AWS Time-Series Database

This says it is an architecture better adapted for time series and related metadata.  Most of what we did in supply chain analysis used time series prediction.

AWS Launches Time-Series Database  by Alex Woodie in Datanami

And details in AWS.

AWS threw its hat into the nascent ring for time-series databases yesterday with the launch of AWS TimeStream, a managed time-series database that AWS says can handle trillions of events per day.

Time-series databases have emerged as a best-in-class approach for storing and analyzing huge amounts of data generated by users and IoT devices. While relational and NoSQL databases are sometimes used for time-stamped and time-series data – such as clickstream data from Web and mobile devices, log data from IT gear, and data generated by industrial machinery — today’s massive data volumes from the IoT have outstripped the capability of those databases to keep up.

As the high-end time-series use cases piled up, AWS decided it was time to take action and make its entry into the still-specialized field, much as it did with last year’s launch of Neptune, a graph database, which is another specialized database field that’s emerging.   ... "

AWS says its new Timestream database organizes data by time intervals, which reduces the amount of data that needs to be scanned to answer a query. It minimizes storage needs and costs by automatically applying rollups, retention, tiering, and compression of data. AWS is delivering the services (it’s still in a technical preview) as a serverless product, which means there’s no underlying server on AWS to manage.

Timestream features what AWS calls an “adaptive query processing engine,” which it says can adapt to different time scales, like milliseconds, microseconds, and nanoseconds. All told, AWS claims Timestream can deliver 1,000 faster query performance at one-tenth the cost of a relational database. ... "