Not sure what this is about. Most of his criticism can be made against any form of computing clusters. Hadoop is optimized for processing raw unstructered data

Not sure what this is about. Most of his criticism can be made against any form of computing clusters. Hadoop is optimized for processing raw unstructered data fast. It's not an alternative to SQL and never was. It's also optimized for data throughput and not like MPI for processing power. MapReduce is an algorithm or paradigm that has to fit your problem. It is not the fault of Hadoop that it is over hyped and mis-used for other problems. Hadoop is not a database or a datastore. If you want to extract data out of e.g. web-pages Hadoop is a great tool as it abstracts away the problems of distributing the algorithm and the data for you. Google (re)invented MapReduce and is a search engine, Yahoo was also a search engine. Hadoop solved Yahoo's problems. I really don't understand the point he's trying to make. If you want to run your business database from Hadoop you are crazy. If you have 5 terabyte of click data from your website and you want to cluster and analyze this data Hadoop (or better Hbase) can help you to solve this problem. It is a different paradigm. It it not like Java programming. It uses Java to implement the MapReduce paradigm. If you don't want to think about how to fit your problem into this paradigm or if your problem is not solvable using Hadoop don't use it. If you want to build a search engine Hadoop is a great fit. If you want to replace your SQL database with Hadoop you are crazy. Also if the network is the bottleneck in your Hadoop cluster you did something wrong. Hadoop is designed for data locality. Usally the output of a Mapper consists of less data than the input. * I've used Hadoop as a student for several academic projects. Mostly information retrieval. So I can't comment on "real world buisseness" usage. I've just have the impression that Hadoop is pretty overhyped and not well understood.