Amazon Web Services (AWS) is releasing Amazon Timestream, a new time series database for IoT and operational applications that can scale to process trillions of time series events per day.
According to AWS, Amazon Timestream saves customers effort and expense by keeping recent data in-memory and moving historical data to a cost-optimized storage tier based upon user-defined policies, while its query processing gives customers the ability to access and combine recent and historical data transparently across tiers with a single query, without needing to specify explicitly in the query whether the data resides in the in-memory or cost-optimized tier.
Amazon Timestream’s analytics features provide time series-specific functionality to help customers identify trends and patterns in data in near real time.
Because Amazon Timestream is serverless, it automatically scales up or down to adjust capacity based on load, without customers needing to manage the underlying infrastructure.
There are no upfront costs or commitments required to use Amazon Timestream, and customers pay only for the data they write, store, or query.
Amazon Timestream gives customers a purpose-built, serverless time series database for collecting, storing, and processing time series data.
Amazon Timestream automatically detects the attributes of the data, so customers no longer need to predefine a schema.
Amazon Timestream simplifies the complex process of data lifecycle management with automated storage tiering that stores recent data in memory and automatically moves historical data to a cost-optimized storage tier based on predefined user policies.
Amazon Timestream also uses a purpose-built adaptive query engine to transparently access and combine recent and historical data across tiers with a single SQL statement, without having to specify which storage tier houses the data.
This enables customers to query all of their data using a single query without requiring them to write complicated application logic that looks up where their data is stored, queries each tier independently, and then combines the results into a complete view.
Amazon Timestream provides built-in time series analytics, with functions for smoothing, approximation, and interpolation, so customers don’t have to extract raw data from their databases and then perform their time series analytics with external tools and libraries or write complex stored procedures that not all databases support.
Amazon Timestream’s serverless architecture is built with fully decoupled data ingestion and query processing systems, giving customers virtually infinite scale and the ability to grow storage and query processing independently and automatically, without requiring customers to manage the underlying infrastructure.
In addition, Amazon Timestream integrates with popular data collection, visualization, and machine learning tools that customers use today, including services like AWS IoT Core (for IoT data collection), Amazon Kinesis and Amazon MSK (for streaming data), Amazon QuickSight (for serverless Business Intelligence), and Amazon SageMaker (for building, training, and deploying machine learning models quickly), as well as open source, third-party tools like Grafana (for observability dashboards) and Telegraf (for metrics collection).
“What we hear from customers is that they have a lot of insightful data buried in their industrial equipment, website clickstream logs, data center infrastructure, and many other places, but managing time series data at scale is too complex, expensive, and slow,” said Shawn Bice, VP, databases, AWS. “Solving this problem required us to build something entirely new. Amazon Timestream provides a serverless database service that is purpose-built to manage the scale and complexity of time series data in the cloud, so customers can store more data more easily and cost effectively, giving them the ability to derive additional insights and drive better business decisions from their IoT and operational monitoring applications.”
For more information about this release, visit https://aws.amazon.com/timestream/.