BigQuery
B
BigQuery

tap-bigquery (matatika variant)

BigQuery data warehouse extractor

Settings

Batch Config Encoding Compression

Compression format to use for batch files.

Batch Config Encoding Format

Format to use for batch files.

Batch Config Storage Prefix

Prefix to use when writing batch files.

Batch Config Storage Root

Root path to use when writing batch files.

Google Application Credentials

JSON content or path to service account credentials.

Google Storage Bucket

An optional Google Storage Bucket, when supplied a file based extract will be used.

Filter Schemas

If an array of schema names is provided, the tap will only process the specified BigQuery schemas (datasets) and ignore others. If left blank, the tap automatically determines ALL available schemas.

Filter Tables

If an array of table names is provided, the tap will only process the specified BigQuery tables and ignore others. If left blank, the tap automatically determines ALL available tables. Shell patterns are supported.

Flattening Enabled

'True' to enable schema flattening and automatically expand nested properties.

Flattening Max Depth

The max depth to flatten schemas.

Project ID

GCP Project

Stream Map Config

User-defined config values to be used within map expressions.

Stream Maps

Config object for stream maps capability. For more information check out Stream Maps.

Meltano Cloud Connector

BigQuery connector is available on Meltano. It is built, maintained, supported, and tested by Meltano.

Why Meltano?
Expert supportDirect access to the team that built and maintains Meltano Cloud. Same-day responses during UK business hours. When something breaks, we fix it fast because we know exactly how it works.
Rigorously testedEvery connector goes through comprehensive testing and quality checks before production. Daily monitoring catches issues before they hit your pipelines. We don't just wrap open-source taps and hope for the best. We validate, we test, we maintain.
No maintenance overheadAPI changes. Connector updates. Schema drift. Breaking changes from upstream sources. We handle it all. Your team focuses on using data. Our team focuses on making sure it's there when you need it.
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