Amazon Timestream for IoT use cases

For IoT use cases, where there are millions of events to be processed in realtime and data feeds come from multiple IoT enabled devices and other sources, it is challenging for an architect to choose a database that can handle the throughput at par. RDBMS or NoSQL databases are difficult to manage in such cases, as they may not perform well or be too costly.

To address this, AWS has developed Timestream, which is a fast, scalable, serverless time series database that performs 1000 times faster than an RDBMS and costs one-tenth of the traditional database platforms. Timestream can store and analyse millions and trillions of events in real-time from IoT sources and can be integrated with SageMaker or QuickSight for analytics, visualisation or processing time series data.

Timestream is serverless and scalable, with an auto-scaling facility to ensure high availability with low cost and optimal resource usage. It can help manage the entire data life cycle. Timestream has a memory store for faster processing of the latest data and magnetic store for low-called historical data. Timestream provides encryption at rest and at motion, and allows key management service (KMS) based customer managed key (CMK) to encrypt historical data (in magnetic stores).

A built-in time series function enables quick analysis of time series data using SQL queries or to interpolate, aggregate and derive metrics in real-time. The data in memory operation is backed up automatically in s3 bucket for safety.