Snowflake
Fidero streams every enriched event into your own Snowflake through Snowpipe Streaming, under a schema it provisions and maintains for you. The data lands in your Snowflake account, not ours.
| Channel | Server |
| Consent category | None – your warehouse receives every event that reaches Fidero, regardless of consent state. Consent & privacy covers why |
| Data residency | Your Snowflake account’s region |
| Sync cadence | Real-time on Growth and Business, daily on Starter |
What it delivers
Section titled “What it delivers”- Every enriched event. Not just conversions – the complete, attributed record streams in, including events that never touched a browser, like a renewal or a webhook. How the pieces fit traces one event end to end
- The schema every destination reads. Each event lands with its name, type,
identifiers and timestamps in typed columns, and its properties, context and
traits in
VARIANTcolumns. Data schema lists every field - A latest-traits view. Fidero maintains a
USER_TRAITS_VIEWgiving the most recent value of each trait per user, so you don’t write the window query yourself
What you provide
Section titled “What you provide”| Item | Detail |
|---|---|
| Account and user | Your Snowflake account identifier and a user for Fidero to connect as, optionally under a named role. |
| Compute warehouse | A warehouse for the provisioning and erasure statements Fidero runs. Streaming ingestion doesn’t use it. |
| Database | The database Fidero creates its schema in – it defaults the schema to FIDERO. |
| Key-pair | A key-pair for authentication. Fidero holds the private key – the public key is registered on the user. |
That’s the whole connection. You enable the warehouse like any other destination – request it, and the same enrichment and delivery monitoring apply. What every destination receives covers the standard treatment.
What’s automatic
Section titled “What’s automatic”- Provisioning. Fidero creates the schema, the
EVENTStable and theUSER_TRAITS_VIEWon first delivery – nothing to set up by hand - Auto-clustering. The events table is clustered by ingestion date, so Snowflake keeps date-scoped queries fast as the table grows
- A schema that absorbs any event. Properties, context and traits land in
VARIANTcolumns, so a new event shape never needs a table migration - Erasure requests. A delete request for a user removes the rows recorded under their user ID from the events table – events from before they identified, which carry only an anonymous ID, aren’t matched
The warehouse copy is yours to keep. Data ownership & portability covers what stays with you if you leave.