SAND Technology Included in Gartner’s Magic Quadrant for Data Warehouse Database Management Systems, 2009
Montreal, Canada – February 26, 2010 SAND Technology Inc. (OTCBB: SNDTF.OB), an international provider of intelligent information management software and best practices, has again been included in Gartner’s recent Magic Quadrant for Data Warehouse Database Management Systems. The Magic Quadrant is a representation of the data warehouse DBMS market that evaluates vendors based on their completeness of vision and ability to execute.
“We are pleased and honored to be included in Gartner’s Magic Quadrant,” said Linda Arens, Vice President, Global Alliances and Marketing for SAND Technology. “In my opinion, this demonstrates that SAND continues to be acknowledged as a significant player in the data warehousing market, based on our success in helping customers in a range of industries enhance their competitiveness by reducing data infrastructure and administration costs, while improving their ability to respond quickly to rapidly changing business requirements.”
SAND/DNA enables enterprise customers in all industries to cost-effectively retain massive amounts of compressed data in a nearline repository for extended periods, in accordance with any applicable business rules and regulatory requirements, and to rapidly retrieve information when needed. A centralized data management solution with unparalleled performance and storage efficiency, the SAND/DNA suite dramatically reduces costs and management complexity while ensuring continuous data availability. Organizations can create data marts on demand to respond to any analytic requirement with all enterprise data — current or historical, detailed or summarized. SAND/DNA’s advanced information management technology compresses data to typically 10 percent of its original size, while giving users the ability to query any attributes of the data without decompressing it first. This next-generation capability is ideal for satisfying enterprise compliance requirements as well as for leveraging valuable information in data warehouses