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Spice v1.5.0 (July 21, 2025)

· 14 min read
Evgenii Khramkov
Evgenii Khramkov
Senior Software Engineer at Spice AI

Announcing the release of Spice v1.5.0! 🔍

Spice v1.5.0 brings major upgrades to search and retrieval. It introduces native support for Amazon S3 Vectors, enabling petabyte scale vector search directly from S3 vector buckets, alongside SQL-integrated vector and tantivy-powered full-text search, partitioning for DuckDB acceleration, and automated refreshes for search indexes and views. It includes the AWS Bedrock Embeddings Model Provider, the Oracle Database connector, and the now-stable Spice.ai Cloud Data Connector, and the upgrade to DuckDB v1.3.2.

What's New in v1.5.0​

Amazon S3 Vectors Support: Spice.ai now integrates with Amazon S3 Vectors, launched in public preview on July 15, 2025, enabling vector-native object storage with built-in indexing and querying. This integration supports semantic search, recommendation systems, and retrieval-augmented generation (RAG) at petabyte scale with S3’s durability and elasticity. Spice.ai manages the vector lifecycle—ingesting data, creating embeddings with models like Amazon Titan or Cohere via AWS Bedrock, or others available on HuggingFace, and storing it in S3 Vector buckets.

Spice integration with Amazon S3 Vectors

Example Spicepod.yml configuration for S3 Vectors:

datasets:
  - from: s3://my_data_bucket/data/
    name: my_vectors
    params:
      file_format: parquet
    acceleration:
      enabled: true
    vectors:
      engine: s3_vectors
      params:
        s3_vectors_aws_region: us-east-2
        s3_vectors_bucket: my-s3-vectors-bucket
    columns:
      - name: content
        embeddings:
          - from: bedrock_titan
            row_id:
              - id

Example SQL query using S3 Vectors:

SELECT *
FROM vector_search(my_vectors, 'Cricket bats', 10)
WHERE price < 100
ORDER BY score

For more details, refer to the S3 Vectors Documentation.

SQL-integrated Search: Vector and BM25-scored full-text search capabilities are now natively available in SQL queries, extending the power of the POST v1/search endpoint to all SQL workflows.

Example Vector-Similarity-Search (VSS) using the vector_search UDTF on the table reviews for the search term "Cricket bats":

SELECT review_id, review_text, review_date, score
FROM vector_search(reviews, "Cricket bats")
WHERE country_code="AUS"
LIMIT 3

Example Full-Text-Search (FTS) using the text_search UDTF on the table reviews for the search term "Cricket bats":

SELECT review_id, review_text, review_date, score
FROM text_search(reviews, "Cricket bats")
LIMIT 3

DuckDB v1.3.2 Upgrade: Upgraded DuckDB engine from v1.1.3 to v1.3.2. Key improvements include support for adding primary keys to existing tables, resolution of over-eager unique constraint checking for smoother inserts, and 13% reduced runtime on TPC-H SF100 queries through extensive optimizer refinements. The v1.2.x release of DuckDB was skipped due to a regression in indexes.

Partitioned Acceleration: DuckDB file-based accelerations now support partition_by expressions, enabling queries to scale to large datasets through automatic data partitioning and query predicate pruning. New UDFs, bucket and truncate, simplify partition logic.

New UDFs useful for partition_by expressions:

  • bucket(num_buckets, col): Partitions a column into a specified number of buckets based on a hash of the column value.
  • truncate(width, col): Truncates a column to a specified width, aligning values to the nearest lower multiple (e.g., truncate(10, 101) = 100).

Example Spicepod.yml configuration:

datasets:
  - from: s3://my_bucket/some_large_table/
    name: my_table
    params:
      file_format: parquet
    acceleration:
      enabled: true
      engine: duckdb
      mode: file
      partition_by: bucket(100, account_id) # Partition account_id into 100 buckets

Full-Text-Search (FTS) Index Refresh: Accelerated datasets with search indexes maintain up-to-date results with configurable refresh intervals.

Example refreshing search indexes on body every 10 seconds:

datasets:
  - from: github:github.com/spiceai/docs/pulls
    name: spiceai.doc.pulls
    params:
      github_token: ${secrets:GITHUB_TOKEN}
    acceleration:
      enabled: true
      refresh_mode: full
      refresh_check_interval: 10s
    columns:
      - name: body
        full_text_search:
          enabled: true
          row_id:
            - id

Scheduled View Refresh: Accelerated Views now support cron-based refresh schedules using refresh_cron, automating updates for accelerated data.

Example Spicepod.yml configuration:

views:
  - name: my_view
    sql: SELECT 1
    acceleration:
      enabled: true
      refresh_cron: '0 * * * *' # Every hour

For more details, refer to Scheduled Refreshes.

Multi-column Vector Search: For datasets configured with embeddings on more than one column, POST v1/search and similarity_search perform parallel vector search on each column, aggregating results using reciprocal rank fusion.

Example Spicepod.yml for multi-column search:

datasets:
  - from: github:github.com/apache/datafusion/issues
    name: datafusion.issues
    params:
      github_token: ${secrets:GITHUB_TOKEN}
    columns:
      - name: title
        embeddings:
          - from: hf_minilm
      - name: body
        embeddings:
          - from: openai_embeddings

AWS Bedrock Embeddings Model Provider: Added support for AWS Bedrock embedding models, including Amazon Titan Text Embeddings and Cohere Text Embeddings.

Example Spicepod.yml:

embeddings:
  - from: bedrock:cohere.embed-english-v3
    name: cohere-embeddings
    params:
      aws_region: us-east-1
      input_type: search_document
      truncate: END
  - from: bedrock:amazon.titan-embed-text-v2:0
    name: titan-embeddings
    params:
      aws_region: us-east-1
      dimensions: '256'

For more details, refer to the AWS Bedrock Embedding Models Documentation.

Oracle Data Connector: Use from: oracle: to access and accelerate data stored in Oracle databases, deployed on-premises or in the cloud.

Example Spicepod.yml:

datasets:
  - from: oracle:"SH"."PRODUCTS"
    name: products
    params:
      oracle_host: 127.0.0.1
      oracle_username: scott
      oracle_password: tiger

See the Oracle Data Connector documentation.

GitHub Data Connector: The GitHub data connector supports query and acceleration of members, the users of an organization.

Example Spicepod.yml configuration:

datasets:
  - from: github:github.com/spiceai/members # General format: github.com/[org-name]/members
    name: spiceai.members
    params:
      # With GitHub Apps (recommended)
      github_client_id: ${secrets:GITHUB_SPICEHQ_CLIENT_ID}
      github_private_key: ${secrets:GITHUB_SPICEHQ_PRIVATE_KEY}
      github_installation_id: ${secrets:GITHUB_SPICEHQ_INSTALLATION_ID}
      # With GitHub Tokens
      # github_token: ${secrets:GITHUB_TOKEN}

See the [GitHub Data Connector Documentation]

Spice.ai Cloud Data Connector: Graduated to Stable.

spice-rs SDK Release: The Spice Rust SDK has updated to v3.0.0. This release includes optimizations for the Spice client API, adds robust query retries, and custom metadata configurations for spice queries.

Contributors​

Breaking Changes​

  • Search HTTP API Response: POST v1/search response payload has changed. See the new API documentation for details.
  • Model Provider Parameter Prefixes: Model Provider parameters use provider-specific prefixes instead of openai_ prefixes (e.g., hf_temperature for HuggingFace, anthropic_max_completion_tokens for Anthropic, perplexity_tool_choice for Perplexity). The openai_ prefix remains supported for backward compatibility but is deprecated and will be removed in a future release.

Cookbook Updates​

The Spice Cookbook now includes 72 recipes to help you get started with Spice quickly and easily.

Upgrading​

To upgrade to v1.5.0, download and install the specific binary from github.com/spiceai/spiceai/releases/tag/v1.5.0 or pull the v1.5.0 Docker image (spiceai/spiceai:1.5.0).

What's Changed​

Dependencies​

Changelog​

  • fix: openai model endpoint (#6394) by @Sevenannn in #6394
  • Enable configuring otel endpoint from spice run (#6360) by @Advayp in #6360
  • Enable Oracle connector in default build configuration (#6395) by @sgrebnov in #6395
  • fix llm integraion test (#6398) by @Sevenannn in #6398
  • Promote spice cloud connector to stable quality (#6221) by @Sevenannn in #6221
  • v1.5.0-rc.1 release notes (#6397) by @lukekim in #6397
  • Fix model nsql integration tests (#6365) by @Sevenannn in #6365
  • Fix incorrect UDTF name and SQL query (#6404) by @lukekim in #6404
  • Update v1.5.0-rc.1.md (#6407) by @sgrebnov in #6407
  • Improve error messages (#6405) by @lukekim in #6405
  • build(deps): bump Jimver/cuda-toolkit from 0.2.25 to 0.2.26 (#6388) by @app/dependabot in #6388
  • Upgrade dependabot dependencies (#6411) by @phillipleblanc in #6411
  • Fix projection pushdown issues for document based file connector (#6362) by @Advayp in #6362
  • Add a PartitionedDuckDB Accelerator (#6338) by @kczimm in #6338
  • Use vector_search() UDTF in HTTP APIs (#6417) by @Jeadie in #6417
  • add supported types (#6409) by @kczimm in #6409
  • Enable session time zone override for MySQL (#6426) by @sgrebnov in #6426
  • Acceleration-like indexing for full text search indexes. (#6382) by @Jeadie in #6382
  • Provide error message when partition by expression changes (#6415) by @kczimm in #6415
  • Add support for Oracle Autonomous Database connections (Oracle Cloud) (#6421) by @sgrebnov in #6421
  • prune partitions for exact and in list with and without UDFs (#6423) by @kczimm in #6423
  • Fixes and reenable FTS tests (#6431) by @Jeadie in #6431
  • Upgrade DuckDB to 1.3.2 (#6434) by @phillipleblanc in #6434
  • Fix issue in limit clause for the Github Data connector (#6443) by @Advayp in #6443
  • Upgrade iceberg-rust to 0.5.1 (#6446) by @phillipleblanc in #6446
  • v1.5.0-rc.2 release notes (#6440) by @lukekim in #6440
  • Oracle: add automated TPC-H SF1 benchmark tests (#6449) by @sgrebnov in #6449
  • fix: Update benchmark snapshots (#6455) by @app/github-actions in #6455
  • Preserve ArrowError in arrow_tools::record_batch (#6454) by @mach-kernel in #6454
  • fix: Update benchmark snapshots (#6465) by @app/github-actions in #6465
  • Add option to preinstall Oracle ODPI-C library in Docker image (#6466) by @sgrebnov in #6466
  • Include Oracle connector (federated mode) in automated benchmarks (#6467) by @sgrebnov in #6467
  • Update crates/llms/src/bedrock/embed/mod.rs by @lukekim in #6468
  • v1.5.0-rc.3 release notes (#6474) by @lukekim in #6474
  • Add integration tests for S3 Vectors filters pushdown (#6469) by @sgrebnov in #6469
  • check for indexedtableprovider when finding tables to search on (#6478) by @Jeadie in #6478
  • Parse fully qualified table names in UDTFs (#6461) by @Jeadie in #6461
  • Add integration test for S3 Vectors to cover data update (overwrite) (#6480) by @sgrebnov in #6480
  • Add 'Run all tests' option for models tests and enable Bedrock tests (#6481) by @sgrebnov in #6481
  • Add support for a members table type for the GitHub Data Connector (#6464) by @Advayp in #6464
  • S3 vector data cannot be null (#6483) by @Jeadie in #6483
  • Don't infer FixedSizeList size during indexing vectors. (#6487) by @Jeadie in #6487
  • Add support for retention_sql acceleration param (#6488) by @sgrebnov in #6488
  • Make dataset refresh progress tracing less verbose (#6489) by @sgrebnov in #6489
  • Use RwLock on tantivy index in FullTextDatabaseIndex for update concurrency (#6490) by @Jeadie in #6490
  • Add tests for dataset retention logic and refactor retention code (#6495) by @sgrebnov in #6495
  • Upgade dependabot dependencies (#6497) by @phillipleblanc in #6497
  • Add periodic tracing of data loading progress during dataset refresh (#6499) by @sgrebnov in #6499
  • Promote Oracle Data Connector to Alpha (#6503) by @sgrebnov in #6503
  • Use AWS SDK to provide credentials for Iceberg connectors (#6498) by @phillipleblanc in #6498
  • Add integration tests for partitioning (#6463) by @kczimm in #6463
  • Use top-level table in full-text search JOIN ON (#6491) by @Jeadie in #6491
  • Use accelerated table in vector_search JOIN operations when appropriate (#6516) by @Jeadie in #6516
  • Fix 'additional_column' for quoted columns (fix for qualified columns broke it) (#6512) by @Jeadie in #6512
  • Also use AWS SDK for inferring credentials for S3/Delta/Databricks Delta data connectors (#6504) by @phillipleblanc in #6504
  • Add per-dataset availability monitor configuration (#6482) by @phillipleblanc in #6482
  • Suppress the warning from the AWS SDK if it can't load credentials (#6533) by @phillipleblanc in #6533
  • Change default value of check_availability from default to auto (#6534) by @lukekim in #6534
  • README.md improvements for v1.5.0 (#6539) by @lukekim in #6539
  • Temporary disable s3_vectors_basic (#6537) by @sgrebnov in #6537
  • Ensure binder errors show before query and other (#6374) by @suhuruli in #6374
  • Update spiceai/duckdb-rs -> DuckDB 1.3.2 + index fix (#6496) by @mach-kernel in #6496
  • Update table-providers to latest version with DuckDB fixes (#6535) by @phillipleblanc in #6535
  • S3: default to public access if no auth is provided (#6532) by @sgrebnov in #6532

Spice v1.4.0 (June 18, 2025)

· 19 min read
William Croxson
William Croxson
Senior Software Engineer at Spice AI

Announcing the release of Spice v1.4.0! ⚡

This release upgrades DataFusion to v47 and Arrow to v55 for faster queries, more efficient Parquet/CSV handling, and improved reliability. It introduces the AWS Glue Catalog and Data Connectors for native access to Glue-managed data on S3, and adds support for Databricks U2M OAuth for secure Databricks user authentication.

New Cron-based dataset refreshes and worker schedules enable automated task management, while dataset and search results caching improvements further optimizes query, search, and RAG performance.

What's New in v1.4.0​

DataFusion v47 Highlights​

Spice.ai is built on the DataFusion query engine. The v47 release brings:

Performance Improvements 🚀: This release delivers major query speedups through specialized GroupsAccumulator implementations for first_value, last_value, and min/max on Duration types, eliminating unnecessary sorting and computation. TopK operations are now up to 10x faster thanks to early exit optimizations, while sort performance is further enhanced by reusing row converters, removing redundant clones, and optimizing sort-preserving merge streams. Logical operations benefit from short-circuit evaluation for AND/OR, reducing overhead, and additional enhancements address high latency from sequential metadata fetching, improve int/string comparison efficiency, and simplify logical expressions for better execution.

Bug Fixes & Compatibility Improvements 🛠️: The release addresses issues with external sort, aggregation, and window functions, improves handling of NULL values and type casting in arrays and binary operations, and corrects problems with complex joins and nested window expressions. It also addresses SQL unparsing for subqueries, aliases, and UNION BY NAME.

See the Apache DataFusion 47.0.0 Changelog for details.

Arrow v55 Highlights​

Arrow v55 delivers faster Parquet gzip compression, improved array concatenation, and better support for large files (4GB+) and modular encryption. Parquet metadata reads are now more efficient, with support for range requests and enhanced compatibility for INT96 timestamps and timezones. CSV parsing is more robust, with clearer error messages. These updates boost performance, compatibility, and reliability.

See the Arrow 55.0.0 Changelog and Arrow 55.1.0 Changelog for details.

Runtime Highlights​

Search Result Caching: Spice now supports runtime caching for search results, improving performance for subsequent searches and chat completion requests that use the document_similarity LLM tool. Caching is configurable with options like maximum size, item TTL, eviction policy, and hashing algorithm.

Example spicepod.yml configuration:

runtime:
  caching:
    search_results:
      enabled: true
      max_size: 128mb
      item_ttl: 5s
      eviction_policy: lru
      hashing_algorithm: siphash

For more information, refer to the Caching documentation.

AWS Glue Catalog Connector Alpha: Connect to AWS Glue Data Catalogs to query Iceberg, Parquet, or CSV tables in S3.

Example spicepod.yml configuration:

catalogs:
  - from: glue
    name: my_glue_catalog
    params:
      glue_key: <your-access-key-id>
      glue_secret: <your-secret-access-key>
      glue_region: <your-region>
    include:
      - 'testdb.hive_*'
      - 'testdb.iceberg_*'
sql> show tables;
+-----------------+--------------+-------------------+------------+
| table_catalog   | table_schema | table_name        | table_type |
+-----------------+--------------+-------------------+------------+
| my_glue_catalog | testdb       | hive_table_001    | BASE TABLE |
| my_glue_catalog | testdb       | iceberg_table_001 | BASE TABLE |
| spice           | runtime      | task_history      | BASE TABLE |
+-----------------+--------------+-------------------+------------+

For more information, refer to the Glue Catalog Connector documentation.

AWS Glue Data Connector Alpha: Connect to specific tables in AWS Glue Data Catalogs to query Iceberg, Parquet, or CSV in S3.

Example spicepod.yml configuration:

datasets:
  - from: glue:my_database.my_table
    name: my_table
    params:
      glue_auth: key
      glue_region: us-east-1
      glue_key: ${secrets:AWS_ACCESS_KEY_ID}
      glue_secret: ${secrets:AWS_SECRET_ACCESS_KEY}

For more information, refer to the Glue Data Connector documentation.

Databricks U2M OAuth: Spice now supports User-to-Machine (U2M) authentication for Databricks when called with a compatible client, such as the Spice Cloud Platform.

datasets:
  - from: databricks:spiceai_sandbox.default.messages
    name: messages
    params:
      databricks_endpoint: ${secrets:DATABRICKS_ENDPOINT}
      databricks_cluster_id: ${secrets:DATABRICKS_CLUSTER_ID}
      databricks_client_id: ${secrets:DATABRICKS_CLIENT_ID}

Dataset Refresh Schedules: Accelerated datasets now support a refresh_cron parameter, automatically refreshing the dataset on a defined cron schedule. Cron scheduled refreshes respect the global dataset_refresh_parallelism parameter.

Example spicepod.yml configuration:

datasets:
  - name: my_dataset
    from: s3://my-bucket/my_file.parquet
    acceleration:
      refresh_cron: 0 0 * * * # Daily refresh at midnight

For more information, refer to the Dataset Refresh Schedules documentation.

Worker Execution Schedules: Workers now support a cron parameter and will execute an LLM-prompt or SQL query automatically on the defined cron schedule, in conjunction with a provided params.prompt.

Example spicepod.yml configuration:

workers:
  - name: email_reporter
    models:
      - from: gpt-4o
    params:
      prompt: 'Inspect the latest emails, and generate a summary report for them. Post the summary report to the connected Teams channel'
    cron: 0 2 * * * # Daily at 2am

For more information, refer to the Worker Execution Schedules documentation.

SQL Worker Actions: Spice now supports workers with sql actions for automated SQL query execution on a cron schedule:

workers:
  - name: my_worker
    cron: 0 * * * *
    sql: 'SELECT * FROM lineitem'

For more information, refer to the Workers with a SQL action documentation;

Contributors​

Breaking Changes​

  • No breaking changes.

Cookbook Updates​

The Spice Cookbook now includes 70 recipes to help you get started with Spice quickly and easily.

Upgrading​

To upgrade to v1.4.0, use one of the following methods:

CLI:

spice upgrade

Homebrew:

brew upgrade spiceai/spiceai/spice

Docker:

Pull the spiceai/spiceai:1.4.0 image:

docker pull spiceai/spiceai:1.4.0

For available tags, see DockerHub.

Helm:

helm repo update
helm upgrade spiceai spiceai/spiceai

What's Changed​

Dependencies​

Changelog​

  • Update trunk to 1.4.0-unstable (#5878) by @phillipleblanc in #5878
  • Update openapi.json (#5885) by @app/github-actions in #5885
  • feat: Testoperator reports benchmark failure summary (#5889) by @peasee in #5889
  • fix: Publish binaries to dev when platform option is all (#5905) by @peasee in #5905
  • feat: Print dispatch current test count of total (#5906) by @peasee in #5906
  • Include multiple duckdb files acceleration scenarios into testoperator dispatch (#5913) by @sgrebnov in #5913
  • feat: Support building testoperator on dev (#5915) by @peasee in #5915
  • Update spicepod.schema.json (#5927) by @app/github-actions in #5927
  • Update ROADMAP & SECURITY for 1.3.0 (#5926) by @phillipleblanc in #5926
  • docs: Update qa_analytics.csv (#5928) by @peasee in #5928
  • fix: Properly publish binaries to dev on push (#5931) by @peasee in #5931
  • Load request context extensions on every flight incoming call (#5916) by @ewgenius in #5916
  • Fix deferred loading for datasets with embeddings (#5932) by @ewgenius in #5932
  • Schedule AI benchmarks to run every Mon and Thu evening PST (#5940) by @sgrebnov in #5940
  • Fix explain plan snapshots for TPCDS queries Q36, Q70 & Q86 not being deterministic after DF 46 upgrade (#5942) by @phillipleblanc in #5942
  • chore: Upgrade to Rust 1.86 (#5945) by @peasee in #5945
  • Standardise HTTP settings across CLI (#5769) by @Jeadie in #5769
  • Fix deferred flag for Databricks SQL warehouse mode (#5958) by @ewgenius in #5958
  • Add deferred catalog loading (#5950) by @ewgenius in #5950
  • Refactor deferred_load using ComponentInitialization enum for better clarity (#5961) by @ewgenius in #5961
  • Post-release housekeeping (#5964) by @phillipleblanc in #5964
  • add LTO for release builds (#5709) by @kczimm in #5709
  • Fix dependabot/192 (#5976) by @Jeadie in #5976
  • Fix Test-to-SQL benchmark scheduled run (#5977) by @sgrebnov in #5977
  • Fix JSON to ScalarValue type conversion to match DataFusion behavior (#5979) by @sgrebnov in #5979
  • Add v1.3.1 release notes (#5978) by @lukekim in #5978
  • Regenerate nightly build workflow (#5995) by @ewgenius in #5995
  • Fix DataFusion dependency loading in Databricks request context extension (#5987) by @ewgenius in #5987
  • Update spicepod.schema.json (#6000) by @app/github-actions in #6000
  • feat: Run MySQL SF100 on dev runners (#5986) by @peasee in #5986
  • fix: Remove caching RwLock (#6001) by @peasee in #6001
  • 1.3.1 Post-release housekeeping (#6002) by @phillipleblanc in #6002
  • feat: Add initial scheduler crate (#5923) by @peasee in #5923
  • fix flight request context scope (#6004) by @ewgenius in #6004
  • fix: Ensure snapshots on different scale factors are retained (#6009) by @peasee in #6009
  • fix: Allow dev runners in dispatch files (#6011) by @peasee in #6011
  • refactor: Deprecate results_cache for caching.sql_results (#6008) by @peasee in #6008
  • Fix models benchmark results reporting (#6013) by @sgrebnov in #6013
  • fix: Run PR checks for tools/ changes (#6014) by @peasee in #6014
  • feat: Add a CronRequestChannel for scheduler (#6005) by @peasee in #6005
  • feat: Add refresh_cron acceleration parameter, start scheduler on table load (#6016) by @peasee in #6016
  • Update license check to allow dual license crates (#6021) by @sgrebnov in #6021
  • Initial worker concept (#5973) by @Jeadie in #5973
  • Don't fail if cargo-deny already installed (license check) (#6023) by @sgrebnov in #6023
  • Upgrade to DataFusion 47 and Arrow 55 (#5966) by @sgrebnov in #5966
  • Read Iceberg tables from Glue Catalog Connector (#5965) by @kczimm in #5965
  • Handle multiple highlights in v1/search UX (#5963) by @Jeadie in #5963
  • feat: Add cron scheduler configurations for workers (#6033) by @peasee in #6033
  • feat: Add search cache configuration and results wrapper (#6020) by @peasee in #6020
  • Fix GitHub Actions Ubuntu for more workflows (#6040) by @phillipleblanc in #6040
  • Fix Actions for testoperator dispatch manual (#6042) by @phillipleblanc in #6042
  • refactor: Remove worker type (#6039) by @peasee in #6039
  • feat: Support cron dataset refreshes (#6037) by @peasee in #6037
  • Upgrade datafusion-federation to 0.4.2 (#6022) by @phillipleblanc in #6022
  • Define SearchPipeline and use in runtime/vector_search.rs. (#6044) by @Jeadie in #6044
  • fix: Scheduler test when scheduler is running (#6051) by @peasee in #6051
  • doc: Spice Cloud Connector Limitation (#6035) by @Sevenannn in #6035
  • Add support for on_conflict:upsert for Arrow MemTable (#6059) by @sgrebnov in #6059
  • Enhance Arrow Flight DoPut operation tracing (#6053) by @sgrebnov in #6053
  • Update openapi.json (#6032) by @app/github-actions in #6032
  • Add tools enabled to MCP server capabilities (#6060) by @Jeadie in #6060
  • Upgrade to delta_kernel 0.11 (#6045) by @phillipleblanc in #6045
  • refactor: Replace refresh oneshot with notify (#6050) by @peasee in #6050
  • Enable Upsert OnConflictBehavior for runtime.task_history table (#6068) by @sgrebnov in #6068
  • feat: Add a workers integration test (#6069) by @peasee in #6069
  • Fix DuckDB acceleration ORDER BY rand() and ORDER BY NULL (#6071) by @phillipleblanc in #6071
  • Update Models Benchmarks to report unsuccessful evals as errors (#6070) by @sgrebnov in #6070
  • Revert: fix: Use HTTPS ubuntu sources (#6082) by @Sevenannn in #6082
  • Add initial support for Spice Cloud Platform management (#6089) by @sgrebnov in #6089
  • Run spiceai cloud connector TPC tests using spice dev apps (#6049) by @Sevenannn in #6049
  • feat: Add SQL worker action (#6093) by @peasee in #6093
  • Post-release housekeeping (#6097) by @phillipleblanc in #6097
  • Fix search bench (#6091) by @Jeadie in #6091
  • fix: Update benchmark snapshots (#6094) by @app/github-actions in #6094
  • fix: Update benchmark snapshots (#6095) by @app/github-actions in #6095
  • Glue catalog connector for hive style parquet (#6054) by @kczimm in #6054
  • Update openapi.json (#6100) by @app/github-actions in #6100
  • Improve Flight Client DoPut / Publish error handling (#6105) by @sgrebnov in #6105
  • Define PostApplyCandidateGeneration to handle all filters & projections. (#6096) by @Jeadie in #6096
  • refactor: Update the tracing task names for scheduled tasks (#6101) by @peasee in #6101
  • task: Switch GH runners in PR and testoperator (#6052) by @peasee in #6052
  • feat: Connect search caching for HTTP and tools (#6108) by @peasee in #6108
  • test: Add multi-dataset cron test (#6102) by @peasee in #6102
  • Sanitize the ListingTableURL (#6110) by @phillipleblanc in #6110
  • Avoid partial writes by FlightTableWriter (#6104) by @sgrebnov in #6104
  • fix: Update the TPCDS postgres acceleration indexes (#6111) by @peasee in #6111
  • Make Glue Catalog refreshable (#6103) by @kczimm in #6103
  • Refactor Glue catalog to use a new Glue data connector (#6125) by @kczimm in #6125
  • Emit retry error on flight transient connection failure (#6123) by @Sevenannn in #6123
  • Update Flight DoPut implementation to send single final PutResult (#6124) by @sgrebnov in #6124
  • feat: Add metrics for search results cache (#6129) by @peasee in #6129
  • update MCP crate (#6130) by @Jeadie in #6130
  • feat: Add search cache status header, respect cache control (#6131) by @peasee in #6131
  • fix: Allow specifying individual caching blocks (#6133) by @peasee in #6133
  • Update openapi.json (#6132) by @app/github-actions in #6132
  • Add CSV support to Glue data connector (#6138) by @kczimm in #6138
  • Update Spice Cloud Platform management UX (#6140) by @sgrebnov in #6140
  • Add TPCH bench for Glue catalog (#6055) by @kczimm in #6055
  • Enforce max_tokens_per_request limit in OpenAI embedding logic (#6144) by @sgrebnov in #6144
  • Enable Spice Cloud Control Plane connect (management) for FinanceBench (#6147) by @sgrebnov in #6147
  • Add integration test for Spice Cloud Platform management (#6150) by @sgrebnov in #6150
  • fix: Invalidate search cache on refresh (#6137) by @peasee in #6137
  • fix: Prevent registering cron schedule with change stream accelerations (#6152) by @peasee in #6152
  • test: Add an append cron integration test (#6151) by @peasee in #6151
  • fix: Cache search results with no-cache directive (#6155) by @peasee in #6155
  • fix: Glue catalog dispatch runner type (#6157) by @peasee in #6157
  • Fix: Glue S3 location for directories and Iceberg credentials (#6174) by @kczimm in #6174
  • Support multiple columns in FTS (#6156) by @Jeadie in #6156
  • fix: Add --cache-control flag for search CLI (#6158) by @peasee in #6158
  • Add Glue data connector tpch bench test for parquet and csv (#6170) by @kczimm in #6170
  • fix: Apply results cache deprecation correctly (#6177) by @peasee in #6177
  • Fix regression in Parquet pushdown (#6178) by @phillipleblanc in #6178
  • Fix CUDA build (use candle-core 0.8.4 and cudarc v0.12) (#6181) by @sgrebnov in #6181
  • return empty stream if no external_links present (#6192) by @kczimm in #6192
  • Use arrow pretty print util instead of init dataframe / logical plan in display_records (#6191) by @Sevenannn in #6191
  • task: Enable additional TPCDS test scenarios in dispatcher (#6160) by @peasee in #6160
  • chore: Update dependencies (#6196) by @peasee in #6196
  • Fix FlightSQL GetDbSchemas and GetTables schemas to fully match the protocol (#6197) by @sgrebnov in #6197
  • Use spice-rs in test operator and retry on connection reset error (#6136) by @Sevenannn in #6136
  • Fix load status metric description (#6219) by @phillipleblanc in #6219
  • Run extended tests on PRs against release branch, update glue_iceberg_integration_test_catalog test (#6204) by @Sevenannn in #6204
  • query schema for is_nullable (#6229) by @kczimm in #6229
  • fix: use the query error message when queries fail (#6228) by @kczimm in #6228
  • fix glue iceberg catalog integration test (#6249) by @Sevenannn in #6249
  • cache table providers in glue catalog (#6252) by @kczimm in #6252
  • fix: databricks sql_warehouse schema contains duplicate fields (#6255) by @phillipleblanc in #6255

Full Changelog: v1.3.2...v1.4.0

Spice v1.3.2 (June 2, 2025)

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

Announcing the release of Spice v1.3.2! ❄️

Spice v1.3.2 is a patch release with fixes to the DuckDB data accelerator and Snowflake data connector.

Changes:

  • DuckDB Data Accelerator: Supports ORDER BY rand() for randomized result ordering and ORDER BY NULL for SQL compatibility.

  • Snowflake Data Connector: Adds TIMESTAMP_NTZ(0) type for timestamps with seconds precision.

Contributors​

Breaking Changes​

No breaking changes.

Cookbook Updates​

No new cookbook recipes.

The Spice Cookbook now includes 67 recipes to help you get started with Spice quickly and easily.

Upgrading​

To upgrade to v1.3.2, use one of the following methods:

CLI:

spice upgrade

Homebrew:

brew upgrade spiceai/spiceai/spice

Docker:

Pull the spiceai/spiceai:1.3.2 image:

docker pull spiceai/spiceai:1.3.2

For available tags, see DockerHub.

Helm:

helm repo update
helm upgrade spiceai spiceai/spiceai

What's Changed​

Dependencies​

No major dependency changes.

Changelog​

  • Handle Snowflake Timestamp NTZ with seconds precision (#6084) by @kczimm in #6084
  • Fix DuckDB acceleration ORDER BY rand() and ORDER BY NULL (#6071) by @phillipleblanc in #6071

Full Changelog: https://github.com/spiceai/spiceai/compare/v1.3.1...v1.3.2

Spice v1.3.1 (May 26, 2025)

· 3 min read
Luke Kim
Luke Kim
Founder and CEO of Spice AI

Announcing the release of Spice v1.3.1! 🛡️

Spice v1.3.1 includes improvements to Databricks SQL Warehouse support and parameterized query handling, along with several bugfixes.

What's New in v1.3.1​

  • Databricks SQL Warehouse Added support for the STRUCT type, enabled join pushdown for queries within the same SQL Warehouse and added projection to logical plans to force federation with correct SQL dialect.

  • SQL Improvements: Fixed an issue where ILike was incorrectly optimized to string equality in DataFusion/Arrow and aliased the random() function to rand() for better compatibility.

  • Parameterized Queries: Fixed parameter schema ordering for queries with more than 10 parameters and resolved placeholder inference issues in CASE expressions.

Contributors​

Breaking Changes​

No breaking changes.

Cookbook Updates​

No new cookbook recipes.

The Spice Cookbook now includes 67 recipes to help you get started with Spice quickly and easily.

Upgrading​

To upgrade to v1.3.1, use one of the following methods:

CLI:

spice upgrade

Homebrew:

brew upgrade spiceai/spiceai/spice

Docker:

Pull the spiceai/spiceai:1.3.1 image:

docker pull spiceai/spiceai:1.3.1

For available tags, see DockerHub.

Helm:

helm repo update
helm upgrade spiceai spiceai/spiceai

What's Changed​

Dependencies​

No major dependency changes.

Changelog​

Full Changelog: github.com/spiceai/spiceai/compare/v1.3.0...v1.3.1

Spice v1.3.0 (May 19, 2025)

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

Announcing the release of Spice v1.3.0! 🏎️

Spice v1.3.0 accelerates data and AI applications with significantly improved query performance, reliability, and expanded Databricks integration. New support for the Databricks SQL Statement Execution API enables direct SQL queries on Databricks SQL Warehouses, complementing Mosaic AI model serving and embeddings (introduced in v1.2.2) and existing Databricks catalog and dataset integrations. This release upgrades to DataFusion v46, optimizes results caching performance, and strengthens security with least-privilege sandboxed improvements.

What's New in v1.3.0​

  • Databricks SQL Statement Execution API Support: Added support for the Databricks SQL Statement Execution API, enabling direct SQL queries against Databricks SQL Warehouses for optimized performance in analytics and reporting workflows.

    Example spicepod.yml configuration:

    datasets:
      - from: databricks:spiceai.datasets.my_awesome_table
        name: my_awesome_table
        params:
          mode: sql_warehouse
          databricks_endpoint: ${env:DATABRICKS_ENDPOINT}
          databricks_sql_warehouse_id: ${env:DATABRICKS_SQL_WAREHOUSE_ID}
          databricks_token: ${env:DATABRICKS_TOKEN}

    For details, see the Databricks Data Connector documentation.

  • Improved Results Cache Performance & Hashing Algorithm: Spice now supports an alternative results cache hashing algorithm, ahash, in addition to siphash, being the default. Configure it via:

    runtime:
      results_cache:
        hashing_algorithm: ahash # or siphash

    The hashing algorithm determines how cache keys are hashed before being stored, impacting both lookup speed and protection against potential DOS attacks.

    Using ahash improves performance for large queries or query plans. Combined with results cache optimizations, it reduces 99th percentile request latency and increases total requests/second for queries with large result sets (100k+ cached rows). The following charts show performance tested against the TPCH Query #17 on a scale factor 5 dataset (30+ million rows, 5GB):

    LatencyReq/sec
    Improvements for the 99th percentile query latency, compared against 1.2.2 with cache key type and hashing algorithm.Improvements for the requests/second, compared against 1.2.2 with cache key type and hashing algorithm.

    Note: ahash was not available in v1.2.2, so it is excluded from comparisons.

    To learn more, refer to the Results Cache Hashing Algorithm documentation.

  • SQL Query Performance: Optimized the critical SQL query path, reducing overhead and improving response times for simple queries by 10-20%.

  • DuckDB Acceleration: Fixed a bug in the DuckDB acceleration engine causing query failures under high concurrency when querying datasets accelerated into multiple DuckDB files.

  • Container Security: The container image now runs as a non-root user with enhanced sandboxing and includes only essential dependencies for a slimmer, more secure image.

DataFusion v46 Highlights​

Spice.ai is built on the DataFusion query engine. The v46 release brings:

  • Faster Performance 🚀: DataFusion 46 introduces significant performance enhancements, including a 2x faster median() function for large datasets without grouping, 10–100% speed improvements in FIRST_VALUE and LAST_VALUE window functions by avoiding sorting, and a 40x faster uuid() function. Additional optimizations, such as a 50% faster repeat() string function, accelerated chr() and to_hex() functions, improved grouping algorithms, and Parquet row group pruning with NOT LIKE filters, further boost overall query efficiency.

  • New range() Table Function: A new table-valued function range(start, stop, step) has been added to make it easy to generate integer sequences — similar to PostgreSQL’s generate_series() or Spark’s range(). Example: SELECT * FROM range(1, 10, 2);

  • UNION [ALL | DISTINCT] BY NAME Support: DataFusion now supports UNION BY NAME and UNION ALL BY NAME, which align columns by name instead of position. This matches functionality found in systems like Spark and DuckDB and simplifies combining heterogeneously ordered result sets.

    Example:

    SELECT col1, col2 FROM t1
    UNION ALL BY NAME
    SELECT col2, col1 FROM t2;

See the DataFusion 46.0.0 release notes for details.

Spice.ai adopts the latest minus one DataFusion release for quality assurance and stability. The upgrade to DataFusion v47 is planned for Spice v1.4.0 in June.

Contributors​

Breaking Changes​

The container image now always runs as a non-root user (UID/GID 65534) with minimal dependencies, resulting in a smaller, more secure image. Standard Linux tools, including bash, are no longer included.

Kubernetes Deployments:

  • Use of the v1.3.0+ Helm chart is required, which includes a securityContext ensuring the sandbox user has required file access.

  • For deployments using a lower version than the v1.3.0 Helm chart, add the following securityContext to the pod specification:

securityContext:
  runAsUser: 65534
  runAsGroup: 65534
  fsGroup: 65534

See the Docker Sandbox Guide for details on how to update custom Docker images to restore the previous behavior.

Cookbook Updates​

  • Added Accelerated Views: Pre-calculate and materialize data derived from one or more underlying datasets.

The Spice Cookbook now includes 67 recipes to help you get started with Spice quickly and easily.

Upgrading​

To upgrade to v1.3.0, use one of the following methods:

CLI:

spice upgrade

Homebrew:

brew upgrade spiceai/spiceai/spice

Docker:

Pull the spiceai/spiceai:1.3.0 image:

docker pull spiceai/spiceai:1.3.0

For available tags, see DockerHub.

Helm:

helm repo update
helm upgrade spiceai spiceai/spiceai

What's Changed​

Dependencies​

Changelog​

See the full list of changes at: v1.2.2...v1.3.0