Query your lakehouse. Pay per query.
A multi-tenant Iceberg lakehouse with a serverless DuckDB query engine. Connect your data, query it in the browser, and keep every tenant fully isolated.
- ▾ analytics
- ▾ customer_events
- · page_views
- · add_to_carts
- ▸ orders
- ▸ thunder_duck_demo
| country | views |
|---|---|
| US | 48,201 |
| DE | 31,884 |
| GB | 22,517 |
| FR | 19,003 |
| JP | 14,762 |
From raw files to answers in three steps
No warehouse to provision, no ETL to babysit. Connect data, write SQL, and get isolated results with cost you can see.
Connect your data
Create an Iceberg catalog on the managed Nessie server, or point one at flat files in your object store. Each catalog is scoped to your company automatically.
Query in Studio
Write SQL against catalog.schema.table with autocompletion and a live catalog tree. Run it and results stream back, paginated, with timing and the execution plan.
Results, isolated
Every result set lands in your private storage prefix. Track cost and performance per query on the monitoring dashboard — and only ever see your own.
Everything a multi-tenant lakehouse needs
Built for teams that serve many customers from one platform — without ever mixing their data.
True multi-tenancy
Every company gets its own isolated namespace, storage prefix, and query results. Tenants never see each other's data — isolation is enforced at query-rewrite time, not by convention.
Serverless DuckDB engine
Each query runs as a fresh, right-sized job on Kubernetes. No warehouse to keep warm — you pay for the compute a query actually uses, down to the CPU-second.
Iceberg + Nessie catalogs
Versioned Apache Iceberg tables backed by a Nessie catalog. Create schemas and tables, branch and roll back, and query them with plain SQL.
Flat files, no ETL
Point a catalog at Parquet, CSV, or JSONL in MinIO, S3, GCS, or Azure Blob and query it in place. We build the views; you write SELECT.
SQL Studio in the browser
A fast editor with autocompletion, a drill-down catalog explorer, formatting, result pagination, and the execution plan — all one click away.
Usage you can see
Per-query execution time, CPU and RAM, row counts, and success/error rates — on a monitoring dashboard you can filter by user and date range.
See thunderduck on your data.
Book a walkthrough and we'll spin up a workspace with your catalogs.