Data & Storage · Integration
Snowflake
Add Snowflake to your product for your customers, and give your AI agents governed access to it.
An embedded Snowflake integration lets a customer aim your product at their own warehouse rather than shipping you an extract. Reads and writes cover databases, schemas, tables and views, and queries execute on the warehouse the customer nominates, under the role they granted. What separates Snowflake from a plain database is that compute is billed by the second while a warehouse is running, so a careless query pattern shows up on their bill rather than yours, and sizing becomes part of the integration design. Authentication is usually key-pair rather than a password, held by a service user with its own grants. fastn stores those per-tenant credentials, rotates them, and tracks Snowflake's API as it changes.
In your product
Embedded for your customers. Per-tenant auth, no per-customer code, maintained by fastn.
Let each customer nominate their own warehouse and role, so your product queries their databases and schemas without data leaving Snowflake.
Write the output of work done in your product into a customer's table, so their analysts see it beside everything else they model.
Read the schema list during setup so your configuration screens offer that customer's real tables instead of a hard-coded list.
Keep queries scoped and warehouse sizing sensible so per-second compute spend stays predictable as your usage grows.
For your AI agents
Governed, audited access for the agents you build, through the MCP server.
An agent answers a reporting question by querying one customer's warehouse, with the role it ran under recorded.
An agent writes a summarised result set into a table it has been granted access to, and that write is logged.
An agent checks which schemas and views it can actually see before attempting a query, rather than guessing.
Example prompt
Query the orders table in this schema for last quarter's revenue and break it down by region.
Set up Snowflake in 4 steps
- 01Enable the Snowflake connector from your fastn dashboard.
- 02Have each customer authorise their own Snowflake account, so calls run under their credentials rather than a shared key.
- 03Decide which records, datasets and fields your product needs, map those fields, then enable the actions and triggers you want.
- 04Call it from your product and expose it to your agents through the same governed connection.
Why teams use the Snowflake integration
What you get by embedding it with fastn instead of building it yourself.
- Ship a Snowflake integration without building it. Your customers connect their own Snowflake account inside your product and work their records, datasets and fields there, with no per-customer code on your side.
- Handle the part that actually costs time: schemas differ per customer and change without notice, and volumes can be large. fastn owns the auth, token refresh, rate limits, pagination and breaking-change fixes, so a Snowflake update is not your on-call problem.
- One integration serves your product and your agents. The same governed Snowflake connection powers in-product features and gives AI agents scoped, audited access, so you read and write your customers' data where it already lives without wiring it twice.
Used by these teams
Compare with
BigQuery
Databricks
AWS RedshiftOften used alongside
Tools the same teams tend to run next to Snowflake, across other categories.
Anthropic Claude
OpenAI
Azure OpenAI
Hugging FaceSnowflake integration FAQ
How do I add a Snowflake integration to my product?
Enable the Snowflake connector in your fastn dashboard, then let each customer authenticate their own Snowflake account. fastn handles the OAuth flow, token storage and refresh per tenant, so there is no Snowflake client code in your app and no per-customer branch in your codebase. Setup is 4 steps.
Do my customers each connect their own Snowflake account?
Yes. Every connection is scoped to the individual customer, so each authorises their own Snowflake account and only ever sees their own records, datasets and fields. That per-tenant isolation is the point of an embedded integration: you support the long tail of customer setups without maintaining an integration per customer.
Can AI agents use this Snowflake integration?
Yes. The same connection is exposed to your agents through the fastn MCP gateway, with permissions scoped per tenant and every call audited. An agent answers a reporting question by querying one customer's warehouse, with the role it ran under recorded.
Who maintains the Snowflake integration?
fastn does. When Snowflake changes an endpoint, deprecates a field or alters its auth, the fix lands in the connector rather than in your backlog, and your customers' connections keep working.
Does the Snowflake integration adapt when a customer's schema changes?
Schema and field mapping is configuration per customer, so a change on their side is a mapping update rather than a code change and a release on yours.
How are large Snowflake reads handled?
Pagination and throttling are handled for you, and initial backfills are rate-limited so a large import does not exhaust a customer's API allowance.
What can I build with the Snowflake integration?
A common starting point: let each customer nominate their own warehouse and role, so your product queries their databases and schemas without data leaving Snowflake. Teams also use it for the other use cases listed above, and expose it to agents for governed reads and writes.
How much does the Snowflake integration cost?
It is included. Pricing is based on connected accounts, not on how many connectors you enable, so adding Snowflake does not change your per-connector cost. You can start free with 3 connected accounts.
Add Snowflake to your product
Start free with 3 connected accounts. No sales call required, and no per-customer integration code.