Heavy Interest in Databases

Heavy Interest in Databases

Judging by readership and views of recently posted articles and related webcasts about industrial databases, there is apparently a significant interest among manufacturers to leverage databases beyond standard operator interface interactions.

When I wrote the “Art and Science of Production Knowledge” feature last fall, it was merely an attempt to help better familiarize Automation World readers with the inner workings of the databases on which so much of their production KPIs and intelligence is based. Little did I know at the time that it would spur so much interest among readers to know even more about databases.

Even now, more than four months after the initial publication of the article I am receiving inquiries from readers wanting to know more about the subject. The most recent message came from a Spanish supplier of control systems and services wanting to know more about NoSQL databases (you can read my article on SQL/NoSQL databases here). The reader wanted to know some specific examples of NoSQL databases that he could investigate for his company’s potential use. Since there has been so much interest in the topic, I decided to share my response with everyone. Here’s a list of some of the top NoSQL databases currently available:

Cassandra was open sourced by Facebook and is a column oriented NoSQL database.

Dynamo was created by Amazon.com and is the most prominent Key-Value NoSQL database.

There are, of course, many others beyond these few cited here. These are merely the ones I have seen covered the most and some, such as MongoDB, Redis and Riak, have been predicted to be among the long-term NoSQL survivors.

If you too are interested in learning more about leveraging your databases for manufacturing optimization, I recommend checking out the webcast we created asking various database experts to explain how engineers can delve into their databases beyond the operator interface to learn more about accessing the data therein to extract specific types of relevant data. You can see that webcast here.

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