An on-premise relational database can be a powerful, reliable, and secure solution. But it can also be complex—particularly since traditional databases weren’t designed for global scalability. If you’re aiming to transition to a solution that offers reliability and scalability, a cloud-based solution can offer the best of both worlds.
Google Cloud offers fully managed database services that help you set up, maintain, manage, and administer relational cloud databases—along with non-relational and self-managed options. That means you can operate the same databases you’re familiar with, while still benefiting from the larger ecosystem of Google Cloud services, Google partners, and the open-source community.
As an added benefit, you can combine database services from Google Cloud with other cloud providers, so you’re not locked into a single-vendor environment. But choosing the right database service for your specific operational needs and business goals can be challenging.
To help, here’s a Google Cloud “cheat sheet” to guide your decision-making.
Self-hosted databases
If you want full control of your database environment, consider a self-hosted database, which runs on your own servers (either on-premise or in a co-location facility). A self-hosted database could be the right choice for those who want control and ownership over their performance and security. Here are some options:
Compute Engine is a customizable compute service from Google that allows you to create and run virtual machines (VMs) on Google infrastructure. It includes pre-built configurations and custom machine types, so you can get started quickly while balancing costs.
Google Cloud VMware Engine (GCVE) allows you to lift and shift VM workloads and VMware-based applications from the data center to Google Cloud (or from one cloud to another). You can do this without having to make changes to your apps, tools, or processes—or your VMware licensing.
Bare Metal Solution allows you to provision infrastructure using Oracle-certified hardware co-located in Google Cloud data centers. Google provides the core infrastructure, network, security, and hardware monitoring capabilities, so you can optimize resource usage and enhance database performance.
Google-managed databases
Google’s relational cloud databases
Relational cloud databases have a fixed schema, so they’re ideal for applications that require a large number of transactions, such as enterprise resource planning (ERP), customer relationship management (CRM), and ecommerce/web applications. In the Google ecosystem, key database services include Cloud SQL, Cloud Spanner, and AlloyDB for PostgreSQL.
Cloud SQL: This fully managed relational Google Cloud database service is compatible with PostgreSQL, MySQL, and SQL Server. Thanks to a common API and control plane across database engines, it’s well-equipped for lifting and shifting on-premise SQL databases to the cloud. It can also be integrated with BigQuery, Kubernetes, and Compute Engine.
Cloud SQL for PostgreSQL: This option allows you to migrate to a compatible platform while keeping your core application code and offloading analytics-centric workloads to SQL-compatible data warehousing solutions like BigQuery. A managed PostgreSQL database could be an option if you’re deploying PostgreSQL workloads after migrating from Oracle.
Cloud Spanner: If you need a relational database with global reach and scalability, then migrating to the cloud will require a rewrite. Cloud Spanner is a fully managed, enterprise-grade, globally distributed database service that combines a relational database structure with non-relational horizontal scaling, making it ideal for use cases such as order and inventory management, financial trading and payment solutions, and retail banking.
AlloyDB for PostgreSQL: As a fully managed PostgreSQL-compatible database, AlloyDB can scale vertically and horizontally, so it’s ideal for enterprise workloads that require high transaction throughputs, large data sizes, or multiple read replicas. Thanks to built-in integration with Vertex AI, Google’s AI platform—and its ability to run vector queries up to 10 times faster than standard PostgreSQL—it can be used to build a range of generative AI applications.
AlloyDB Omni: This downloadable edition of AlloyDB is designed to run on almost any platform—in a private data center, in any cloud, at the edge, and even on developer laptops. It’s available at a fraction of the cost of legacy databases, with a free developer edition; however, it’s self-managed, so it has different use cases—such as modernizing in place as a first step to cloud or on-the-edge applications.
Other cloud database options
For some use cases, a non-relational or NoSQL database may be the better option, since they provide a more flexible schema than a relational database. Most can scale horizontally to petabytes of data. In the Google ecosystem, key database services include Cloud Firestore, Cloud BigTable and Memorystore.
Firestore: This fully managed, highly scalable, serverless NoSQL Google Cloud database service aggregates data from multiple sources—including web, mobile, and IoT—and automatically partitions data as it grows. A key benefit is its ability for application development with built-in cross-client sync, such as IoT applications and real-time analytics.
Cloud Bigtable: This fully managed NoSQL Google Cloud database service isn’t serverless. But with extremely high throughput and millisecond latencies, it can handle massive volumes of analytical and operational data, making it ideal for use cases such as financial analyses, IoT analytics, fraud detection, personalized marketing, and recommendation engines.
Memorystore: This fully managed in-memory Google Cloud data store—compatible with Memcached and Redis protocols—provides sub-millisecond latency. Since in-memory databases retrieve data from memory, they’re incredibly fast when compared to traditional databases that use disk operations, though you’re at high risk of losing that data if there’s a server failure. This option is best for transient data stores such as session stores, leaderboards, and news feeds.
Why consider a partner for database migrations?
Choosing a cloud-based database service is not an easy decision. Whether you’re migrating from an on-premise environment or from cloud to cloud, these migrations can be highly complex, and you’ll want to minimize downtime and avoid disruptions to your business.
That’s where working with a Google Cloud partner like Pythian can help. Our data management services for Google Cloud can help you assess your database environment and find the right migration strategy for your business needs—for the fastest time to value. Find out more in our Any Database to Google Cloud eBook or get in touch with a Pythian Google Cloud expert to see how our team can help.
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