Google Cloud databases named a Leader in The Forrester Wave Database-as-a-Service, Q2 2019

Google Cloud databases named a Leader in The Forrester Wave Database-as-a-Service, Q2 2019

We’re pleased to announce that Google is a Leader in the Q2 2019 Forrester Database-as-a-Service Wave™, which we believe reflects the depth of our database technology and variety of options for enterprises. This Wave evaluated all of our managed database services: Cloud Spanner, Cloud Bigtable, Cloud Firestore, Cloud SQL, Cloud Memorystore, and BigQuery.  

Along with building flexible, compatible, and scalable databases, we recently extended our database offerings to many open source-centric partners to provide tightly integrated services across management, billing and support.

Forrester noted that “Google’s DBaaS offering has grown over the years, with large enterprises embracing various Google Cloud services…Enterprise customer references like the platform’s broad offerings to support large and complex applications, high performance, scale, ease of use, and automation.”

Choosing the right database for the job

To build a data platform that works for you and your company, it’s essential to have flexibility in the building blocks you choose. That’s true whether you’re migrating databases straight into the cloud, or re-architecting and modernizing your workloads. Database services from Google Cloud come in a range of options, roughly organized into those that offer compatibility and manageability and those that solve hard engineering problems—such as scalability, manageability, reliability, and flexibility—in unique ways. Here’s a look at Google Cloud’s database offerings.

Relational databases

NoSQL/non-relational databases

  • Cloud Firestore is a cloud-native serverless document database, designed to help store, sync, and query data for web, mobile, and IoT apps. Cloud Firestore customers choose it for scalability and easier app dev.
  • Cloud Memorystore is an in-memory data store service to build application caches with super-fast data access—especially useful if you’re migrating Redis-based workloads.

Data warehousing

BigQuery, our serverless data warehouse, is highly scalable with built-in machine learning. Here’s how one retail company uses BigQuery for fast analytics.

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