VegaDB overview

VegaDB is Vegalake’s distributed database and SQL warehouse. It gives applications, analysts and data teams one PostgreSQL-compatible endpoint for managed data and federated DuckLake, Apache Iceberg and Delta Lake tables.

What you get

Warehouses and data are independent

A warehouse supplies compute for a workload. Catalogs, schemas, tables, permissions and history belong to the workspace. This means you can stop idle compute without deleting data and run separate warehouses for ingestion, BI, data science and high-concurrency applications.

                       ┌─ BI warehouse ───── dashboards
Governed data layer ───├─ ELT warehouse ──── transformations
                       └─ App warehouse ───── APIs and products

Each warehouse exposes one stable connection endpoint and its own size, scaling, timeout and concurrency policy.

Query across clouds and formats

Registered catalogs make external data look like ordinary qualified SQL objects. Credentials stay in Vegalake Secrets and access is governed at workspace, catalog, schema and table level.

SELECT c.segment, sum(o.net_amount) AS revenue
FROM aws_iceberg.sales.orders o
JOIN azure_ducklake.crm.customers c USING (customer_id)
WHERE o.ordered_at >= current_date - INTERVAL '30 days'
GROUP BY c.segment
ORDER BY revenue DESC;

VegaDB keeps a query consistent with the selected table snapshots and versions, including when one statement spans several catalogs.

SQL surface

The SQL language includes joins and subqueries, CTEs and recursive CTEs, set operations, window functions, QUALIFY, PIVOT and UNPIVOT, ASOF JOIN, lateral expressions, prepared parameters, nested types, JSON, arrays, maps, structs, approximate aggregates and vector-distance functions.

Start with the SQL reference for syntax, types, statements, functions and compatibility notes.