AWS recently announced the general availability of Amazon Timestream, a serverless purpose-built database that exposes time-series data through SQL. With Amazon Timestream, customers can save time and costs in managing the lifecycle of time series data by keeping recent data in memory and moving historical data to a cost-optimized storage tier based on user-defined policies.
Almost two years ago AWS introduced Amazon Timestream during re:Invent as a purpose-built time series database service for collecting, storing, and processing time-series data, such as server and network logs, sensor data, and industrial telemetry data for IoT and operational applications. The public cloud vendor built the service with fully-decoupled data ingestion and query processing systems, providing customers with infinite scale and the ability to grow storage and query processing independently and automatically - without requiring them to manage the underlying infrastructure. Furthermore, there are no upfront costs, and customers only pay for the data they write, store, or query.
Customers can use Amazon Timestream with the console, the AWS Command Line Interface (CLI), AWS SDKs, and AWS CloudFormation. Furthermore, customers can use the time-series database service, for instance, to quickly analyze time-series data generated by IoT applications by leveraging the built-in analytic functions such as smoothing, approximation, and interpolation. As an example, a smart home device manufacturer can use Amazon Timestream to collect motion or temperature data from the device sensors, interpolate to identify the time ranges without motion, and alert consumers to take actions such as turning down the heat to save energy.
Source: https://aws.amazon.com/timestream/
The public cloud vendor claims the time series database service makes it easy to collect, store, and process trillions of time series events per day, up to 1,000 times faster and at as little as to 1/10th the cost of a relational database – which is possible by keeping the recent data in memory and moving the historical data to a cost-optimized storage based on a retention policy defined by the customer.
As Danilo Poccia, chief evangelist (EMEA) at Amazon Web Services, explains in a blog post on the GA of Amazon Timestream:
All data is always automatically replicated across multiple availability zones (AZ) in the same AWS region. New data is written to the memory store, where data is replicated across three AZs before returning success of the operation. Data replication is quorum based such that the loss of nodes, or an entire AZ, does not disrupt durability or availability. In addition, data in the memory store is continuously backed up to Amazon Simple Storage Service (S3) as an extra precaution.
Also, the service integrates easily with other data collection, visualization, and machine learning tools such as 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 Prometheus and Telegraf (for metrics collection).
Holger Mueller, principal analyst and vice president at Constellation Research Inc., told InfoQ:
AWS continues with its specialty database strategy and it is now putting its TimeStream DB into GA. And there is a lot of out of the box automation that TimeStream offers, starting from self service provisioning over tiering of data. The latter is critical for processing large streams of data. And with that, AWS enables key next generation application use cases in logging, IOT, event-based processing and more.
Note that Amazon Timestream is not the only time-series database service offering available on AWS. There is also a third-party solution available called Timescale Cloud, present across 76 regions with AWS, Azure, and Google. Furthermore, a respondent on a Hacker News thread stated:
Unfortunately for Timestream, Timescale Cloud is 10x-70x cheaper to use than Timestream.
Currently, Amazon Timestream is available in US East (N. Virginia), Europe (Ireland), US West (Oregon), and US East (Ohio), and pricing details can be found on the pricing page. Furthermore, guidance and documentation are available on the Timestream landing page and samples in a GitHub repo.
