Exploring AWS Timestream for Time-Series Data Management
Amazon Timestream is a fast, scalable, serverless time series database service for IoT and operational applications.
Timestream makes it easy to store and analyze trillions of events per day up to 1,000 times faster and at as little as 1/10th the cost of relational databases. It saves you time and expense 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.
| Always Encrypted | Amazon Timestream ensures that your time series data is always encrypted at rest or in transit. Amazon Timestream also enables you to specify an AWS KMS customer-managed key (CMK) for encrypting data in the magnetic store. |
| High performance at a low cost | Amazon Timestream offers up to 1,000x faster query performance at as little as 1/10th the cost of relational databases. It provides high throughput ingestion, rapid point-in-time queries through its memory store, and fast analytical queries through its cost-optimized magnetic store. You pay only for the data you ingest, store, and query. |
| Simplified data access | With Amazon Timestream, you no longer need to use disparate tools to access recent and historical data. Amazon Timestream’s purpose-built query engine transparently accesses and combines data across storage tiers without you having to specify the data location. |
| Serverless with auto-scaling | Amazon Timestream is serverless – there are no servers to manage and no capacity to provision, so you can focus on building your applications. Amazon Timestream gives you the scale to process trillions of events and millions of queries per day. As your application needs change, it automatically scales to adjust capacity. |
| Purpose-built for time series | You can quickly analyze time-series data using SQL, with built-in time-series functions for smoothing, approximation, and interpolation. Amazon Timestream also supports advanced aggregates, window functions, and complex data types such as arrays and rows. |