A few years ago I wrote an article about "When Big Data is a Big Con" which talked about some of the hype issues around Big Data. One of the key points I raised was about how many folks were just slapping on Big Data badges to the same old same old, another was that Map Reduce really doesn't work they way traditional IT estates behave which was a significant barrier to entry for Hadoop as a new technology. Mark Little took this idea and ran with it on InfoQ about Big Data Evolution or Revolution? Well at the Hadoop Summit in Amsterdam this week the message was clear...
Hadoop has the opportunity to become the 'JVM of Big Data' but with a philosophy that the language you use on that Big Data Virtual Machine is down to your requirements and most critically down to what people in your enterprise want to use.
Its great to see a good idea grow by taking a practical approach rather than sticking to flawed dogma. Brilliant work from the Hadoop community I salute you!
SQL is back, SQL is key, SQL is in fact the King of HadoopPart of me is disappointed in this. I've never really liked SQL and quite liked the LISPiness of Map Reduce but the reason behind this is simple.
When it comes to technology adoption its people that are key, and large scale adoption means small scale changeThink about Java. A C language (70s concept) derivative running on a virtual machine (60s) using some OO principles (60s) with a kickass set of libraries (90s). It exploded because it wasn't a big leap and I think we can now see the same sort of thing with Hadoop now that its stopped with purity and gone for the mainstream. Sure there will be some NoSQL pieces out there and Map Reduce has its uses but its this change towards using SQL that will really cause Hadoop usage to explode.What is good however is that the Hadoop philosophy remains in-tact, this isn't the Java SE 6 debacle where aiming after 'Joe Six-pack' developer resulted in a bag of mess. This instead is about retaining that philosophy of cheap infrastructure and massive scale processing but adding a more enterprise friendly view (not developer friendly, enterprise friendly) and its that focus which matters.
Hadoop has the opportunity to become the 'JVM of Big Data' but with a philosophy that the language you use on that Big Data Virtual Machine is down to your requirements and most critically down to what people in your enterprise want to use.
Its great to see a good idea grow by taking a practical approach rather than sticking to flawed dogma. Brilliant work from the Hadoop community I salute you!
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