Google Cloud has three relational database options:

• Cloud SQL: Managed MySQL, PostgreSQL and SQL Server databases on Google Cloud. It reduces maintenance costs and automates database provisioning, storage capacity management, backup, and out-of-the-box high availability and disaster recovery/failover. For these reasons, Cloud SQL is best suited for general purpose web frameworks, CRM, ERP, SaaS and e-commerce applications.
• Cloud Spanner: Cloud Spanner is a globally distributed and highly orchestrated enterprise-grade database with up to 99.999% availability, built specifically to combine the benefits of a relational database structure with non-relational horizontal scalability. It is a unique database that combines ACID transactions, SQL queries, and a relational structure with the scalability typically associated with non-relational 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 unlimited scalability with high stability and high availability.
• Bare Metal Solution: Provides hardware to run specialized, low-latency workloads on Google Cloud. This is especially useful if you have an Oracle database that you want to lift and move to Google Cloud. This makes it possible to exit the operation of data centers and opens the way to the modernization of outdated programs.

Non-relational databases

Non-relational databases (or NoSQL databases) store complex, unstructured data in non-tabular form, such as documents. Non-relational databases are often used when large amounts of complex and diverse data need to be organized, or when the data structure regularly evolves to meet new business requirements. Unlike relational databases, they are faster because they do not need to access multiple tables to get the answer to a query, making them ideal for storing data that may change frequently or for applications that process many different types of data.

For example, a clothing store might have a database where shirts have their own document containing all their information, including size, brand and color, with room to add other parameters later, such as sleeve size, collar, etc.

What makes NoSQL databases fast

• They are typically optimized for a specific workload pattern (eg key-value, graph, wide column)
• Horizontal scaling, usually using range or hashed distributions
• Final Consistency: Many NoSQL stores typically exhibit late consistency (e.g. lazy on reads). However, Firestore uniquely offers strong global consistency.
• Transactions: Most NoSQL stores do not support transactions between buckets or flexible isolation modes. However, Firestore uniquely offers ACID transactions between buckets with serializable isolation.

Due to these properties, non-relational databases are used in applications that require large scale, reliability, availability, and frequent data changes. They can easily scale horizontally by adding more servers, unlike some relational databases that scale vertically by increasing the size of the machine as the data grows. Although some relational databases such as Cloud Spanner support scalability and strict consistency.

У Google Cloud є три нереляційні бази даних:

• Firestore: It’s a serverless document database that scales on demand, is strictly consistent, offers up to 99.999% availability, and operates as a backend-as-a-service. DBaaS itself is optimized for building applications. It is ideal for all general purpose use cases such as e-commerce, gaming, IoT and real-time dashboards. Firestore enables users to interact and collaborate on data in real-time and offline, making it ideal for real-time and mobile applications.
• Cloud Bigtable: Cloud Bigtable is a table that can scale to billions of rows and thousands of columns, allowing you to store terabytes or even petabytes of data. It is ideal for storing very large amounts of data with a single key with very low latency. It supports high read and write throughput with sub-millisecond latency and is an ideal data source for MapReduce operations. It also supports the open source HBase API standard for easy integration with the Apache ecosystem, including HBase, Beam, Hadoop and Spark, as well as the Google ecosystem Cloud.
• Memorystore: Memorystore is an in-memory storage service for Redis and Memcached on Google Cloud. Best suited for in-memory and temporary data stores, it automates the complex tasks of provisioning, replication, failover, and patching so you can spend more time coding. Because it offers ultra-low latency and high performance, Memorystore is great for web and mobile applications, games, leaderboards, social media, chat and news applications.

BlaBlaCar uses Google Cloud

“We were looking to enter two highly competitive markets while reaching into a third market that we felt had great potential. We realized that moving to Google Cloud would help to make this expansion possible, allowing us to test markets and products at scale, efficiently, and with minimal investment.”

—Olivier Bonnet, Chief Technology Officer, BlaBlaCar