Читать книгу Official Google Cloud Certified Professional Data Engineer Study Guide - Dan Sullivan - Страница 33

Some storage services are designed to store large volumes of data, including petabyte scales, whereas others are limited to smaller volumes.

Cloud Storage is an example of the former. An individual item in Cloud Storage can be up to 5 TB, and there is no limit to the number of read or write operations. Cloud Bigtable, which is used for telemetry data and large-volume analytic applications, can store up to 8 TB per node when using hard disk drives, and it can store up to 2.5 TB per node when using SSDs. Each Bigtable instance can have up to 1,000 tables. BigQuery, the managed data warehouse and analytics database, has no limit on the number of tables in a dataset, and it may have up to 4,000 partitions per table. Persistent disks, which can be attached to Compute Engine instances, can store up to 64 TB.

Single MySQL First Generation instances are limited to storing 500 GB of data. Second Generation instances of MySQL, PostgreSQL, and SQL Server can store up to 30 TB per instance. In general, Cloud SQL is a good choice for applications that need a relational database and that serve requests in a single region.

The limits specified here are the limits that Google has in place as of this writing. They may have changed by the time you read this. Always use Google Cloud documentation for the definitive limits of any GCP service.