SQL Federation & Acceleration | Spice AI
SQL Federation & Acceleration
Federate across data warehouses, data lakes, operational databases, and services, and accelerate data locally for sub-second performance.
Federate and accelerate in a single runtime
Consolidate operational, analytical, and object store data into a governed and accelerated SQL layer.
Easily connect to disparate data sources
Query across data lakes, operational databases, and analytical warehouses. Join, aggregate, and analyze without data movement.
Deliver sub-second query performance
Accelerate frequently-accessed data by materializing and indexing hot tables with local engines like DuckDB and SQLite.
Simplify your data stack
Replace multiple engines, ETL jobs, and custom caches with one lightweight runtime that handles federation, acceleration, and hybrid search in a single environment.
Do more with your data
100x
Up to 100x faster queries
80%
up to 80% cost savings on data lakehouse spend
2x
Increase in data reliability
Engineered for the enterprise
Spice enables data and AI teams to build, scale, and operate production-grade systems without the overhead and complexity of traditional query engines.
Familiar open-source tooling
Connect via JDBC, ODBC, or Arrow Flight to consolidate data from legacy and modern systems. Transform slow or distributed data into fast, interactive experiences using modern open-source engines like Apache DataFusion, DuckDB, and SQLite.
Integrated AI and search workflows
Bring hybrid search and LLM inference into the same SQL environment as your data. Federate, accelerate, compose hybrid search, and call LLMs directly from SQL, all in one governed interface.
Fast, virtualized views
Create virtual tables or materialized views for dashboards, APIs, and applications. Deliver federated and accelerated results with real-time data.
Governance, observability, and control
Monitor data freshness, query latency, and ingest lag with built-in metrics and fully-observable and distributed tracing. Apply role-based access controls across federated data to ensure compliance and auditability at scale.
Proven in production
Run data-intensive workloads on a high-performance engine trusted by teams building real-time systems at scale.
“Spice opened the door to take these critical control-plane datasets and move them next to our services in the runtime path.”
Peter Janovsky
Software Architect, Twilio
“It just spins up and works, which is really nice. The responsiveness is amazing, which is a huge gain for the customer.”
Darin Douglass
Principal Software Engineer, Barracuda
“Partnering with Spice AI has transformed how NRC Health delivers AI-driven insights. By unifying siloed data across systems, we accelerated AI feature development, reducing time-to-market from months to weeks - and sometimes days. With predictable costs and faster innovation, Spice isn't just solving some of our data and AI challenges - it's helping us redefine personalized healthcare.”
Tim Ottersburg
VP of Technology, NRC Health
Integrations across all of your data sources
Accelerate your data stack with a library of 30+ prebuilt connectors for the most common databases, warehouses, and file stores - from Databricks and S3 to MySQL and PostgreSQL.
FAQs
Learn how to connect data sources, enable acceleration, and start querying with Spice.
What is SQL federation?
SQL federation lets you query data across multiple sources as if it were one. With Spice, you can connect directly to systems like S3, PostgreSQL, or Snowflake and execute unified SQL queries. Spice handles source integration, query planning, and result merging automatically without ETL.
How does acceleration in Spice work?
Spice materializes and indexes hot data locally using embedded engines such as DuckDB, PostgreSQL, and SQLite. Frequently-queried data is cached and optimized for sub-second responses, while changes from the source are synced through CDC. This approach delivers analytical performance for operational workloads - ideal for APIs, dashboards, and AI agents.
How is Spice different from other query engines?
Traditional query engines focus on analytics and often require separate systems for federation, caching, and serving. Spice unifies these capabilities in a single runtime built for operational and AI workloads.
What sets Spice apart from other query engines is its broader, application-focused feature set designed for modern data and AI workloads. Spice combines federation, hybrid search, and embedded LLM inference into a single runtime, enabling teams to build complete, end-to-end workflows without the management overhead and performance concessions of using multiple systems.
See Spice in action
Walk through your use case with an engineer and see how Spice handles federation, acceleration, and AI integration for production workloads.