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Spice v1.8.2 (Oct 21, 2025)

ยท 5 min read
Jack Eadie
Token Plumber at Spice AI

Announcing the release of Spice v1.8.2! ๐Ÿ”

Spice v1.8.2 is a patch release focused on reliability, validation, performance, and bug fixes, with improvements across DuckDB acceleration, S3 Vectors, document tables, and HTTP search.

What's New in v1.8.2โ€‹

Support Table Relations in /v1/search HTTP Endpointโ€‹

Spice now supports table relations for the additional_columns and where parameters in the /v1/search endpoint. This enables improved search for multi-dataset use cases, where filters and columns can be used on specific datasets.

Example:

curl 'http://localhost:8090/v1/search' \
-H 'Content-Type: application/json' \
-H 'Accept: application/json' -d '{
"text": "hello world",
"additional_columns": ["tbl1.foo", "tbl2.bar", "baz"],
"where": "tbl1.foo > 100000",
"limit": 5
}'

In this example, search results from the tbl1 dataset will include columns foo and baz, where foo > 100000. For tbl2, columns bar and baz will be returned.

DuckDB Data Accelerator Table Partitioning & Indexingโ€‹

  • Configurable DuckDB Index Scan: DuckDB acceleration now supports configurable duckdb_index_scan_percentage and duckdb_index_scan_max_count parameters, supporting fine-tuning of index scan behavior for improved query performance.

Example:

datasets:
- from: postgres:my_table
name: my_table
acceleration:
enabled: true
engine: duckdb
mode: file
params:
# When combined, DuckDB will use an index scan when the number of qualifying rows is less than the maximum of these two thresholds
duckdb_index_scan_percentage: '0.10' # 10% as decimal
duckdb_index_scan_max_count: '1000'
  • Hive-Style Partitioning: In file-partitioned mode, the DuckDB data accelerator uses Hive-style partitioning for more efficient file management.

  • Table-Based Partitioning: Spice now supports partitioning DuckDB accelerations within a single file. This approach maintains ACID guarantees for full and append mode refreshes, while optimizing resource usage and improving query performance. Configure via the partition_mode parameter:

datasets:
- from: file:test_data.parquet
name: test_data
params:
file_format: parquet
acceleration:
enabled: true
engine: duckdb
mode: file
params:
partition_mode: tables
partition_by:
- bucket(100, Field1)

S3 Vectors Reliabilityโ€‹

  • Race Condition Fix: Resolved a race condition in S3 Vectors index and bucket creation. The runtime also now checks if an index or bucket exists after a ConflictException, ensuring robust error handling during index creation and improving reliability for large-scale multi-index vector search.

Document Table Improvementsโ€‹

  • Primary Key Update: Document tables now use the location column as the primary key, improving performance, consistency, and query reliability.

Additional Improvements & Bugfixesโ€‹

  • Reliability: Improved error handling and resource checks for S3 Vectors and DuckDB acceleration.
  • Validation: Expanded validation for partitioning and index creation.
  • Performance: Optimized partition refresh and index scan logic.
  • Bugfix: Don't nullify DuckDB release callbacks for schemas.

Contributorsโ€‹

Breaking Changesโ€‹

No breaking changes.

Cookbook Updatesโ€‹

No major cookbook updates.

The Spice Cookbook includes 81 recipes to help you get started with Spice quickly and easily.

Upgradingโ€‹

To upgrade to v1.8.2, use one of the following methods:

CLI:

spice upgrade

Homebrew:

brew upgrade spiceai/spiceai/spice

Docker:

Pull the spiceai/spiceai:1.8.2 image:

docker pull spiceai/spiceai:1.8.2

For available tags, see DockerHub.

Helm:

helm repo update
helm upgrade spiceai spiceai/spiceai

AWS Marketplace:

๐ŸŽ‰ Spice is now available in the AWS Marketplace!

What's Changedโ€‹

Changelogโ€‹

  • Update mongo config for benchmarks by @krinart in #7546
  • Configurable DuckDB duckdb_index_scan_percentage & duckdb_index_scan_max_count by @lukekim in #7551
  • Fix race condition in S3 Vectors index and bucket creation by @kczimm in #7577
  • Use 'location' as primary key for document tables by @Jeadie in #7567
  • Update official Docker builds to use release binaries by @phillipleblanc in #7597
  • Hive-style partitioning for DuckDB file mode by @kczimm in #7563
  • New Generate Changelog workflow by @krinart in #7562
  • Add support for DuckDB table-based partitioning by @sgrebnov in #7581
  • DuckDB table partitioning: delete partitions that no longer exist after full refresh by @sgrebnov in #7614
  • Rename duckdb_partition_mode to partition_mode param by @sgrebnov in #7622
  • Fix license issue in table-providers by @phillipleblanc in #7620
  • Make DuckDB table partition data write threshold configurable by @sgrebnov in #7626
  • fix: Don't nullify DuckDB release callbacks for schemas by @peasee in #7628
  • Fix integration tests by reverting the use of batch inserts w/ prepared statements by @phillipleblanc in #7630
  • Return TableProvider from CandidateGeneration::search by @Jeadie in #7559
  • Handle table relations in HTTP v1/search by @Jeadie in #7615

Spice v1.7.1 (Sep 29, 2025)

ยท 6 min read
Kevin Zimmerman
Principal Software Engineer at Spice AI

Announcing the release of Spice v1.7.1! ๐Ÿ”

Spice v1.7.1 is a patch release focused on search improvements, bug fixes, and performance enhancements. This release introduces the Reciprocal Rank Fusion (RRF) user-defined table function (UDTF) for hybrid search, improves vector and text search reliability, and resolves several issues across the runtime, connectors, and query engine.

What's New in v1.7.1โ€‹

Reciprocal Rank Fusion (RRF) UDTF: Spice now supports Reciprocal Rank Fusion (RRF) as a user-defined table function, enabling advanced hybrid search scenarios that combine results from multiple search methods (e.g., vector and text search) for improved relevance ranking.

Features:

  • Multi-search fusion: Combine results from vector_search, text_search, and other search UDTFs in a single query.
  • Advanced tuning: Per-query ranking weights, recency boosting, and configurable decay functions.
  • Performance: Optional user-specified join key for optimal performance.
  • Automatic joining: Falls back to on-the-fly JOIN key computation when no explicit key is provided.

Example usage:

SELECT id, title, content, fused_score
FROM rrf(
vector_search(documents, 'machine learning algorithms', rank_weight => 1.5),
text_search(documents, 'neural networks deep learning', rank_weight => 1.2),
join_key => 'id', -- optional join key for optimal performance
k => 60.0 -- optional smoothing factor
)
WHERE fused_score > 0.01
ORDER BY fused_score DESC;

Learn more in the RRF documentation.

Acceleration Refresh Metrics: Spice now exposes additional Prometheus metrics that provide detailed observability into dataset acceleration refreshes. These metrics help monitor data freshness and ingestion lag for accelerated datasets with a time column.

Reported metrics:

Metric NameDescription
dataset_acceleration_max_timestamp_before_refresh_msMaximum value of the dataset's time column before refresh (milliseconds).
dataset_acceleration_max_timestamp_after_refresh_msMaximum value of the dataset's time column after refresh (milliseconds).
dataset_acceleration_refresh_lag_msDifference between max timestamp after and before refresh (milliseconds).
dataset_acceleration_ingestion_lag_msLag between current wall-clock time and max timestamp after refresh (milliseconds).

These metrics are emitted during each acceleration refresh and can be scraped by Prometheus for monitoring and alerting. For more details, see the Observability documentation.

Bug Fixes & Improvementsโ€‹

This release resolves several issues and improves reliability across search, connectors, and query planning:

  • Full-Text Search (FTS): Ensure FTS metadata columns can be used in projection, fix JOIN-level filters not having columns in schema, and adds support for persistent file-based FTS indexes. Default limit of 1000 results if no limit specified.
  • Vector Search: Default limit of 1000 results if no limit specified, and fix removing embedding column.
  • Databricks SQL Warehouse: Improved error handling and support for async queries.
  • Other: Fixes for Anthropic model regex validation, tweaked AI-model health checks, and improved error messages.

Contributorsโ€‹

Breaking Changesโ€‹

No breaking changes.

Cookbook Updatesโ€‹

  • Added Hybrid-Search using RRF - Combine results from multiple search methods (vector and text search) using Reciprocal Rank Fusion for improved relevance ranking.

The Spice Cookbook includes 78 recipes to help you get started with Spice quickly and easily.

Upgradingโ€‹

To upgrade to v1.7.1, use one of the following methods:

CLI:

spice upgrade

Homebrew:

brew upgrade spiceai/spiceai/spice

Docker:

Pull the spiceai/spiceai:1.7.1 image:

docker pull spiceai/spiceai:1.7.1

For available tags, see DockerHub.

Helm:

helm repo update
helm upgrade spiceai spiceai/spiceai

AWS Marketplace:

๐ŸŽ‰ Spice is now available in the AWS Marketplace!

What's Changedโ€‹

Changelogโ€‹

  • ensure FTS metadata columns can be used in projection (#7282) by @Jeadie in #7282
  • Fix JOIN level filters not having columns in schema (#7287) by @Jeadie in #7287
  • Use file-based fts index (#7024) by @Jeadie in #7024
  • Remove 'PostApplyCandidateGeneration' (#7288) by @Jeadie in #7288
  • RRF: Rank and recency boosting (#7294) by @mach-kernel in #7294
  • RRF: Preserve base ranking when results differ -> FULL OUTER JOIN does not produce time column (#7300) by @mach-kernel in #7300
  • fix removing embedding column (#7302) by @Jeadie in #7302
  • RRF: Fix decay for disjoint result sets (#7305) by @mach-kernel in #7305
  • RRF: Project top scores, do not yield duplicate results (#7306) by @mach-kernel in #7306
  • RRF: Case sensitive column/ident handling (#7309) by @mach-kernel in #7309
  • For vector_search, use a default limit of 1000 if no limit specified (#7311) by @lukekim in #7311
  • Fix Anthropic model regex and add validation tests (#7319) by @ewgenius in #7319
  • Enhancement: Implement before/after/lag metrics for acceleration refresh (#7310) by @krinart in #7310
  • Refactor chat model health check to lower tokens usage for reasoning models (#7317) by @ewgenius in #7317
  • Enable chunking in SearchIndex (#7143) by @Jeadie in #7143
  • Use logical plan in SearchQueryProvider. (#7314) by @Jeadie in #7314
  • FTS max search results 100 -> 1000 (#7331) by @Jeadie in #7331
  • Improve Databricks SQL Warehouse Error Handling (#7332) by @sgrebnov in #7332
  • use spicepod embedding model name for 'model_name' (#7333) by @Jeadie in #7333
  • Handle async queries for Databricks SQL Warehouse API (#7335) by @phillipleblanc in #7335
  • RRF: Fix ident resolution for struct fields, autohashed join key for varying types (#7339) by @mach-kernel in #7339

Spice v1.7.0 (Sep 23, 2025)

ยท 21 min read
Sergei Grebnov
Senior Software Engineer at Spice AI

Announcing the release of Spice v1.7.0! โšก

Spice v1.7.0 upgrades to DataFusion v49 for improved performance and query optimization, introduces real-time full-text search indexing for CDC streams, EmbeddingGemma support for high-quality embeddings, new search table functions powering the /v1/search API, embedding request caching for faster and cost-efficient search and indexing, and OpenAI Responses API tool calls with streaming. This release also includes numerous bug fixes across CDC streams, vector search, the Kafka Data Connector, and error reporting.

What's New in v1.7.0โ€‹

DataFusion v49 Highlightsโ€‹

DataFusion Clickbench Performance Graph Source: DataFusion 49.0.0 Release Blog.

Performance Improvements ๐Ÿš€

  • Equivalence System Upgrade: Faster planning for queries with many columns, enabling more sophisticated sort-based optimizations.
  • Dynamic Filters & TopK Pushdown: Queries with ORDER BY and LIMIT now use dynamic filters and physical filter pushdown, skipping unnecessary data reads for much faster top-k queries.
  • Compressed Spill Files: Intermediate files written during sort/group spill to disk are now compressed, reducing disk usage and improving performance.
  • WITHIN GROUP for Ordered-Set Aggregates: Support for ordered-set aggregate functions (e.g., percentile_disc) with WITHIN GROUP.
  • REGEXP_INSTR Function: Find regex match positions in strings.

Spice Runtime Highlightsโ€‹

EmbeddingGemma Support: Spice now supports EmbeddingGemma, Google's state-of-the-art embedding model for text and documents. EmbeddingGemma provides high-quality, efficient embeddings for semantic search, retrieval, and recommendation tasks. You can use EmbeddingGemma via HuggingFace in your Spicepod configuration:

Example spicepod.yml snippet:

embeddings:
- from: huggingface:huggingface.co/google/embeddinggemma-300m
name: embeddinggemma
params:
hf_token: ${secrets:HUGGINGFACE_TOKEN}

Learn more about EmbeddingGemma in the official documentation.

POST /v1/search API Use Search Table Functions: The /v1/search API now uses the new text_search and vector_search Table Functions for improved performance.

Embedding Request Caching: The runtime now supports caching embedding requests, reducing latency and cost for repeated content and search requests.

Example spicepod.yml snippet:

runtime:
caching:
embeddings:
enabled: true
max_size: 128mb
item_ttl: 5s

See the Caching documentation for details.

Real-Time Indexing for Full Text Search: Full Text search indexing is now supported for connectors that enable real-time changes, such as Debezium CDC streams. Adding a full-text index on a column with refresh_mode: changes works as it does for full/append-mode refreshes, enabling instant search on new data.

Example spicepod.yml snippet:

datasets:
- from: debezium:cdc.public.question
name: questions
acceleration:
enabled: true
engine: duckdb
primary_key: id
refresh_mode: changes # Use 'changes'
params: *kafka_params
columns:
- name: title
full_text_search:
enabled: true # Enable full-text-search indexing
row_id:
- id

OpenAI Responses API Tool Calls with Streaming: The OpenAI Responses API now supports tool calls with streaming, enabling advanced model interactions such as web_search and code_interpreter with real-time response streaming. This allows you to invoke OpenAI-hosted tools and receive results as they are generated.

Learn more in the OpenAI Model Provider documentation.

Runtime Output Level Configuration: You can now set the output_level parameter in the Spicepod runtime configuration to control logging verbosity in addition to the existing CLI and environment variable support. Supported values are info, verbose, and very_verbose. The value is applied in the following priority: CLI, environment variables, then YAML configuration.

Example spicepod.yml snippet:

runtime:
output_level: info # or verbose, very_verbose

For more details on configuring output level, see the Troubleshooting documentation.

Bug Fixesโ€‹

Several bugs and issues have been resolved in this release, including:

  • CDC Streams: Fixed issues where refresh_mode: changes could prevent the Spice runtime from becoming Ready, and improved support for full-text indexing on CDC streams.
  • Vector Search: Fixed bugs where vector search HTTP pipeline could not find more than one IndexedTableProvider, and resolved errors with field mismatches in vector_search UDTF.
  • Kafka Integration: Improved Kafka schema inference with configurable sample size, improved consumer group persistence for SQLite and Postgres accelerations, and added cooperative mode support.
  • Perplexity Web Search: Fixed bug where Perplexity web search sometimes used incorrect query schema (limit).
  • Databricks: Fixed issue with unparsing embedded columns.
  • Error Reporting: ThrottlingException is now reported correctly instead of as InternalError.
  • Iceberg Data Connector: Added support for LIMIT pushdown.
  • Amazon S3 Vectors: Fixed ingestion issues with zero-vectors and improved handling when vector index is full.
  • Tracing: Fixed vector search tracing to correctly report SQL status.

Contributorsโ€‹

New Contributorsโ€‹

Breaking Changesโ€‹

No breaking changes.

Cookbook Updatesโ€‹

The Spice Cookbook includes 78 recipes to help you get started with Spice quickly and easily.

Upgradingโ€‹

To upgrade to v1.7.0, use one of the following methods:

CLI:

spice upgrade

Homebrew:

brew upgrade spiceai/spiceai/spice

Docker:

Pull the spiceai/spiceai:1.7.0 image:

docker pull spiceai/spiceai:1.7.0

For available tags, see DockerHub.

Helm:

helm repo update
helm upgrade spiceai spiceai/spiceai

AWS Marketplace:

๐ŸŽ‰ Spice is now available in the AWS Marketplace!

What's Changedโ€‹

Dependenciesโ€‹

Changelogโ€‹

Spice v0.18.3-beta (Sep 30, 2024)

ยท 5 min read
Jack Eadie
Token Plumber at Spice AI

Announcing the release of Spice v0.18.3-beta ๐Ÿ› ๏ธ

The Spice v0.18.3-beta release includes several quality-of-life improvements including verbosity flags for spiced and the Spice CLI, vector search over larger documents with support for chunking dataset embeddings, and multiple performance enhancements. Additionally, the release includes several bug fixes, dependency updates, and optimizations, including updated table providers and significantly improved GitHub data connector performance for issues and pull requests.

Highlights in v0.18.3-betaโ€‹

GitHub Query Mode: A new github_query_mode: search parameter has been added to the GitHub Data Connector, which uses the GitHub Search API to enable faster and more efficient query of issues and pull requests when using filters.

Example spicepod.yml:

- from: github:github.com/spiceai/spiceai/issues/trunk
name: spiceai.issues
params:
github_query_mode: search # Use GitHub Search API
github_token: ${secrets:GITHUB_TOKEN}

Output Verbosity: Higher verbosity output levels can be specified through flags for both spiced and the Spice CLI.

Example command line:

spice -v
spice --very-verbose

spiced -vv
spiced --verbose

Embedding Chunking: Chunking can be enabled and configured to preprocess input data before generating dataset embeddings. This improves the relevance and precision for larger pieces of content.

Example spicepod.yml:

- name: support_tickets
embeddings:
- column: conversation_history
use: openai_embeddings
chunking:
enabled: true
target_chunk_size: 128
overlap_size: 16
trim_whitespace: true

For details, see the Search Documentation.

Dependenciesโ€‹

Contributorsโ€‹

  • @Sevenannn
  • @peasee
  • @Jeadie
  • @sgrebnov
  • @phillipleblanc
  • @ewgenius
  • @slyons

What's Changedโ€‹

- Update datafusion table provider patch by @Sevenannn in https://github.com/spiceai/spiceai/pull/2817
- refactor: Set max_rows_per_batch for ODBC to 4000 by @peasee in https://github.com/spiceai/spiceai/pull/2822
- Use User message for health check by @Jeadie in https://github.com/spiceai/spiceai/pull/2823
- Upgrade Helm chart (Spice v0.18.2-beta) by @sgrebnov in https://github.com/spiceai/spiceai/pull/2820
- Add verbosity flags for spiced, spice: `-v`, `-vv`, `--verbose`, `--very-verbose`. by @Jeadie in https://github.com/spiceai/spiceai/pull/2831
- Rename `spiceai` data connector to `spice.ai` by @sgrebnov in https://github.com/spiceai/spiceai/pull/2680
- Prepare for v0.19.0-beta release (version bump) by @sgrebnov in https://github.com/spiceai/spiceai/pull/2821
- Bump clap from 4.5.17 to 4.5.18 (#2801) by @phillipleblanc in https://github.com/spiceai/spiceai/pull/2848
- Enable "rc" feature for serde in spicepod crate by @ewgenius in https://github.com/spiceai/spiceai/pull/2851
- Update spicepod.schema.json by @github-actions in https://github.com/spiceai/spiceai/pull/2852
- chore: update table providers by @peasee in https://github.com/spiceai/spiceai/pull/2858
- fix: Use GitHub search for issues in GraphQL by @peasee in https://github.com/spiceai/spiceai/pull/2845
- fix: Use GitHub search for pull_requests by @peasee in https://github.com/spiceai/spiceai/pull/2847
- Support chunking dataset embeddings by @Jeadie in https://github.com/spiceai/spiceai/pull/2854
- refactor: Update GraphQL client to be more robust for filter push down by @peasee in https://github.com/spiceai/spiceai/pull/2864
- docs: Update accelerator beta criteria by @peasee in https://github.com/spiceai/spiceai/pull/2865
- Change `BytesProcessedRule` to be an optimizer rather than an analyzer rule by @phillipleblanc in https://github.com/spiceai/spiceai/pull/2867
- Don't run E2E or PR tests on documentation by @Jeadie in https://github.com/spiceai/spiceai/pull/2869
- Verify benchmark query results using snapshot testing (spice.ai connector) by @sgrebnov in https://github.com/spiceai/spiceai/pull/2866
- feat: Add GraphQLOptimizer by @peasee in https://github.com/spiceai/spiceai/pull/2868
- Update quickstarts for Endgame by @Jeadie in https://github.com/spiceai/spiceai/pull/2863
- Update version to v0.18.3-beta by @sgrebnov in https://github.com/spiceai/spiceai/pull/2882
- Update DataFusion: fix coalesce, Aggregation with Window functions unparsing support by @sgrebnov in https://github.com/spiceai/spiceai/pull/2884
- Revert "Rename `spiceai` data connector to `spice.ai`" by @sgrebnov in https://github.com/spiceai/spiceai/pull/2881
- Adding integration test for DuckDB read functions by @slyons in https://github.com/spiceai/spiceai/pull/2857
- Show more informative mysql error message by @Sevenannn in https://github.com/spiceai/spiceai/pull/2883
- Fix `no process-level CryptoProvider available` when using REPL and TLS by @sgrebnov in https://github.com/spiceai/spiceai/pull/2887
- Change UX for chunking and enable overlap_size in chunking by @Jeadie in https://github.com/spiceai/spiceai/pull/2890
- Add `log/slog` to spice CLI tool by @Jeadie in https://github.com/spiceai/spiceai/pull/2859
- feat: Add GitHub GraphQLOptimizer by @peasee in https://github.com/spiceai/spiceai/pull/2870
- Fix mysql invalid tablename error message by @Sevenannn in https://github.com/spiceai/spiceai/pull/2896
- fix: Remove login column rename in pulls and update Optimizer by @peasee in https://github.com/spiceai/spiceai/pull/2897
- Fix require check checking. by @Jeadie in https://github.com/spiceai/spiceai/pull/2898

**Full Changelog**: https://github.com/spiceai/spiceai/compare/v0.18.2-beta...v0.18.3-beta

Resourcesโ€‹

Communityโ€‹

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.