As a document database service, Amazon DocumentDB meets customers where they are and accommodates their needs for a scalable, low-latency, fully-managed native JSON database.
Introduced in a DBTA webinar, “Exploring Amazon DocumentDB Elastic Clusters,” Vin Yu, senior technical product manager at AWS, highlighted DocumentDB’s new elastic clusters feature which allows users to quickly scale and support massive read and writes workloads, all while mitigating cost and alleviating menial administrative labor.
Yu presented an overview of Amazon DocumentDB, explaining the solution as a scalable, highly-durable, and fully-managed database service for operating mission-critical MongoDB API-based workloads. If users work with JSON data, require a flexible schema, indexing, ad hoc query capabilities, or have operational and analytical workloads, a document database is a strategically beneficial choice.
“If you’re looking for a fully-managed database service for your JSON documents and workloads, DocumentDB could be a good fit,” said Yu.
He then divided DocumentDB into three main points of advantage; fast and scalable, fully-managed, and MongoDB API compatible.
Amazon DocumentDB provides auto scaling storage and I/O for up to 64 TiB, allowing users to scale compute within mere minutes, out to 15 replicas for millions of reads. Clusters can span globally across multiple AWS regions with local read latency—particularly useful for globally-distributed enterprises or disaster recovery.
With built-in high availability, backups enabled by default, embedded durability and security, automatic patching, and monitoring and alerting functions, DocumentDB’s fully-managed architecture takes care of administrative tasks for the user, allowing them to focus on building applications rather than tedious maintenance.
Finally, DocumentDB’s MongoDB API compatibility enables users to leverage existing drivers, applications, and tools with DocumentDB, streamlining the onboarding process. Yu emphasized that Amazon works to meet the needs of its customers, delivering specific capabilities they need, when they need it.
Yu then introduced Amazon DocumentDB Elastic Clusters, a new feature that is analogous to multiple, separate filing cabinets for physical documents. These clusters partition out data into multiple instances, increasing the simplicity of its management.
“Elastic clusters are a new type of DocumentDB cluster that support millions of writes per second and petabytes of storage capacity,” explained Yu. “What we’ve done is we listen to our customers, and what they told us is that they need more scale as opposed to what’s available today in instance-based clusters. That motivated us to figure out how we can support that type of workload for our customers.”
Like DocumentDB’s architecture, elastic clusters are fast and scalable, with most queries completed in milliseconds. Unlike instance-based clusters, elastic clusters scale easily to millions of reads/writes per second with petabytes of storage. In as little as a few minutes, scaling operations can be completed.
Yu explained that elastic clusters are also fully-managed; built-in high-availability, automatic patching, snapshot backups, and embedded security remove the labor of administrative tasks from the workloads of its users.
The elastic clusters are MongoDB API compatible, like the database service itself, supporting applications, drivers, and tools to adapt to the skillset of the user.
To learn more about Amazon DocumentDB’s elastic clusters and to see a demo of the feature at work, you can view an archived version of the webinar here.