NASHVILLE, Tenn., Oct. 20, 2014 /PRNewswire/ -- PARTNERS CONFERENCE & EXPO -- Teradata Corp. (NYSE: TDC), the big data analytics and marketing applications company, today announced engineering advancements to the Teradata Database that deliver analytic performance and system efficiency through new memory and CPU optimizations. These enhancements strengthen Teradata's approach to in-memory computing and enable customers to seamlessly and automatically realize the greatest benefit from their investment in memory.

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"Teradata is relentlessly dedicated to engineering a smarter, simpler way to leverage memory and CPU to drive performance," said Scott Gnau, president, Teradata Labs. "Blindly throwing additional memory at a problem has diminishing returns, particularly when it comes to big data. Teradata's sophisticated approach automatically and efficiently places the right data in-memory to get the performance they need for the best cost."

In Teradata Database 15.10, Teradata Intelligent Memory will be enhanced with the following capabilities, which reduce the load on memory bandwidth, improve CPU efficiency, reduce I/O to disk, and improve overall system efficiency:



    --  Query pipelining and new in-memory table structures  Pipelining is an
        innovative approach to query processing where the output of one query
        step feeds into the input of the next query step without leaving memory.
        This greatly increases system efficiency and throughput by reducing
        unnecessary data movement. Also, while this data is held in memory, it
        will be stored as column-partitioned tables, instead of row-partitioned
        tables, which reduces the memory footprint and speeds consumption by the
        CPU.

    --  Exploit CPU instructions and cacheNew algorithms take advantage of
        Intel's vector instructions and on-board cache to apply operations in
        parallel. This increases CPU throughput and efficiency and further
        reduces the amount of data moving in and out of memory. The Teradata
        Database will also optimize Intel's new Haswell processor, which will
        feature additional vector instructions, further improving CPU
        performance, and efficiency.

    --  New data temperature measurements Teradata Virtual Storage now uses new
        weightings for measuring how frequently data is accessed by
        distinguishing between tactical and strategic workloads. Tactical
        workloads, which are generally high-priority business queries, increase
        the heat of data faster than strategic workloads. The hot or frequently
        used data is moved into memory faster. This aligns data in memory with
        business priorities. Teradata also increased the precision of the hot
        data stored in-memory by allowing logical I/O's, data referenced
        in-memory, to also count towards data temperature. The result is even
        more accurate alignment of business needs with data held in-memory to
        improve analytic performance.

These enhancements to the Teradata Database will be available in the first half of 2015.

About Teradata
Teradata (NYSE: TDC) helps companies get more value from data than any other company. Teradata's leading portfolio of big data analytic solutions, integrated marketing applications, and services can help organizations gain a sustainable competitive advantage with data. Visit teradata.com.

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Teradata and the Teradata logo are trademarks or registered trademarks of Teradata Corporation and/or its affiliates in the U.S. and worldwide.

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SOURCE Teradata