Store tables in Apache Iceberg and let the Embrasure Engine answer agent queries.
Embrasure is a data warehouse for AI agents. Your tables stay open in Apache Iceberg, and the Embrasure Engine answers agent queries over them. You can keep Snowflake or BigQuery alongside it.
Tables are stored in Apache Iceberg, either in storage buckets you own or in Embrasure-managed storage. Embrasure layers agent-accelerated formats and indexes on top of those tables, so an agent query reads only the data it needs.
Your Iceberg tables remain the source of truth. Other Iceberg-compatible tools can keep reading them.
The Embrasure Engine is Embrasure's query engine for agent workloads. It reads the agent-accelerated formats directly, which suits the many short follow-up queries an agent runs while it explores, checks, and retries.
Embrasure manages the compute.
Embrasure sends each query to the most efficient engine for the data it needs:
| Data | Where the query runs |
|---|---|
| Connected Iceberg tables | The Embrasure Engine, or DuckDB, Trino, or Apache Spark when they suit the query better |
| Data only in Snowflake or BigQuery | Your warehouse, directly |
Routing is automatic. Ember, agents using MCP or the CLI, and SQL in Embrasure all send SQL the same way, and Embrasure picks the engine. See the SQL reference for the dialect and naming rules.
You don't need to move off Snowflake or BigQuery or sync every table to get started. Dashboards and scheduled jobs keep running on your existing warehouse. Connect your warehouse with a read-only identity, as described in cloud and warehouses, and add Iceberg tables as agent workloads grow.
Workspace permissions apply to every query, whichever engine runs it. See security and permissions.