Realtime analytics drives a migration away from databases to more scalable parallel dataflow architectures.
Bill McColl, 29 October 2009
Over the past year or so, a new movement, the “NoSQL” movement has emerged promoting the advantages of doing a variety of kinds of analytics without using any relational database technologies at all.
Whatever one thinks of the capabilities and limitations of distributed key-value stores relative to relational databases, one thing is clear – the stranglehold that SQL has held over all aspects of data analytics since 1990 is now coming to an end. Other non-SQL approaches to analytics such as MapReduce/Hadoop, a very simple dataflow architecture for batch computing, are now gaining ground. As the need for realtime analytics grows we will continue to see a migration away from databases and towards more scalable parallel dataflow architectures for analytics.
Phi Beta Iota: We accept “Real-Time Analytics” as an appropriate term and in lieu of the improper use of “Real-Time Intelligence.” As the Information Communications Technologies (ICT) industry matures, machine-speed anf “real-time” analytics will be mandatory for both the sciences and the humanities. See these other related Journal entries: