Amazon Timestream is a fully managed, serverless, and purpose-built time series database service offered by AWS. It is designed to handle trillions of time-stamped data points per day with minimal operational overhead. Time series databases are particularly well-suited for workloads such as IoT data, application monitoring, DevOps, and industrial telemetry, where data arrives in a sequential, time-stamped format.
Purpose-Built for Time Series Data:
Optimized for time series workloads, enabling efficient ingestion, storage, and querying of sequential data with time stamps.
Serverless Architecture:
Fully managed and serverless, meaning there is no need to manage servers, provision storage, or perform scaling. It automatically scales based on workload.
Data Lifecycle Management:
Allows you to specify data retention policies:
Memory Store for fast query access (e.g., recent data for analytics).
Magnetic Store for cost-effective storage of older, less frequently accessed data.
Built-in Analytics:
Provides SQL-like queries to analyze and process data in place, without the need for additional tools.
Supports advanced time-series analytics, such as smoothing, interpolation, and aggregations over time.
Seamless Integration:
Easily integrates with AWS services such as AWS IoT Core, Amazon Kinesis, AWS Lambda, Amazon QuickSight, and more.
High Performance:
Offers low-latency data writes and high-throughput reads, designed for applications that require near-real-time insights.
Scalable:
Dynamically scales to handle data volume changes without manual intervention.
Data Security:
Supports encryption at rest and in transit, ensuring that sensitive time series data is protected.
Integrates with AWS Identity and Access Management (IAM) for fine-grained access control.