Announcing the release of Spice v0.9.1-alpha! 🧙‍♂️

The v0.9.1 release focused on stability, bug fixes, and usability by adding spice CLI commands for listing Spicepods (spice pods), Models (spice models), Datasets (spice datasets), and improved status (spice status) details. In addition, the Arrow Flight SQL (flightsql) data connector and SQLite (sqlite) data store were added.

Highlights in v0.9.1-alpha​

FlightSQL data connector: Arrow Flight SQL can now be used as a connector for federated SQL query.

SQLite data backend: SQLite can now be used as a data store for acceleration.

Announcing the release of Spice v0.9-alpha! 🧙‍♂️

The v0.9 release adds several data connectors including the Spice data connector for the ability to connect to other Spice instances. Improved observability for the Spice runtime has been added with the new /metrics endpoint for monitoring deployed instances.

Highlights in v0.9-alpha​

Arrow Flight SQL endpoint: The Arrow Flight endpoint now supports Flight SQL, including JDBC, ODBC, and ADBC enabling database clients like DBeaver or BI applications like Tableau to connect to and query the Spice runtime.

Spice.ai data connector: Use other Spice runtime instances as data connectors for federated SQL query across Spice deployments and for chaining Spice runtimes.

Keyring secret store: Use the operating system native credential store, like macOS keychain for storing secrets used by the Spice runtime.

PostgreSQL data connector: PostgreSQL can now be used as both a data store for acceleration and as a connector for federated SQL query.

Databricks data connector: Databricks as a connector for federated SQL query across Delta Lake tables.

S3 data connector: S3 as a connector for federated SQL query across Parquet files stored in S3.

Metrics endpoint: Added new /metrics endpoint for Spice runtime observability and monitoring with the following metrics:

- spiced_runtime_http_server_start counter
- spiced_runtime_flight_server_start counter
- datasets_count gauge
- load_dataset summary
- load_secrets summary
- datasets/load_error counter
- datasets/count counter
- models/load_error counter
- models/count counter

Announcing the release of Spice v0.8-alpha! 🏹

This is a minor release that builds on the new Rust-based runtime, adding stability and a preview of new features for the first major release.

Highlights in v0.8-alpha​

Secrets management: Spice 0.8 runtime can now configure and retrieve secrets from local environment variables and in a Kubernetes cluster.

Data tables can be locally accelerated using PostgreSQL

Announcing the release of Spice v0.7-alpha! 🏹

Spice v0.7-alpha is an all new implementation of Spice written in Rust. The Spice v0.7 runtime provides developers with a unified SQL query interface to locally accelerate and query data tables sourced from any database, data warehouse, or data lake.

Learn more and get started in minutes with the updated Quickstart in the repository README!

Highlights in v0.7-alpha​

DataFusion SQL Query Engine: Spice v0.7 leverages the Apache DataFusion query engine to provide very fast, high quality SQL query across one or more local or remote data sources.

Data tables can be locally accelerated using Apache Arrow in-memory or by DuckDB.

In February, we announced Spice.ai OSS v0.6 with its data processing and transport completely rebuilt upon Apache Flight. This enables Spice.ai OSS to scale to datasets 10-100 times larger and brings Spice.ai into the Apache Arrow ecosystem paving the way for integrations with many popular projects, like Apache Parquet, pandas and big data systems like Hive, Drill, Spark, Snowflake, BigQuery, and many more.

In Spice.ai OSS v0.6.1 we announced a new big data system integration… our own, Spice.xyz!

Figure 1. Spice.xyz - Data and AI infrastructure for web3