Analytical storage for agents
Your agents bring the compute. We take care of the storage.
Store your analytical data in shared tables that your agents and tools can read and update. We manage the storage, access and table maintenance. You choose where the queries run.
Built on Apache Iceberg, an open table format supported by multiple query engines.
5 GB free · No credit card · Hosted in Europe
Want to run it yourself? Explore self-hosting →
› SELECT bed, avg(moisture)
FROM garden.moisture
GROUP BY bed;
Illustrative query, not a recorded run.
Paste the prompt into your agent. You approve the connection in your browser. Your agent receives its own revocable access.
DuckDB
PyIceberg
SparkYour tools run the queries. We look after the tables.
Your agent uses an engine such as DuckDB to query data from a laptop, a server or a cloud environment. LakehouseBox provides the shared storage and the catalog that keep those tables available.
With a managed data warehouse
Managed storage and query compute
Store your data and query it with the platform’s managed compute. The platform provides both the storage and the query service.
Useful when you want managed query infrastructure.
With LakehouseBox
Shared tables. Your query engine.
Store shared tables and connect your own query engine. We manage the storage, the access and the table maintenance; your tools run the queries.
Useful when your agents or applications already have somewhere to run queries.
An agent can use DuckDB to work with shared tables without provisioning a separate warehouse. The compute it uses has its own cost; it is compute you already have.
See it in action
Ask a question. Keep the answer.
01Ask a question
Not the rain. 1.2 mm fell on Friday morning and nothing since. Beds 2 and 3 were watered twice, Saturday 04:00 and Sunday 08:00, and drained back within the day each time. Bed 1 got water once, Saturday around 17:00, and has held 21 % since. Bed 4 climbed slowly all weekend, 25 % to 32 %.
Your agent starts with data in your catalog.
02Analyse with DuckDB
The query runs in your agent’s environment.
03Save the result
CREATE TABLE garden.bed_moisture_hourly AS SELECT … ;
A new Iceberg table is ready for another session or an authorised teammate.
The session ends. The data stays.
How this ran
| Data | garden.sensor_readings, 185,884 rows, a real garden's sensors, stored in a LakehouseBox catalog |
| Query | DuckDB 1.5.5 on a laptop, in the agent's environment · 363 ms |
| Saved | back to the catalog in 1,231 ms · reopened by a new process 340 ms after attaching |
| When | Recorded 2026-09-20 against the live service. The chart is drawn from the saved table. The CREATE TABLE ran in DuckDB; the statement above is abbreviated. |
What can you do with LakehouseBox?
Give agents persistent data
Keep tables and results available between sessions and across agents.
Build an analytics project
Query shared data from the laptop or server you already use, with DuckDB, PyIceberg or Spark.
Collect data over time
Append recurring exports, application events or sensor readings to analytical tables, from your agent, the CLI or an ingest endpoint your systems post to.
Share data with others
Give teammates and agents access to the same tables, with read or read-and-write permission per catalog.
Public data
Public data deserves a home, too.
Weather, holidays, places and more: public datasets people and agents can discover and join with their own data. Open formats, with the source, licence and a data card written for an agent.
Seven datasets are live today, public at the storage level. Browse the public data catalog →
Free storage for your public data
The catalog is live. Next is free hosting for datasets you publish: open tables anyone can JOIN with their own. Interested in publishing one? Get in touch.
Our cloud. Your infrastructure. Same LakehouseBox.
Hosted in Europe
Start with our hosted service. We operate the storage, the catalog and the table maintenance on Hetzner servers in Nuremberg, Germany, as a Spanish company. No US-controlled company operates any part of the service or holds your data. Whether a law such as the US CLOUD Act can reach a provider depends on that provider’s ties to the United States; we list every provider in our path, and every dependency outside the EU, on the sovereignty page.
Operator, location, applicable law and the dependency ledger, stated as facts: the sovereignty page.
Start freeSelf-hosted beta
Run LakehouseBox on your own infrastructure with the same agent-facing tools and engine connections. It is a handful of containers, one compose file and one state directory, so it runs wherever Docker runs. Today that is the compose file and the deploy scripts, not a packaged installer; licence and support terms are being decided.
Run today on Hetzner; the other providers are untested. Anything with Docker and a disk should do.
Explore self-hosting →The LakehouseBox blog
Does your agent need a data warehouse?
Before buying more infrastructure, try the compute you already have. An agent, DuckDB and shared Iceberg tables can be enough to get started, and they show you what your workload actually needs.
Read the story“Start with the compute you already have.”
Pricing
Start with a place for your data.
- Apache Iceberg catalog and storageincluded
- Access for people and agentsincluded
- Managed table maintenanceincluded
- Connections for supported enginesincluded
- Up to 10 catalogs per project; 20 snapshots or 7 days of history per tableenforced
- No limit on tables or namespaces. Guideline, not enforced today: 50,000 objects per catalogadvisory
Query compute runs in your environment. LakehouseBox does not bill you for query execution.
Beta. Not yet, and we say so
- One site, no SLA. Off-host copies every 5 minutes for accounts and grants, hourly for table metadata, nightly for data files; restore rehearsed in about 35 minutes; no automatic failover yet. High availability is planned.beta
- Paid plans wait for the company registration; the payment provider will be European.later
- Public datasets. Designed and measured, not switched on.coming
- Snowflake. The catalog integration connects; the data path needs work on both sides.limited
- A full web dashboard. Your account page is small: catalogs, a SQL explorer, access tokens, members, usage.partial
Limits, backups and what is measured: the docs.