I use a data historian (sometimes called time series database) for collecting and persisting large (billions) of rows of measurement data. The data being collected is off of a manufacturing equipment and represents sensors such as temperature, pressure…. I've been wondering if I should be researching some type of BigData replacement. The historian simply stores key=value types data, primarily made up of timestamp=value. At 3:00, temperature was 40, at 3:01, it was 40…. Lots of repetitive data, but historians are good at compression, but cost $$. I have to believe that commodity hardware is a lot less than year over year software maintenance. Has anyone used any of the Apache Hadoop products in this scenario?
Thanks
