Another key benefit of ECL, Villanustre says, is that it's very much like high-level query languages such as SQL. If you're a Microsoft Excel maven, then, you should have no trouble picking up ECL.
Developing queries is further simplified by the work HPCC has done with analytics provider Pentaho and its open source Kettle project, which lets users create ECL queries in a drag and drop interface. This isn't possible with Hadoop's Pig or Hive query languages yet.
HPCC is also designed to answer real-world questions. Hadoop requires users to put together separate queries for each variable they seek; HPCC does not.
"ECL is a little bit like SQL...in that it is declarative, so you tell the computer what you want rather than how to do it," Villanustre says. Pig and Hive, on the other hand, are quite primitive. "They are hard to program, they are hard to maintain and they are hard to extend and reuse the code-which are the key elements for any computer language to be successful."
Hadoop's Advantages? It's Scalable, Flexible, Inexpensive
Charles Zedlewski, vice president of products at Cloudera, disagrees with this perspective. Cloudera, after all, is among the best-known and most successful Hadoop start-ups, providing turnkey Hadoop implementations to companies as diverse as eBay, Chevron and Nokia.
"In fact, today Hadoop probably has the ability to cater to a wider range of end users than the data management systems that have come before, and that has always been the strength of Hadoop," Zedlewski says. "The three things that Hadoop does really well is it's very scalable, it's very flexible and very inexpensive."
As well as being flexible and robust, it's this last point that has so many people interested in Hadoop. However, while Hadoop runs on commodity hardware, you either have to hire someone to put everything together or find a third-party provider such as Cloudera to do it for you. With HPCC, much of the functionality you need is available out of the box-and it runs on commodity boxes as well.