SaaS Native Warehouse Connectors Threaten Fivetran
Conor McCarter, co-founder of Prequel, on Fivetran's existential risk
Data warehouse export is attractive because it turns an existing byproduct of a SaaS product into high margin add on revenue. The vendor already stores the raw events and records. The extra work is packaging them into Snowflake, BigQuery, Redshift, or Databricks reliably. That lets the SaaS company capture spend that would otherwise go to Fivetran, while also making the product stickier because customers can analyze the vendor’s data alongside everything else in their warehouse.
-
The unit economics can be unusually good. Native connectors are often sold as a premium feature, with examples ranging from per transaction pricing to packaging the connector as 10% to 30% of annual contract value. The underlying data already exists, so pricing is driven more by workflow value than by content creation cost.
-
This is why native connectors threaten Fivetran’s best SKUs first. Fivetran charges by usage and built a business around maintaining roughly 200 high trust connectors, but high volume sources like Stripe are exactly where a SaaS vendor has the most reason to internalize the connection and keep that revenue stream.
-
Reliability is the gate. Third party ETL tools earn their premium by handling API changes, rate limits, sync failures, and edge cases around the clock. A connector only becomes massively profitable after a vendor can deliver warehouse sync with the same integrity, because broken data exports create support load and erode trust fast.
The direction of travel is toward warehouse sync becoming a standard enterprise feature for larger SaaS vendors. As more products bundle native export into higher tiers, connector revenue shifts from standalone ETL vendors toward the software companies that own the source data, and third party platforms are pushed toward the long tail, cross source orchestration, and observability.