Google has announced several new products and features for the database services on Google Cloud Platform. These announcements include Cloud SQL for Microsoft SQL Server, version 11 support for Cloud SQL for PostgreSQL and multi-region replication for Cloud Bigtable.
As Google's managed database service, Cloud SQL abstracts away various maintenance tasks like patching, backups, and replication while promising 99.95% availability. As such, Cloud SQL is similar to competitor's services like Azure SQL Database and Amazon Relational Database Service. Previously, Cloud SQL offered support for MySQL and PostgreSQL, and now extends this with support for Microsoft SQL as well. The addition of Microsoft SQL means that customers who want to run MS SQL on GCP no longer need to run this on virtual machines, but can instead use the new fully managed option. This, according to Stephanie Condon, Staff Writer at ZDNet, provides many innovative opportunities.
Because it's fully managed, customers using Cloud SQL for Microsoft SQL Server won't have to worry about VM operations or tasks like backups, replication, patches and updates. They'll be able to lift and shift existing SQL Server workloads to GCP, without changing apps, and take advantage of GCP services like BigQuery for analytics.
Already part of Cloud SQL for a year now, Google has now updated their PostgreSQL offer with version 11 support, the latest version of the database system. Consequently, this offers several enhancements and new features, including better partitioning, support for transactions in stored procedures, just in time compilation in expressions, and enhanced query parallelism capabilities.
Cloud Bigtable is Google's fully managed NoSQL service, which was designed to handle petabyte-sized workloads. In relation to this, the multi-region replication capabilities for Cloud Bigtable are now generally available, allowing operators to make data available over regions, or even worldwide, similar to the global distribution offering in Azure Cosmos DB. According to Dominic Preuss, Director of Product Management, and Tobias Ternstrom, Product Management Lead, multi-region replication opens a variety of new opportunities.
- Serve global audiences with lower latency by bringing data that's generated in any region, such as personalized recommendations, closer to the users wherever they are
- Aggregate data ingested from worldwide sources (such as IoT sensor data) to a single location for analytics and machine learning
- Increase the availability and durability of your data beyond the scope of a single region
- Isolate batch and serving workloads
Furthermore, replication in Cloud Bigtable supports up to four replicated instances, allowing read and write actions to take place on each of these. Even though the feature by default uses an eventual consistent model, it is also possible to reconfigure this to use a read-your-writes or strong consistency model instead.