Traditional databases vs. the threat from in-memory, NoSQL

Traditional databases may not be able to keep up with the petabytes of data---soon to be exabytes---that we're storing and that's going to lead to the rise of in-memory databases as well as other hardware-assisted tools.

Traditional databases may not be able to keep up with the petabytes of data---soon to be exabytes---that we're storing and that's going to lead to the rise of in-memory databases as well as other hardware-assisted tools.

That's the gist of a presentation by Gartner analyst Donald Feinberg. This presentation was deemed a maverick idea since it may not quite pan out.

At a high-level view, here's the push and pull against (and possibly for) the traditional databases that made Oracle famous.

The problem: DataBase Management System (DBMS) architectures are antiquated, too slow and struggle with real-time data feeds. Among the bigger problems, Feinberg noted:

"Web-scale applications are a good example of the applications requiring more scalability than available today with DBMS models with market penetration. This has required many application developers to look elsewhere (e.g., caching and noSQL) for alternatives."

The need for real-time analysis is "leading to new in-memory DBMS and caching products to increase the speed in an attempt to reduce this latency."

And finally, mixed data types are killing the traditional database model.

Simply put, Feinberg likens DBMS as punch cards. Feinberg recommends that IT execs start examining in-memory databases, noSQL and other technologies.

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