ParAccel Introduces Version 2.0 of the ParAccel Analytic Database
Originally published July 1, 2009
ParAccel, Inc., recently introduced version 2.0 of the ParAccel Analytic Database (PADB), the latest version of the company’s high–speed, low–effort, massively parallel (MPP) columnar database management system (DBMS) for data warehousing and analytics. PADB 2.0 tackles the most complex business questions even faster by leveraging dozens of new features and enhancements, including patent–pending innovations in query optimization and SAN integration. PADB’s new Omne query optimizer enables previously unseen levels of performance and sophistication in addressing demanding analytic workloads. In addition, PADB 2.0 offers breakthroughs in enterprise readiness and operational continuity for business critical applications.
Customers look to ParAccel when they seek effortless, high-performance data warehousing and analytic processing. ParAccel customers do not face the schema limitations or indexing requirements that other databases impose, and PADB 2.0 further advances ParAccel’s query sophistication leadership with Omne, a new analytic query optimizer that is uniquely columnar–, MPP– and compression-aware, and includes patent–pending capability to efficiently join unlimited numbers of tables. Omne also boasts advanced automatic query de-correlation, column pruning, and view–folding, as well as other techniques to efficiently process ad hoc and highly complex queries that can give companies an analytic advantage.
“Our data volumes are growing dramatically, and we need the ability to scale our systems to maximize performance while minimizing our costs,” said Stephen Shaw, Founder and CEO of Autometrics, a Software–as–a–Service (SaaS) provider of data quality management and business intelligence (BI) solutions. “The performance improvements we have witnessed with the ParAccel Analytic Database version 2.0 have been so impressive that we have accelerated its adoption into our next-generation SaaS marketing analytics solutions,” he said. “The ParAccel Analytic Database provides a ‘load-and-go’ approach to scalable performance. We were up and running our queries using our existing tools—without any tuning—in a matter of hours.”
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