Luke Kim

🎉 Today marks the 1.0-stable release of Spice.ai Open Source—purpose-built to help enterprises ground AI in data. By unifying federated data query, retrieval, and AI inference into a single engine, Spice mitigates AI hallucinations, accelerates data access for mission-critical workloads, and makes it simple and easy for developers to build fast and accurate data-intensive applications across cloud, edge, or on-prem.

Announcing the release of Spice v1.0-rc.3 🧊

Spice v1.0.0-rc.3 is the third release candidate for the first major version of Spice.ai OSS. This release continues the focus on production readiness and includes new Iceberg Catalog APIs, DuckDB improvements, and a new Iceberg Catalog Connector.

Highlights in v1.0-rc.3​

• Iceberg Catalog APIs: Spice now functions as an Iceberg Catalog provider, implementing a core subset of the Iceberg Catalog APIs. This enables Iceberg Catalog clients native discovery of datasets and schemas through Spice APIs.

• GET /v1/namespaces - List all catalogs registered in Spice.

• GET /v1/namespaces?parent=catalog - List schemas registered under a given catalog.

• GET /v1/namespaces/:catalog_schema/tables - List tables registered under a given schema.

• GET /v1/namespaces/:catalog_schema/tables/:table - Get the schema of a given table.

• Iceberg Catalog Connector: The Iceberg Catalog Connector is a new integration to discover and query datasets from a remote Iceberg Catalog.

Example connecting to a remote Iceberg Catalog with tables stored in S3:

catalogs:
  - from: iceberg:https://my-iceberg-catalog.com/v1/namespaces
    name: ice
    params:
      iceberg_s3_access_key_id: ${secrets:ICEBERG_S3_ACCESS_KEY_ID}
      iceberg_s3_secret_access_key: ${secrets:ICEBERG_S3_SECRET_ACCESS_KEY}
      iceberg_s3_region: us-east-1

View the Iceberg Catalog Connector documentation for more details.

• DuckDB Improvements: Added cosine_distance support for DuckDB-backed vector search, improved unnest nested type handling for array_element and lists, and optimized query performance.

• SQLite Data Accelerator: Graduated to Release Candidate (RC).

• File Data Accelerator: Graduated to Release Candidate (RC).

Announcing the release of Spice v0.19.1-beta 🔥

Spice v0.19.1 brings further performance and stability improvements to data connectors, including improved query push-down for file-based connectors (s3, abfs, file, ftp, sftp) that use Hive-style partitioning.

Highlights in v0.19.1​

TPC-H and TPC-DS Coverage: Expanded coverage for TPC-H and TPC-DS benchmarking suites across accelerators and connectors.

GitHub Connector Array Filter: The GitHub connector now supports filter push down for the array_contains function in SQL queries using search query mode.

NSQL CLI Command: A new spice nsql CLI command has been added to easily query datasets with natural language from the command line.

Announcing the release of Spice v0.17.4-beta.

The v0.17.4-beta release adds compatibility, performance, and reliability improvements to the DuckDB and SQLite accelerators. The GitHub data connector adds a Stargazers table, Snowflake and Clickhouse data connectors have improved resiliency for empty tables, and core data processing and quality has been improved.

Highlights in v0.17.4-beta​

Improved benchmarking, testing, and robustness of data accelerators: Continued compatibility, performance, and reliability improvements for SQLite and DuckDB data accelerators and expanded performance and quality testing.

GitHub Stargazers: The GitHub Data Connector adds support for a /stargazers table making it easy to query GitHub Stargazers using SQL!

The v0.16-alpha release is the first candidate release for the beta milestone on a path to finalizing the v1.0 developer and user experience. Upgraders should be aware of several breaking changes designed to improve the Secrets configuration experience and to make authoring spicepod.yml files more consistent. See the [Breaking Changes](#Breaking Changes) section below for details. Additionally, the Spice Java SDK was released, providing Java developers a simple but powerful native experience to query Spice.

Highlights in v0.16-alpha​

• Secret Stores: More than one Secret Store can now be specified. For example, to configure Spice with both Environment Variable and AWS Secrets Manager Secret Stores, use the following secrets configuration in spicepod.yaml:

secrets:
  - from: env
    name: env
  - from: aws_secrets_manager:my_secret_name
    name: aws_secret

Secrets managed by configured Secret Stores can be referenced in component params using the syntax ${<store_name>:<key>}. E.g.

datasets:
  - from: postgres:my_table
    name: my_table
    params:
      pg_host: localhost
      pg_port: 5432
      pg_pass: ${ env:MY_PG_PASS }

• Java Client SDK: The Spice Java SDK has been released for JDK 17 or greater.

• Federated SQL Query: Significant stability and reliability improvements have been made to federated SQL query support in most data connectors.

• ODBC Data Connector: Providing a specific SQL dialect to query ODBC data sources is now supported using the sql_dialect param. For example, when querying Databricks using ODBC, the databricks dialect can be specified to ensure compatibility. Read the ODBC Data Connector documentation for more details.