Connect the database you already have
A database connection brings its schema with it. Tables land as datasets, and the schema becomes the first draft of your source model instead of something you retype into a modelling tool.
How it works
Schema comes across
Tables, columns, types and declared keys are read from the database and used to seed the source model.
Select what you need
Pull specific tables rather than mirroring the whole database, and add more later without reconnecting.
Credentials held once
The connection owns its credentials. Rotating a password means editing one connection, not every flow that reads from it.
Read-oriented
The connector reads. Writing back is an explicit publishing action, not a side effect of a pipeline run.
What happens after it lands
Once rows are in the catalogue, the connector that produced them stops mattering. The dataset is profiled, can be cleaned, modelled, put in a flow, governed and published exactly like every other dataset — which means switching how data arrives never means rebuilding what happens to it afterwards.
Questions about this connector
Does DataLens write back to my database?
Only when you publish to it deliberately. Reading a source never modifies it.
Can I pull only part of a table?
Yes — filters are applied at the source so you land the rows you need rather than the whole table.
How do I keep the dataset current?
Either re-run the load on a schedule as part of a flow, or use the CDC connector so changes follow the source continuously.
Other ways in
CSV & Excel upload
Drag a file in and start working. Profiled on arrival, no schema declared up front.
REST API
Point at an endpoint, map the response shape, and land it as rows.
FTP & SFTP
Collect the drops that still arrive as files on a server.
CDC sync
Change data capture, so the dataset follows the source instead of ageing.
CRM
Bring customer records across without exporting them to a spreadsheet first.
Data lake
Read from — and write back to — object storage you already own.
Documents
PDFs and documents stored whole, for retrieval and generation rather than rows.
AI model providers
Your own model credentials, held as a connection like any other source.
See it on your own data
DataLens is in private beta. Bring a file, a database or an API and work through the whole lifecycle in one sitting.
Request beta access