Picking the right database for your application is not easy. The choice depends on the use case: transactional processing, analytical processing, in-memory database, and so forth.

We have three different relational database options:

Cloud SQL: Provides managed MySQL, PostgreSQL, and SQL Server databases on Google Cloud. It reduces maintenance cost and automates database provisioning, storage capacity management, backups, and out-of-the-box high availability and disaster recovery/failover. For these reasons, it is best for general-purpose web frameworks, CRM, ERP, SaaS, and e-commerce applications.

Cloud Spanner: Cloud Spanner is an enterprise-grade, globally distributed, and strongly consistent database that offers up to 99.999% availability, built specifically to combine the benefits of relational database structure with nonrelational horizontal scale. It is a unique database that combines ACID transactions, SQL queries, and relational structure with the scalability that you typically associate with nonrelational or NoSQL databases. As a result, Spanner is best used for applications such as gaming, payment solutions, global financial ledgers, retail banking, and inventory management that require the ability to scale limitlessly with strong consistency and high availability.

Bare Metal Solution: Provides hardware to run specialized workloads with low latency on Google Cloud. This is specifically useful if there is an Oracle database that you want to lift and shift into Google Cloud. This enables data center retirements and paves a path to modernize legacy applications.

We have three nonrelational databases in Google Cloud:

Firestore: Firestore is a serverless document database that scales on demand, is strongly consistent, supports ACID transactions, offers up to 99.999% availability, and acts as a backend-as-a-service. It is a DBaaS that is optimized for building applications. It is perfect for all general-purpose use cases such as e-commerce, gaming, IoT, and real-time dashboards. With Firestore, users can interact with and collaborate on live and offline data, making it great for real-time application and mobile apps.

Cloud Bigtable: Cloud Bigtable is a sparsely populated table that can scale to billions of rows and thousands of columns, enabling you to store terabytes or even petabytes of data. It is ideal for storing large amounts of single-keyed data with very low latency. It supports high read and write throughput at single-digit-millisecond latency, and it is an ideal data source for MapReduce operations. It also supports the open source HBase API standard, so it easily integrates with the Apache ecosystem, including HBase, Beam, Hadoop, and Spark, along with Google Cloud ecosystem.

Memorystore: Memorystore is a fully managed in-memory data store service for Redis and Memcached at Google Cloud. It is best for in-memory and transient data stores and automates the complex tasks of provisioning, replication, failover, and patching so that you can spend more time coding. Because it offers extremely low latency and high performance, Memorystore is great for web and mobile, gaming, leaderboard, social, chat, and newsfeed applications.