Question 1

How do MongoDB documents map to BigQuery columns?

Accepted Answer

Better than to most warehouses, because the shapes actually line up. Top level fields become columns, embedded documents become RECORD and arrays become repeated fields, so you can query nested data with dot notation and unnest lists without parsing strings. Two caveats. BigQuery has no array of arrays, so a nested list falls back to JSON. And connections made before a 2024 change write all structured values as JSON instead of native types.

Question 2

What does MongoDB change capture need?

Accepted Answer

Change streams, opened at cluster level and filtered to the namespaces and operations you care about, with resume tokens so a run can pick up where it stopped. That means a deployment that supports change streams, so a replica set or sharded cluster rather than a standalone server, and an oplog kept long enough to resume after a pause. The connecting user needs to list databases and collections, read the selected collections and open a cluster level change stream.

Question 3

Why is a MongoDB field missing from my BigQuery table?

Accepted Answer

Most likely because it was not in the sample. Schema inference looks at the hundred most recent documents in a collection, with recursion off, so a field that only appears in older documents or shows up rarely may not make it into the initial schema. You can add it afterwards, and fields discovered later are added to the BigQuery table automatically rather than needing a rebuild. It is worth checking the schema against a collection you know is irregular before trusting it.

Question 4

What happens if the sync falls behind the MongoDB oplog?

Accepted Answer

The change stream reports lost history and that collection needs a resync, so size oplog retention against the longest outage you can imagine rather than the shortest. On deletes themselves: a change stream delete carries only the document key, so a key only tombstone is emitted and the row is marked in BigQuery, or removed outright with hard deletes on. The fallback paths, a full scan or a tracking field query, do not capture deletes at all.

Question 5

Why replicate MongoDB into BigQuery?

Accepted Answer

Because a document store is an awkward place to answer analytical questions. Ad hoc aggregation across collections is difficult and competes with your application for resources. ETL into a data warehouse makes the same documents queryable with SQL and joinable to CRM or billing data, and BigQuery is a particularly good fit because its record and repeated types hold the nested structure rather than forcing you to flatten it away.

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