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Hadoop Adoption Accelerates, But Not For Data Analytics – ReadWrite

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First you use it as a digital landfill

Then you figure out how to process the data

Then you can do work like analytics or apps

26% of Hadoop proponents cite how long it takes to deploy as a reason stunting Hadoop adoption:

Is Hadoop really better for ETL than a SQL database? Really?

I guess a couple of things.  For ETL, it depends on the data.  How long do you want to keep it, how structured is it, how dynamic of a mapping do you want to correlate against, how often do the mappings change?

Also, you use each of the major approaches for datastores for what they're really good at. At Bitvore, we have a hybrid system.  We deal with dynamic, unstructured data that's difficult to put in a box and correlate.  We use a nosql hbase and hadoop for dynamic strucutring and dynamic tagging, sql/mysql for reporting and user management, and graph-based datastore for reasoning and foksonomy/taxonomy crawling.   

So IMHO, yes, it's really better--for some things. 

So it's not an either/or. It's a both!

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