Who benefits from the warehouse connection?

Mainly larger organisations that already run a data warehouse with ETL. For small and mid-sized teams an automation service is usually simpler and cheaper.

Is snori more of a source or a target?

Mostly a source: structured knowledge flows into the warehouse. Through reverse ETL, snori can also be a target and receive prepared data back.

Which tools can I use?

In principle any that can talk to a REST interface – such as Fivetran, Airbyte, Hightouch or Census. snori provides the Workspace API; you steer the pipeline in your tool.

What does the connection cost extra with snori?

Nothing. The Workspace API is included in the plan. Only the cost of your pipeline tool and your warehouse applies, not snori.

Data pipelines & ETL: Fivetran, Airbyte & co.

If you analyse data centrally in a data warehouse, you move it through pipelines: ETL tools pull data together from many sources, reverse ETL pushes it back into operational systems. snori fits in here as a clean, structured source and as a destination. Honestly, this route pays off mainly if you already run a warehouse – for smaller teams an automation service is usually the easier choice.

What are data pipelines, ETL and reverse ETL?

ETL stands for "extract, transform, load": data is extracted from source systems, reshaped and loaded into a central destination – classically a data warehouse like Snowflake or BigQuery. Fivetran and the open-source tool Airbyte are well-known examples that automate exactly this. The reverse route is called reverse ETL: pushing prepared data from the warehouse back into operational tools – Hightouch and Census (now part of Fivetran) do this. Closely related are customer data platforms like Segment, which collect event data and distribute it onward. Together these tools form the infrastructure larger organisations use to bring their data together and send it back out.

snori and your pipeline: the directions

Here snori is above all a source, but can also be a destination.

snori as the source – knowledge flows into the warehouse

Your smart tables and pages in snori are structured and therefore well suited to a warehouse. Through the Workspace API an ETL tool pulls the content and loads it alongside your other data sources into the warehouse – a clean, curated complement to raw and transactional data.

snori as the target – prepared data comes back

The other way round, reverse ETL can push results from the warehouse back into snori: an enriched customer profile, a computed segment, a prepared metric lands as a row or page where your team works with it.

How to set up the connection

In snori, open the settings for the Workspace API and create an access key for this specific workspace.
You decide what that key may do: read only, append, change or also delete.
In your ETL or reverse-ETL tool you set up snori as a source or destination and enter the key.
Done: the pipeline handles the transport in the direction and on the schedule you set.

No server, no code on the snori side – you run the pipeline itself in your analytics stack.

Who can access your data

This is where snori is different. An access key in snori can never do more than you allow. You decide separately for each connection: may the pipeline only read, or also write? See only this one workspace, or several? Every change is versioned and can be rolled back. So you connect snori to your warehouse without losing control of your content – and your data stays encrypted in a German data centre.

Does your setup really need a pipeline?

Be honest with yourself here: a data warehouse with ETL pays off when you analyse many data sources centrally. For most teams the more direct route is simpler – an automation service like Zapier, Make or n8n connects snori without a warehouse. And if you want no service in between at all, you talk to snori directly via the Workspace API.