Aster Data has built a business out of map/reduce, and the release today of a thousand new SQL query building blocks—what it calls “functions”—is designed to give business users access to map/reduce computed analytics.
Whereas open-source big data solution Hadoop, for instance, is based entirely on its own implementation of map/reduce, as well as a set of homegrown query structuring frameworks like Pig and Hive, Aster Data wants to use SQL right from the start. Sharmila Shahani-Mulligan, executive vice president of marketing at Aster Data, said that this is a significant advantage over Hadoop.
“Hadoop lends itself more to batch-type processing. Most of our customers are running analytics on a daily basis with the expectation of results returned every few minutes,” she said. “It’s not real-time, but it’s near real-time.
“The second advantage is SQL map/reduce. We are literally targeting the business analyst with SQL using full map/reduce underneath.”
Map/reduce is the framework for processing huge amounts of data, and it is the basis of the Apache Hadoop project, as well as of Big Table, which runs Google’s search engine. Using map/reduce, huge stores of data can be processed, and the results can be combined into a cohesive set of information.
Stephanie McReynolds, director of product marketing at Aster Data, said the new sets of query-building tools aren’t limited to business users. “We introduced many new business analyst-ready functions,” she said. “[These] functions address particular business issues, like path analysis for website traffic.
“We also have a series of packages for power users. These are for people building their own SQL map/reduce applications. They want to use Java or C functions to get ahead. These are smaller building blocks.”
Shahani-Mulligan said that Aster Data’s analytics can be tweaked and queried by business users, a major advantage over Hadoop. She said that many business users already know SQL, which cannot be said of Hive or Pig. She said that with Hadoop, developers likely need to be called in to implement any analytics batches that need to be run, but with Aster Data, the business users can do that themselves.
“With almost any of our [customers] you talk to, one of the big appeals has been that their existing business analysts can work with functions and don’t have to use a new language,” said Shahani-Mulligan. “This is why we came out with SQL map/reduce. Some of them also have Hadoop, but it requires you to do constant programming in map/reduce versus having a simple-to-use interface.”
