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Structural differences and limitations with Google BigQuery

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Required license: Professional or Enterprise

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No hidden datasets as source or destination

Google BigQuery workspaces cannot have a as its source or destination dataset.

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Post-job scripts run in transactions

Post-job scripts run inside of transactions. They are limited to .

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Table mode limitations

Google BigQuery workspaces cannot use the following table modes:

  • Incremental

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Generator limitations

Google BigQuery workspaces cannot use the following generators:

  • Cross Table Sum

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Cannot process STRUCT or INTERVAL types

Tonic Structural cannot process STRUCT or INTERVAL types in Google BigQuery.

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External, snapshot, and cloned table handling

In the destination database, Structural creates external, snapshot, and cloned tables as normal tables.

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Cannot assign generators when partition filters required

You cannot assign generators to partitioned tables that require a partition filter.

The TONIC_GRPC_ENABLED indicates whether to use GRPC-based endpoints to access Google BigQuery.

If TONIC_GRPC_ENABLED is true, then you can leave all of the columns set to Passthrough.

If TONIC_GRPC_ENABLED is false, then you must truncate the tables.

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No subsetting, but support for table filtering

Google BigQuery workspaces do not support subsetting.

However, for tables that use the De-Identify table mode, you can provide a WHERE clause to filter the table. For details, go to .

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No upsert

Google BigQuery workspaces do not support upsert.

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No output to a container repository

For Google BigQuery workspaces, you cannot write the destination data to a container repository.

hidden datasetarrow-up-right
statements that are supported within transactionsarrow-up-right
environment setting
Using table filtering for data warehouses and Spark-based data connectors