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ConnectorData & events
BigQuery
Governed aggregates from your BigQuery datasets, one canonical definition per metric.
Ask how BigQuery fits what you run.
Answers are based on this listing. For anything it can't answer, our team can.
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About
The BigQuery connector pulls the aggregates behind an operator's metrics from the datasets you grant, running as a service account you create and can revoke. Paired with a semantic pack, each metric compiles to one canonical query, so the number an operator quotes is auditable back to the SQL and the dataset that produced it. Authorized views work naturally here: you can expose exactly the columns the connector should see and nothing else.
The target contract requires verified tenant and source-dataset context and explicit fallback labels. Resumability, coverage, and bookkeeping behavior must be validated for the deployment. BigQuery is managed early access and deliberately read-mostly.
Highlights
- Pulls governed aggregates
- One canonical definition per metric
- Writes use idempotency keys and single-flight controls to suppress duplicate effects on retry
- Provisioned with a deployment engineer through the early-access program
- Kind
- Connector
- Category
- Data & events
- Publisher
- Fibric
- Availability
- Early access
- Delivery
- Managed by Fibric; nothing to install
- Data direction
- Reads and writes
- Pricing
- Early access
- Sold by
- Fibric
- Support
- Developed and supported by Fibric
- Tags
- warehouse, analytics, metrics, real-data
Authentication
A Google Cloud service account with BigQuery read roles on the datasets you grant, its key stored in your tenant's secret store.
What it reads
- Metric query results from the datasets you grant
- Table and partition freshness, so stale sources are flagged
- The connector's own job history, for cost visibility
What it can do
- Records read cursors and query receipts in its own dataset
- Tags records it has processed
How it works
1
Sense
Metric query results from the datasets you grant.
2
Reason
Operators reason over this connector's signals next to the rest of your stack, so decisions are grounded in the same records you run on.
3
Act
Target capability: Records read cursors and query receipts in its own dataset. Actual authority, duplicate controls, and recovery depend on the validated deployment and downstream system.
Pricing
Managed early access
This listing is informational and not self-serve. A deployment review must validate the connector, credentials, action boundary, recovery path, support, and contractual pricing before use.
- Deployment engineer
- Wires and verifies the integration with you during onboarding
- Managed validation
- Review maturity, authority, supported records, and deployment boundaries before go-live
- Execution records
- Supported reads, proposals, policy decisions, and reported outcomes kept for review
- Support from the builders
- Developed, run, and supported directly by Fibric
Requirements
- A Google Cloud project with BigQuery enabled
- A service account granted read access, via dataset roles or authorized views, on what your metrics need
Your deployment engineer verifies each line with you during onboarding.
Support and resources
Supported by the people who built it
This connector is developed, run, and supported by the same Fibric team. Support starts during onboarding with a named deployment engineer and doesn't hand you off afterward.
Works with
Listings this is designed to pair with. Each listing has its own live or managed early-access state.
Data & events connector
Snowflake
A managed early-access pattern for querying governed warehouse metrics with source context and explicit missing-state handling.
View details
Data & events connector
PostgreSQL
Reads your operational tables under row-level tenant isolation, the same wall that keeps tenants out of each other's data.
View details
Data & events connector
Amazon S3
Watches a bucket for the report, feed, or proof file that lands: an inbox an ingest operator can pick up and normalize.
View details
This connector is developed, published, and supported by Fibric. It integrates with BigQuery through published APIs. Third-party names and logos identify the systems an integration connects to; they are the property of their respective owners, who are not affiliated with Fibric and do not sponsor or endorse this listing. Trademark policy
Bring BigQuery into your early-access deployment
Early access means a deployment engineer wires this with you, and it runs propose-only until you approve live actions.