While the existing solutions so far relied on complex MapReduce batch jobs to process data stored within Hadoop Distributed File System (HDFS), Aster SQL-H creates a higher-level of abstraction by allowing ANSI standard SQL queries against Hadoop data. It leverages the power and flexibility of Aster SQL and SQL-MapReduce to provide business analysts with a low latency, interactive data discovery environment through their existing BI tools and SQL-MapReduce functions.
So far there was a bit of an impossibility due to short supply of combination of technical and analytical skills required to process big data within an enterprise. Such an integration that can process a combination of data stored both within Apache Hadoop and Aster Data platform along with traditional Business Intelligence software can prove game changing for enterprises.
SQL-H interfaces with the Apache HCatalog project to access data within apache Hadoop from Aster Platform. This Aster-managed communication with Hadoop nodes, to intelligently read just the data needed from Hadoop for SQL queries and SQL-MapReduce functions in Aster is the key part of this announcement. The company has given due credits to Hortonworks which was the major contributor for HCatalog project.
“Aster SQL-H provides value on two levels. This is the first time in the industry that standard query language or SQL access can be transparently and seamlessly provided for Hadoop data,” said Tasso Arygros, co-president, Teradata Aster. “Secondly, a lot of the unique assets and advantages of the Aster MapReduce platform, including our 50-plus pre-built MapReduce analytical applications and the patented SQL-MapReduce® interface are made available to analyze Hadoop data. The business value is huge – more analytics and better enterprise use of data at a fraction of the time and cost.”