Data & Storage · Integration
Vertica
Add Vertica to your product for your customers, and give your AI agents governed access to it.
Vertica is a columnar, massively parallel SQL database built for analytics at volumes a row store struggles with, and the thing that sets it apart from every other warehouse in this catalogue is the projection. Data is physically stored as projections, which are sorted and encoded copies of a table, and a query is fast or slow depending on whether a suitable one exists. An integration that ignores that will ship a query which looks fine in test and crawls on real data. Deployments vary too: Enterprise mode keeps storage on the nodes while Eon mode separates compute from communal object storage, and a customer might run either, on their own hardware or in a cloud. Vertica came from HP, passed through Micro Focus and belongs to OpenText now, so there is no independent Vertica site left to point at. fastn holds each connection's credentials per tenant.
In your product
Embedded for your customers. Per-tenant auth, no per-customer code, maintained by fastn.
Have each customer point your product at the Vertica cluster they already run, so analytics happen where the data sits.
Run parameterised SQL against the schemas and tables a customer nominates, with results scoped to the connection they authorised.
Select only the columns you need, since a columnar store rewards a narrow read and punishes asking for everything.
Write results your product produced back into a table the customer's existing reports already query.
For your AI agents
Governed, audited access for the agents you build, through the MCP server.
An agent inspects the schema and the available projections before it composes a query.
An agent answers a question from the customer's own tables, and the query it ran is recorded.
An agent writes to a table it has been permitted to write to, and to nothing else.
Example prompt
Query the events table for the last 30 days and break the totals down by channel.
Set up Vertica in 4 steps
- 01Enable the Vertica connector in your fastn dashboard.
- 02Have each customer supply their own cluster host and database credentials, and note whether they run Enterprise or Eon mode.
- 03Map the schemas, tables and columns your product reads, and check which projections exist before you depend on a query at volume.
- 04Call it from your product and expose the same connection to your agents through the MCP gateway.
Why teams use the Vertica integration
What you get by embedding it with fastn instead of building it yourself.
- Ship a Vertica integration without building it. Your customers connect their own Vertica 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 Vertica update is not your on-call problem.
- One integration serves your product and your agents. The same governed Vertica 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
Snowflake
BigQuery
TableauOften used alongside
Tools the same teams tend to run next to Vertica, across other categories.
Anthropic Claude
OpenAI
Azure OpenAI
Hugging FaceVertica integration FAQ
How do I add a Vertica integration to my product?
Enable the Vertica connector in your fastn dashboard, then let each customer authenticate their own Vertica account. fastn handles the OAuth flow, token storage and refresh per tenant, so there is no Vertica client code in your app and no per-customer branch in your codebase. Setup is 4 steps.
Do my customers each connect their own Vertica account?
Yes. Every connection is scoped to the individual customer, so each authorises their own Vertica 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 Vertica 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 inspects the schema and the available projections before it composes a query.
Who maintains the Vertica integration?
fastn does. When Vertica 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 Vertica 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 Vertica 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 Vertica integration?
A common starting point: have each customer point your product at the Vertica cluster they already run, so analytics happen where the data sits. 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 Vertica integration cost?
It is included. Pricing is based on connected accounts, not on how many connectors you enable, so adding Vertica does not change your per-connector cost. You can start free with 3 connected accounts.
Add Vertica to your product
Start free with 3 connected accounts. No sales call required, and no per-customer integration code.