Follow the source instead of reloading it
Full reloads get slower as the source grows and go stale between runs. Change data capture keeps the dataset in step by applying only what changed.
How it works
Two modes
Polling mode compares against a change column. Log mode reads the database replication slot for a complete, ordered change stream.
Inserts, updates and deletes
A delete at the source becomes a delete in the dataset, rather than a row that lingers because the reload query never saw it.
Ordered application
Changes are applied in the order they happened, so an update followed by a delete does not resurrect a row.
Lineage preserved
The dataset keeps its history through the sync — CDC does not reset what you know about it.
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
What is the difference between polling and log mode?
Polling compares a timestamp or sequence column on a schedule and needs no special database privileges. Log mode reads the replication slot, catches deletes and out-of-band changes that polling misses, and is a Pro capability.
Do I need database admin rights?
Polling mode needs only read access. Log mode needs replication privileges on the source database.
What happens if the sync falls behind?
The lag is reported. In log mode the changes are queued at the source, so catching up applies them in order rather than losing them.
Other ways in
CSV & Excel upload
Drag a file in and start working. Profiled on arrival, no schema declared up front.
Database
Read from your existing relational database and pull tables in as datasets.
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.
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