Flexible storage
Use managed data, federated sources or open lakehouse formats across your preferred object stores.
The data + intelligence plane
SQL, vector search and live operational data.
Bring SQL, vector retrieval and streaming data together on a massively parallel engine. Choose managed or open storage and place compute where the organization needs it.
01
SELECT region, sum(net_amount) AS revenue02
FROM lakehouse.sales.orders03
WHERE ordered_at >= current_date - INTERVAL '30 days'04
GROUP BY region05
ORDER BY revenue DESC;06
07
→ warehouse analytics-prod · 12 ms first batchSTATUSREADYREGIONME-CENTRAL
VegaDB / role in the platform
Use VegaDB for analytical SQL, vector retrieval and real-time operational data. Query business data alongside the metrics, logs and traces produced by your workflows.
Capabilities
What you can build with VegaDB
Vector retrieval
Keep semantic retrieval beside governed operational and analytical data for context-aware applications.
Massively parallel SQL
Execute demanding analytical work across elastic, distributed compute with familiar SQL.
Distributed execution
Place compute close to data across cloud, on-premises and controlled environments.
Real-time operational store
Unify run events, metrics, logs, traces and graph changes for immediate operational decisions.
Workload isolation
Scale BI, transformation, exploration and application workloads independently over shared governed data.
How it works
Follow the data and execution.
01
Place
Choose managed, federated or open storage and put compute where the workload requires it.
02
Query
Use SQL, vector search and streaming access through familiar PostgreSQL-compatible tools.
03
Scale
Run queries in parallel and give each workload its own compute over shared data.
04
Serve
Serve query results to applications, agents and dashboards.
VegaDB / start with one outcome