ParAccel Combines Column-Store, MPP And In-Database Analytics
ParAccel is the developer of the ParAccel Analytic Database (PADB), a database that combines the fast, selective-querying and compression advantages of a column-store database with the scale-out capabilities of massively parallel processing. The vendor says its platform supports a range of analyses, from reporting to complex advanced-analytics workloads. Built-in analytics enable analysts to perform advanced mathematical, statistical, and data-mining functions, and an open API extends in-database processing capabilities to third-party analytic applications. Table functions are used to feed and receive results to and from third-party and custom algorithms written in languages such as C and C++. ParAccel has partnered with Fuzzy Logix, a vendor that offers an extensive library of descriptive statistics, Monte Carlo simulations and pattern-recognition functions. The table functions approach also supports MapReduce techniques and more than 700 analyses commonly used by financial services.