Amazon Web Services (AWS) announced the general availability of Amazon Timestream, a new time series database for IoT and operational applications 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.
Amazon Timestream saves customers effort and expense by keeping recent data in-memory and moving historical data to a cost-optimized storage tier based upon user-defined policies, while its query processing gives customers the ability to access and combine recent and historical data transparently across tiers with a single query, without needing to specify explicitly in the query whether the data resides in the in-memory or cost-optimized tier.
Amazon Timestream’s analytics features provide time series-specific functionality to help customers identify trends and patterns in data in near real time. Because Amazon Timestream is serverless, it automatically scales up or down to adjust capacity based on load, without customers needing to manage the underlying infrastructure.
There are no upfront costs or commitments required to use Amazon Timestream, and customers pay only for the data they write, store, or query.
Today’s customers want to build IoT, edge, and operational applications that collect, synthesize, and derive insights from enormous amounts of data that change over time (known as time series data). For example, manufacturers might want to track IoT sensor data that measure changes in equipment across a facility, online marketers might want to analyze clickstream data that capture how a user navigates a website over time, and data center operators might want to view data that measure changes in infrastructure performance metrics.
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