Andrew Brust for ZDNet:
Performing analytics on clickstream and log file data are canonical examples of Big Data in action; they represent a sweet spot for the technology. Hadoop is also a canonical example of Big Data in action and, more and more, Hadoop and Big Data are taken as synonymous. But from recent discussions with Web analytics stalwart Webtrends and log file analytics startup Loggly, I’ve come to learn that these core Big Data scenarios do not always mesh well with Big Data’s best known technology.
What are these shortcomings? The answer is already known by everyone that used or at least read something about Hadoop: Hadoop is not real-time. What a surprise!
Original title and link: Hadoop’s Shortcomings ( ©myNoSQL)