LavaLake
LavaLake combines a data warehouse and lakehouse with SQL, dashboards, and AI agents for deployment in a customer's own data center.
What LavaLake is
LavaLake combines a data warehouse and lakehouse with SQL, dashboards, and AI agents for deployment in a customer's own data center. Its built-in assistant can find data, query metrics, and create dashboards under the signed-in user's permissions. An included MCP server also lets external agents use platform tools with those permissions. The product lists read-only database connections for PostgreSQL, MySQL, MS SQL Server, SAP Business One, and SAP S/4HANA; it can import CSV and DATEV files and search PDF, Word, and text documents. Hybrid search combines vector and keyword results using a locally run embedding model with PostgreSQL and pgvector. The lakehouse uses Apache Iceberg on S3-compatible storage, Nessie, and Trino. Tableau and Power BI connect through a read-only HTTP feed. The free Core plan has no time limit and supports up to 16 vCPU on one machine. High availability and fully air-gapped operation are planned, while change data capture and continuous ingestion are in development.
Good
- Assistant actions run under signed-in user permissions
- Includes SQL analytics and dashboards
- Searches PDF, Word, and text documents
- Read-only feed supports Tableau and Power BI
- Free Core plan has no time limit
Watch out
- High availability is listed as planned
- Fully air-gapped operation is listed as planned
- Change data capture and continuous ingestion remain in development
- Kubernetes Helm path has operational gaps
Who it suits
LavaLake may suit teams that want analytics and AI tools deployed in their own data center, with access controls applied to assistant and BI activity. It is also relevant to teams working with its listed database, file, and document sources.
Verdict
LavaLake brings governed analytics, lakehouse storage, search, and AI assistance into a self-hosted deployment. Teams needing high availability, full air-gapping, or continuous ingestion should note those capabilities are not currently listed as complete.
Plans and prices
From LavaLake's own pricing page, checked 7 Oct 2026.
| Plan | Price | What it gives you |
|---|---|---|
| Core | Free | Up to 16 vCPU · single machine · community support · free; no time limit |
| Team | €249 a month | Up to 192 vCPU · up to 10 users · ticket support, answer within a business day · per month |
| Business | €1,250 a month | Up to 512 vCPU · unlimited users · 8/5 support with a committed response time · per month |
| Enterprise | €2,499 a month | Unlimited vCPU · unlimited users · named contact · migration support included · per month, per cluster |
The facts
Each one read from LavaLake's own pages, with the date it was checked.
What it does
- Access controls
- The security design uses Keycloak OIDC, RFC 8693 token exchange, Trino-enforced row access and column masking, and a WORM hash-chain audit log.checked 7 Oct 2026
- AI assistant
- Its built-in assistant can find data, query metrics, and create dashboards, with actions running under the signed-in user's permissions.checked 7 Oct 2026
- AI data handling
- The maker says the lakehouse and local search stay on the customer's network, while external AI providers receive conversation content and assistant tool results.checked 7 Oct 2026
- BI integrations
- A read-only HTTP feed supports Tableau and Power BI, applying the analyst's identity and recording data fetches in the audit chain.checked 7 Oct 2026
- Data sources
- The product lists PostgreSQL, MySQL, MS SQL Server, SAP Business One, and SAP S/4HANA as read-only database sources.checked 7 Oct 2026
- Deployment
- The reference deployment is a Docker Compose stack on one machine, with Ansible installation for Debian/Ubuntu; the Kubernetes Helm path has operational gaps including policy integration.checked 7 Oct 2026
- Files and documents
- It supports CSV and DATEV file imports and makes PDF, Word, and text documents searchable.checked 7 Oct 2026
- MCP
- The platform includes an MCP server that lets external agents use platform tools under the user's permissions.checked 7 Oct 2026
- Notable limitations
- High availability and fully air-gapped operation are listed as planned, and change data capture and continuous ingestion are in development.checked 7 Oct 2026
- Purpose
- LavaLake combines a data warehouse and lakehouse with AI agents, SQL, and dashboards for deployment in a customer's own data center.checked 7 Oct 2026
- Search
- Hybrid search combines vector and keyword results using a locally run nomic-embed-text model and PostgreSQL with pgvector.checked 7 Oct 2026
- Storage and formats
- The lakehouse uses Apache Iceberg on S3-compatible storage with Nessie as its versioned catalog and Trino as its query engine.checked 7 Oct 2026
The company
- Founded
- 2026checked 28 Sep 2026
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