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.
Amazon S3 Vectors Support: Spice.ai now integrates with Amazon S3 Vectors (opens in a new tab), 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.
Example Spicepod.yml configuration for S3 Vectors:
Example SQL query using S3 Vectors:
For more details, refer to the S3 Vectors Documentation (opens in a new tab).
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":
Example Full-Text-Search (FTS) using the text_search UDTF on the table reviews for the search term "Cricket bats":
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:
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:
Scheduled View Refresh: Accelerated Views now support cron-based refresh schedules using refresh_cron, automating updates for accelerated data.
Example Spicepod.yml configuration:
For more details, refer to Scheduled Refreshes (opens in a new tab).
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:
AWS Bedrock Embeddings Model Provider: Added support for AWS Bedrock embedding models, including Amazon Titan Text Embeddings and Cohere Text Embeddings.
Example Spicepod.yml:
For more details, refer to the AWS Bedrock Embedding Models Documentation (opens in a new tab).
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:
See the Oracle Data Connector documentation (opens in a new tab).
GitHub Data Connector: The GitHub data connector supports query and acceleration of members, the users of an organization.
Example Spicepod.yml configuration:
See the GitHub Data Connector Documentation (opens in a new tab)
Spice.ai Cloud Data Connector: Graduated to Stable (opens in a new tab).
spice-rs SDK Release: The Spice Rust SDK has updated to v3.0.0 (opens in a new tab). This release includes optimizations for the Spice client API, adds robust query retries, and custom metadata configurations for spice queries.
POST v1/search response payload has changed. See the new API documentation (opens in a new tab) for details.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.The Spice Cookbook (opens in a new tab) now includes 72 recipes to help you get started with Spice quickly and easily.
To upgrade to v1.5.0, download and install the specific binary from github.com/spiceai/spiceai/releases/tag/v1.5.0 (opens in a new tab) or pull the v1.5.0 Docker image (spiceai/spiceai:1.5.0).
spice run (#6360) by @Advayp (opens in a new tab) in #6360 (opens in a new tab)vector_search() UDTF in HTTP APIs (#6417) by @Jeadie (opens in a new tab) in #6417 (opens in a new tab)members table type for the GitHub Data Connector (#6464) by @Advayp (opens in a new tab) in #6464 (opens in a new tab)FixedSizeList size during indexing vectors. (#6487) by @Jeadie (opens in a new tab) in #6487 (opens in a new tab)retention_sql acceleration param (#6488) by @sgrebnov (opens in a new tab) in #6488 (opens in a new tab)RwLock on tantivy index in FullTextDatabaseIndex for update concurrency (#6490) by @Jeadie (opens in a new tab) in #6490 (opens in a new tab)JOIN ON (#6491) by @Jeadie (opens in a new tab) in #6491 (opens in a new tab)s3_vectors_basic (#6537) by @sgrebnov (opens in a new tab) in #6537 (opens in a new tab)