Cloud Datastore is a highly available and durable fully managed NoSQL database service for serving data to your applications. This schema-less document database is geo-replicated and ideal for fast, flexible development of mobile and web applications. It automatically scales as your data and traffic grows—so you’ll never again worry about provisioning enough resources to handle your peak load. It already handles over 15 trillion queries per month.
The Cloud Datastore v1 API is now generally available for all customers, and the Cloud Datastore Service Level Agreement (SLA) now covers access both from App Engine and the v1 API and provides high confidence in the scalability and availability of the service for your toughest web and mobile workloads. Already, customers like Snapchat, Workiva, and Khan Academy have built amazing mobile and web applications with Cloud Datastore. Khan Academy, for instance, uses Datastore for user data — from user progress tracking to content management.
“It’s our primary database,” said Ben Kraft, Infrastructure Engineer at Khan Academy. “We depend on it being fast and reliable for everything we do.”
Now that the v1 API is generally available, we have deprecated the v1beta3 API with a twelve-month grace period before we decommission it fully on August 17th, 2017. Changes between v1beta 3 and v1 are minor, so transitioning to the new version is quick and straightforward.
The v1 API for Cloud Datastore allows you to access your database for Google Compute Engine, Google Container Engine, or any other server via our RESTful or gRPC endpoints. You can access your existing App Engine data now from different compute environments, enabling you to select the best mix for your needs.
You can use the v1 API via the idiomatic Google Cloud Client Libraries (in Node.js, Python, Java, Go, and Ruby), or alternatively via the low-level native client libraries for JSON and Protocol Buffers over gRPC. You can learn more about the various client libraries in our documentation.
Along with this cross-platform access, you can use Google Cloud Dataflow to execute a wide range of data processing patterns against Cloud Datastore, including batch and streaming computation. Take a look in the GitHub repository for examples of using the Dataflow SDK with Cloud Datastore.
New resourcesWe've also been busy making new resources available to enable you to make more effective use of Cloud Datastore.
- Best Practices: The down-low on the best practices on topics ranging from transactions to strongly consistent queries.
- Storage Size Calculations: A new transparent method of calculating the size of your database as announced as part of our simplified pricing.
- Limits: Information about production limits for Datastore, for example the maximum size of a transaction.
- Multitenancy: Guidance on how you can use namespaces for multitenancy in your application.
Cloud ConsoleLastly, we've made numerous improvements to our Cloud Console interface. If you haven't used it before, get to know it by reading a new article on editing entities in the console. Some highlights:
- App Engine Python users will be delighted to know that URL-Safe Keys are supported in the Key Filter field on the Entities page.
- The entity editor supports properties with complex types such as Array and Embedded entity.
To learn more about Cloud Datastore, check out our getting started guide.