Just because Google is no longer using something doesn't mean it's no longer useful for other companies. Most companies will never need to do the same level of

Just because Google is no longer using something doesn't mean it's no longer useful for other companies. Most companies will never need to do the same level of computation that Google needs to do. The fact is, Hadoop is becoming more and more easy to setup, with distributions like Cloudera & Hortonworks allowing users to set up clusters with minimal upfront knowledge of Hadoop and how it works. The article uses HBase and Hive together in the same sentence which is kind of weird, Hive and HBase are completely different. Hive was made by Facebook to allow users to map schemas to a large set of files so their employees could run MapReduce jobs without Java knowledge, but instead SQL (HSQL)...basically a way to bridge the gap between Hadoop and non-java / programmers. HBase is a different beast all together and has no relation to MapReduce...the only thing it has in common with Hadoop is that it uses HDFS as its underlying FS (but doesn't have to). It's a NoSQL database that is modeled after BigTable (K -> V) and is pretty complicated...more so than just Hadoop/MR. I think Hadoop will be around for quite a while, especially since it's becoming almost trivial to deploy. I see a lot of companies repurposing older servers into hadoop clusters and they are VERY happy with its performance. I rarely see where Hadoop is not providing enough to the user, but rather the user is not providing enough for Hadoop.