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The fastest lakehouse SQL engine, replacing Trino/Presto, SparkSQL
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The most cost-effective alternative to Elasticsearch observability
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The AI-Ready analytics database for the AI era
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One catalog across VeloDB and your whole lakehouse.
Datastrato builds the open metadata layer for the modern data stack. Paired with VeloDB, you get a single catalog that spans warehouse tables, lakehouse files, and streaming sources — discoverable from BI tools, AI agents, and engines alike.
What Datastrato does
Datastrato unifies metadata across heterogeneous storage and engines, so teams can find, govern, and query data without managing a catalog per system. Schemas, lineage, and access policies stay consistent end-to-end.
Why VeloDB + Datastrato
Single source of truth
Register VeloDB tables alongside Iceberg, Hive, and other sources in one catalog — no duplicate definitions to keep in sync.
Multi-engine federation
Engines that speak the catalog can discover VeloDB tables and route queries appropriately, without bespoke connectors.
Governance built in
Apply access policies and capture lineage centrally; VeloDB inherits the same controls used across the rest of the stack.
Open by design
Datastrato is built on open standards, so you keep portability and avoid lock-in to any single warehouse or platform.
What you can build
Lakehouse-wide search
Help analysts and AI agents find the right VeloDB table among thousands of datasets across systems.
Cross-engine analytics
Let federated query engines pick up VeloDB tables from the catalog and join them with lakehouse data on demand.
Centralized governance
Manage row/column policies, tags, and lineage from one place; enforce them whether the query lands in VeloDB or elsewhere.
How the data flows
Ready to get started?
Tell us about your stack and use case. Our team will help you stand up VeloDB with Datastrato for your environment.
