Amazon Timestream turbocharges IoT database performance

Amazon Web Services (AWS) has announced "general availability" of Amazon Timestream, which is based on its new time-series database for IoT applications and "operational applications."

Among the first Amazon Timestream customers mentioned by AWS were Guardian Life, Autodesk and PubNub – each of which gave glowing feedback.

Region specific: Currently, Amazon Timestream isn't available in Seattle, where the tech giant is headquartered, or 46 other US states.  (Source: Amazon)
Region specific: Currently, Amazon Timestream isn't available in Seattle, where the tech giant is headquartered, or 46 other US states.
(Source: Amazon)

Despite claims of general availability, there are plenty more additional regions that AWS wants to roll out the revamped IoT database solution.

To get hold of Amazon Timestream today, US customers must be based in Virginia, Ohio, or Oregon. Ireland is the only other country mentioned by AWS where Amazon Timestream is available.

OK, show me what you can do
Amazon Timestream performance improvements, as detailed by AWS in a rather lengthy press release, look impressive.

When compared with relational databases, Amazon Timestream's approach can apparently scale to process trillions of time-series events per day and up to 1,000 times faster (and can be as low as one tenth the cost).

There are no upfront costs or commitments required to use Amazon Timestream, and customers pay only for the data they write, store or query.

Amazon Timestream analytics is pitched as helping customers identify data trends and patterns in "near real-time."

It also seems that Amazon Timestream is much easier to manage than those comparatively tardy relational databases.

One reason for that, says AWS, is the new solution spares 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."

Neither do customers have to bother about managing the underlying infrastructure, claims AWS. As it's a serverless solution, Amazon Timestream "automatically scales up or down to adjust capacity based on load."

AWS adds that the query processing gives customers the ability to "access and combine recent and historical data transparently across tiers with a single query."

Tooled up
Amazon Timestream integrates with a number of AWS' data collection, visualization and machine learning tools.

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These include AWS IoT Core (for IoT data collection), Amazon Kinesis and Amazon MSK (for streaming data), Amazon QuickSight (for serverless business Intelligence), and Amazon SageMaker (for building, training, and deploying machine learning models quickly).

Some open source, third-party tools are also in the integration mix, including Grafana (observability dashboards) and Telegraf (metrics collection).

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— Ken Wieland, contributing editor, special to Light Reading

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