IBM doubles down on big data
IBM has announced two new offerings designed to help companies and governments tackle big data: BLU Acceleration and significant enhancements to IBM's Big Data platform, aimed at making it easier and faster to deploy Hadoop in the enterprise.
BLU Acceleration, IBM says, combines a number of ways to enable users to have much faster access to key information, leading to better decision-making. According to the company, these include "data skipping," an ability to skip over data that doesn't need to be analyzed, such as duplicate information; the ability to analyze data in parallel across different processors; and greater ability to analyze data transparently to the application, without the need to develop a separate layer of data modeling.
BLU Acceleration also features "actionable compression," where data no longer has to be decompressed to be analyzed. BLU Acceleration extends the capabilities of traditional in-memory systems (which allow data to be loaded into RAM instead of hard disks for faster performance) by providing in-memory performance even when data sets exceed the size of the memory.
IBM has also announced PureData System for Hadoop, which reportedly can reduce from weeks to minutes the ramp-up time organizations need to implement enterprise class Hadoop technology, an extension of IBM's Hadoop-based platform, InfoSphere BigInsights. IBM says PureData System for Hadoop integrates into an existing analytics ecosystem and provides a more cost-effective way to move older "cold data" into an active archive, which allows for historical data analysis, while active "hot data" is being analyzed in real time.