embeddings creation (#6656) by @sgrebnov in #6656
  • Make models E2E chat test more robust (#6657) by @sgrebnov in #6657
  • Update Search GH Workflow to use Test Operator (#6650) by @sgrebnov in #6650
  • Score and P95 latency calculation for MTEB Quora-based vector search tests in Test Operator (#6640) by @sgrebnov in #6640
  • Fix multiple query error being classified as an internal error (#6635) by @Advayp in #6635
  • Add Support for S3 Table Buckets (#6573) by krinart in #6573
  • set MISTRALRS_METAL_PRECOMPILE=0 for metal (#6652) by @kczimm in #6652
  • Vector search to push down udtf limit argument into logical sort plan (#6636) by @mach-kernel in #6636
  • docs: Update qa_analytics.csv (#6643) by @peasee in #6643
  • Update SECURITY.md (#6642) by @Jeadie in #6642
  • docs: Update qa_analytics.csv (#6641) by @peasee in #6641
  • Separate token usage (#6619) by @Advayp in #6619
  • Fix typo in release notes (#6634) by @Advayp in #6634
  • Add environment variable for org token (#6633) by @Advayp in #6633
  • CDC: Compute embeddings on ingest (#6612) by @mach-kernel in #6612
  • Add view name to view creation errors (#6611) by @lukekim in #6611
  • Add core logic for running MTEB Quora-based vector search tests in Test Operator (#6607) by @sgrebnov in #6607
  • Revert "Update generate-openapi.yml (#6584)" (#6620) by @Jeadie in #6620
  • Non-accelerated views should report as ready only after all dependent datasets are ready (#6617) by @sgrebnov in #6617

Spice v0.15-alpha (July 1, 2024)

Β· 5 min read
Luke Kim
Founder and CEO of Spice AI

The v0.15-alpha release introduces support for streaming databases changes with Change Data Capture (CDC) into accelerated tables via a new Debezium connector, configurable retry logic for data refresh, and the release of a new C# SDK to build with Spice in Dotnet.

Highlights in v0.15-alpha​

  • Debezium data connector with Change Data Capture (CDC): Sync accelerated datasets with Debezium data sources over Kafka in real-time.

  • Data Refresh Retries: By default, accelerated datasets attempt to retry data refreshes on transient errors. This behavior can be configured using refresh_retry_enabled and refresh_retry_max_attempts.

  • C# Client SDK: A new C# Client SDK has been released for developing applications in Dotnet.

Debezium data connector with Change Data Capture (CDC)​

Integrating Debezium CDC is straightforward. Get started with the Debezium CDC Sample, read more about CDC in Spice, and read the Debezium data connector documentation.

Example Spicepod using Debezium CDC:

datasets:
- from: debezium:cdc.public.customer_addresses
name: customer_addresses_cdc
params:
debezium_transport: kafka
debezium_message_format: json
kafka_bootstrap_servers: localhost:19092
acceleration:
enabled: true
engine: duckdb
mode: file
refresh_mode: changes

Data Refresh Retries​

Example Spicepod configuration limiting refresh retries to a maximum of 10 attempts:

datasets:
- from: eth.blocks
name: blocks
acceleration:
refresh_retry_enabled: true
refresh_retry_max_attempts: 10
refresh_check_interval: 30s

Breaking Changes​

None.

New Contributors​

Contributors​

What's Changed​

Dependencies​

No major dependency updates.

Commits​

Full Changelog: https://github.com/spiceai/spiceai/compare/v0.14.1-alpha...v0.15.0-alpha

Resources​

Community​

Spice.ai started with the vision to make AI easy for developers. We are building Spice.ai in the open and with the community. Reach out on Slack or by email to get involved.