Posted On: Nov 29, 2021
Amazon Timestream has added three new capabilities, namely, scheduled queries, multi-measure records, and magnetic storage writes, to make time series data processing faster, cost-effective, and therefore more accessible to many more customers. These features enable customers to write, store, and access their time series data more economically and efficiently, so they can continue to derive insights from their data and drive better data-driven business decisions.
Starting today, customers can use Amazon Timestream’s Scheduled Queries for faster and more affordable time series data processing. With scheduled queries, customers simply define the queries for computing aggregates, rollups, and other real-time analytics on their data; along with the frequency at which the query must be run. Then, Amazon Timestream periodically and automatically runs the scheduled queries and reliably writes the query results into a configurable destination table, within a few minutes. Customers can then point their dashboards and reports to simply query the destination table, instead of querying the considerably larger source tables. This leads to performance and cost gains that can exceed an order of magnitude or more. This is because destination tables contain much less data than the source tables. Given destination tables contain much less data than source tables, customers can store data in the destination tables for a much longer duration at a fraction of the data storage cost of the source table. They can also choose to reduce the data retention period of their source tables and further optimize their spend.
With this release, Amazon Timestream also supports multi-measure records, a new data modeling capability that enables faster data writes, efficient data storage, performant data access, and ease of use. Multi-measure records enable customers to store multiple time series measures in a single table row, instead of storing one measure per row. This optimized data layout reduces the volume of data stored in a table, which helps customers lower their data storage spend, improve query performance, and minimize the cost of analytical queries. Multi-measure records also make it easy for customers to migrate time series data and queries from existing relational databases to Amazon Timestream with minimal changes.
From today, Amazon Timestream also allows customers to write their late arrival data into the magnetic store, so they can further optimize their data storage spend. Late arrival data is data with a timestamp that is in the past. Customers can now use Amazon Timestream’s existing write APIs to send late arrival data to the magnetic store by simply enabling a property on their tables. With magnetic storage writes, customers no longer have to maintain a memory store with a large data retention period for the purpose of processing late arrival data. Customers can now set their memory store data retention period to match the high throughput data ingestion and fast point-in-time query requirements of their applications. They can use the magnetic store for asynchronous processing of late arrival data, long-term data storage, and for fast analytical queries.
Scheduled Queries, multi-measure records, and magnetic storage writes are now available as part of Amazon Timestream’s APIs and the AWS Management Console for Amazon Timestream. Amazon Timestream is a fast, scalable, secure, and purpose-built time series database for Application Monitoring, edge and IoT workloads that can scale to process trillions of time series events per day up to 1,000 times faster than relational databases, and at as low as 1/10th the cost. The service is also HIPAA eligible, ISO certified, PCI DSS compliant, and in scope for AWS’s SOC reports SOC 1, SOC 2, and SOC 3. Amazon Timestream is currently available in US East (N. Virginia), US East (Ohio), US West (Oregon), Europe (Ireland), and Europe (Frankfurt). To get started, visit our product page.