Syncsort Upgrades ETL Software For Data Warehousing

Enhancements to DMExpress include support for SAP, IBM mainframes and applications built with Micro Focus tools. Additional data types supported includes Oracle Large Objects.

InformationWeek Staff, Contributor

February 4, 2009

2 Min Read

Syncsort has upgraded its extract, transform and load tool used in data warehousing with the ability to handle larger volumes of data from multiple heterogeneous sources.

DMExpress 5.0, a leading ETL tool in the business intelligence market, also includes additional platform support and ease-of-use features.

The upgrade's enhancements include support for SAP, IBM mainframes and applications built with Micro Focus tools. Additional data types supported by the latest version of DMExpress includes Oracle Large Objects. The upgrade also has been optimized for the Netezza and Vertica data warehouse platforms.

"With its support of SAP, IBM Mainframe, and Micro Focus, as well as its tailored optimization for Netezza and Vertica, DMExpress 5.0 integrates smoothly into our customers' processes and applications, allowing them to focus on what they do best: their business," HarveyTessler, senior VP of marketing for Syncsort, said in a statement.

In benchmark testing in November, DMExpress was used to extract, transform and load 5.4 TB of raw TPC-H data into a Vertica analytic database at a rate of 1.6 GB per second, according to Syncsort. The software ran on Hewlett-Packard c7000 Blade servers at a cost of $46 per GB hour.

"The added functionality in DMExpress 5.0 coupled with the world record achievement reaffirms Syncsort as a leader in the field of data integration," Tessler said.

Pricing for the recently launched upgrade was not disclosed. Syncsort competes with Microsoft and Unisys. Within Gartner's "Magic Quadrant" that rates vendors in various technology categories, Syncsort was listed as a "niche player" in data integration, along withETI and others.

The market comprises vendors that offer software products for constructing and implementing data access and delivery infrastructure for a variety of data integration scenarios,Gartner says. Those scenarios include data acquisition for BI and data warehousing, creation of integrated master data stores, data migrations and conversions, synchronization of data between operational applications, creation of federated views of data from multiple data stores, delivery of data services in anSOA context, and unification of structured and unstructured data.

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