Introduction to datasets

This page provides an overview of datasets in BigQuery.

Datasets

A dataset is contained within a specific project. Datasets are top-level containers that are used to organize and control access to your tables and views. A table or view must belong to a dataset, so you need to create at least one dataset before loading data into BigQuery. Use the format projectname.datasetname to fully qualify a dataset name when using GoogleSQL, or the format projectname:datasetname to fully qualify a dataset name when using the bq command-line tool.

Location

You specify a location for storing your BigQuery data when you create a dataset. For a list of BigQuery dataset locations, see BigQuery locations. After you create the dataset, the location cannot be changed, but you can copy datasets to different locations, or manually move (recreate) the dataset in a different location.

BigQuery processes queries in the same location as the dataset that contains the tables you're querying. BigQuery stores your data in the selected location in accordance with the Service Specific Terms.

Data retention

Datasets use time travel in conjunction with the fail-safe period to retain deleted and modified data for a short time, in case you need to recover it. For more information, see Data retention with time travel and fail-safe.

Storage billing models

You can be billed for BigQuery data storage in either logical or physical (compressed) bytes, or a combination of both. The storage billing model you choose determines your storage pricing. The storage billing model you choose doesn't impact BigQuery performance. Whichever billing model you choose, your data is stored as physical bytes.

You set the storage billing model at the dataset level. If you don't specify a storage billing model when you create a dataset, it defaults to using logical storage billing. However, you can change a dataset's storage billing model after you create it. If you change a dataset's storage billing model, you must wait 14 days before you can change the storage billing model again.

When you change a dataset's billing model, it takes 24 hours for the change to take effect. Any tables or table partitions in long-term storage are not reset to active storage when you change a dataset's billing model. Query performance and query latency are not affected by changing a dataset's billing model.

Datasets use time travel and fail-safe storage for data retention. Time travel and fail-safe storage are charged separately at active storage rates when you use physical storage billing, but are included in the base rate you are charged when you use logical storage billing. You can modify the time travel window you use for a dataset in order to balance physical storage costs with data retention. You can't modify the fail-safe window. For more information about dataset data retention, see Data retention with time travel and fail-safe. For more information on forecasting your storage costs, see Forecast storage billing.

You can't enroll a dataset in physical storage billing if you have any existing legacy flat-rate slot commitments located in the same region as the dataset. This doesn't apply to commitments purchased with a BigQuery edition.

Limitations

BigQuery datasets are subject to the following limitations:

  • The dataset location can only be set at creation time. After a dataset is created, its location cannot be changed.

  • All tables that are referenced in a query must be stored in datasets in the same location.

  • When you copy a table, the datasets that contain the source table and destination table must reside in the same location.

  • Dataset names must be unique for each project.

  • If you change a dataset's storage billing model, you must wait 14 days before you can change the storage billing model again.

  • You can't enroll a dataset in physical storage billing if you have any existing legacy flat-rate slot commitments located in the same region as the dataset.

Quotas

For more information on dataset quotas and limits, see Quotas and limits.

Pricing

You are not charged for creating, updating, or deleting a dataset.

For more information on BigQuery pricing, see Pricing.

Security

To control access to datasets in BigQuery, see Controlling access to datasets. For information about data encryption, see Encryption at rest.

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