Connect MongoDB to Google BigQuery
Move MongoDB collections into Google BigQuery as flattened, typed rows ready for SQL analytics and dashboards.
- MongoDB · document inserttrigger
- Flatten documentaction
- Append row to BigQueryaction
- Loaded into BigQuerydone
Product data lives in MongoDB as nested documents, but analysts want it in Google BigQuery as flat tables. Spojit reads from MongoDB on change or on schedule, flattens documents into typed columns, and loads them into BigQuery, with durable retries that survive long-running loads.
MongoDB and BigQuery, working together
When a document is inserted in MongoDB
append a flattened row to a Google BigQuery table
When a document is updated in MongoDB
upsert the matching row in Google BigQuery
When a nightly MongoDB collection scan runs
load a full snapshot into a Google BigQuery staging table
When a new event document lands in MongoDB
stream it into a Google BigQuery analytics table
Built for how MongoDB and BigQuery really work
Document flattening
Turn nested MongoDB documents and arrays into typed BigQuery columns you can query with SQL.
No BigQuery connector needed
Miraxa builds the authenticated BigQuery load and streaming API calls without a pre-built connector.
Snapshot or stream
Run full nightly snapshots or change-driven streaming, whichever fits the collection.
Why teams build this on Spojit
MongoDB Atlas offers some BigQuery connectivity, but it can be limited and ties you to specific tiers; generic ELT vendors bill by volume. Spojit reads your collections directly, flattens documents the way your analysts want, and builds the BigQuery API calls itself, billed by execution time.
With Spojit
- Direct Mode loads documents into BigQuery with no AI credits for deterministic flattening.
- Durable execution handles BigQuery load jobs and rate limits with automatic retries.
- Billed by execution time, not per row or gigabyte moved, so large loads stay predictable.
MongoDB + BigQuery, answered
How are nested documents handled?
Spojit flattens nested fields and arrays into typed BigQuery columns, so analysts query flat tables instead of JSON blobs.
Do I need a BigQuery connector?
No. Miraxa builds the authenticated BigQuery API calls, including load jobs and streaming inserts.
Full reload or incremental?
Both. You can snapshot a whole collection nightly or stream individual changes as they happen.
What is possible depends on your plan and authorized API access. Some MongoDB and BigQuery endpoints and capabilities are gated by the vendor (for example, parts of an API may require a higher tier, and write access can require a custom or add-on connection on an eligible plan), so not every workflow is available on every account from day one. You can request a feature or integration any time, and we will get in touch to figure out how to make it work.
Connect MongoDB and BigQuery today
Describe what you want to automate and Miraxa builds the workflow. Start free, no credit card required.