Time series data is a sequence of data points recorded over a time interval for measuring events that change over time, and Amazon Timestream is designed to store and analyze this type of data.
- It is a fast, scalable, and serverless time-series database service designed to store and analyze time-series data points per day.
- It simplifies data lifecycle management with storage tiers, including a memory store for recent data and a magnetic store for historical data.
- It is used for IoT applications, DevOps applications, and analytics applications.
- The Timestream rule action writes attributes from an MQTT message into an Amazon Timestream table, and there are tools and utilities available on GitHub to enable loading data and building applications with Amazon Timestream.
- It has built-in time series analytics functions, helping you identify trends and patterns in your data in near real-time.
Overall, Amazon Timestream is a powerful tool for storing and analyzing time-series data, with features like built-in analytics functions, serverless architecture, and storage tiers for efficient data lifecycle management.
Try Amazon Timestream free
50 GB of ingestion, 100 GB of magnetic tier storage, 750GB of memory tier storage, and 750 GB of data scanned for one month with the AWS Free Tier.
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