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New IBM Software Helps Organizations Get More from Big Data


IBM has introduced DB2 10 and InfoSphere Warehouse 10 software that integrates with big data systems, automatically compresses data into tighter spaces to prevent storage sprawl, and slices information from the past, present, and future to eliminate expensive application code. Over the past 4 years, more than 100 clients, 200 business partners, and hundreds of experts from IBM Research and Software Development Labs around the world collaborated to develop the new software.

Key themes of the new software are support for next-generation applications and improving processes so that business users can quickly gain insights and IT staff are freed up for higher value tasks.

Improving decision making, a new Time Travel Query feature enables easier access to data at any point in time. A native implementation of bi-temporal capabilities, this feature accomplishes what many organizations have done in the past with custom coding, says Conor O'Mahony, program director for database software at IBM.  "Providing this capability natively within the database software dramatically simplifies their environments, both from an implementation point of view as well as from an ongoing maintenance point of view." Strong use cases for this capability are in auditing and compliance, he adds.

In addition, the new offering provides adaptive compression and "multi-temperature" data management to instantly compress data to make it easier for business applications to use it and place into the most effective storage. Compression speeds up the flow and better manages big data for use by analytics applications, and the new software automatically assesses how frequently data is needed and moves it to cost effective storage based on how "hot" or "cold" it is, according to IBM.  "What we are doing with the compression is applying multiple techniques to achieve compression rates that haven't been achieved before in a row store," says O'Mahony. "The compression goes hand in hand with the multi-temperature data management and the two combined provide a pretty potent storage optimization capability." A number of clients are saying that they see benefits not only with optimizing the price/performance of the storage environments but also with allowing them to have more data available for analysis, O'Mahony adds.

With this release, IBM has also worked to help customers deal with emerging technologies. For example, a new graph store capability has been added to DB2. "We obviously already have a relational store capability, and we have a native XML store capability that we call PureXML, and now we are adding a graph store capability," O'Mahony explains.  "Not only are we adding the graph store capability, but we are adding support for the SPARQL query language that is most commonly used for graph stores. Now, we support SQL, we support XQuery for native XML retrieval and also SPARQL for working with graph stores."

Information from Hadoop-based systems can also be easily integrated with real-time analysis of structured data in the warehouse to enable better and faster business decisions, the company says.  "We can make a call out to a Hadoop-based system from within DB2 or InfoSphere Warehouse and we seamlessly integrate the results of the analysis from the Hadoop-based system with the results from the data warehouse when we are presenting the results for a query," O'Mahony notes.

For more information on DB2 and InfoSphere Warehouse software, visit www.ibm.com/software/data/db2-warehouse-10


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