It's almost criminal how poorly some traditional data warehouse analytics applications perform under Big Data loads. Architecturally, there are lots of reasons why this is so. And when evaluating how one system will perform compared to another, you'll need to consider the gamut of advantages of one approach over another. I want to touch on just one here: in-database analytics.
Simply put, most production data warehouses installed today are not designed to execute in-database analytics. That means when a query hits the system, the data warehouse generally needs to locate the data in the storage environment and pull it into the analytics engine for execution. Queries are stalled because they were dependent upon the slowest element of the entire system: the mechanical work required by the disk subsystem to retrieve the data. For many organizations, this lag in response time has been a drag on business performance as well as analytics response time.
The arrival of in-database analytics has changed the situation dramatically. With in-database analytics, the analytical functions reside inside the database, so it's no longer necessary for the queries to wait for data to load.
With Sybase IQ 15.4, for example, you can choose from C++, SQL, and Java plug-ins to run data mining and statistical analysis instantly inside the database. No matter how big the Big Data part of your query is, the analytics begin immediately. You do not need to wait for the disks to finish spinning for the analytics work to commence. There's even an in-database plug-in for the Predictive Model Markup Language (PMML) standard so you can apply proven models quickly to a data set and get results fast.
With in-database analytics, companies can analyze information and make decisions that were once beyond their capabilities. They can run critical drill-downs and deep analyses not possible or practical with older technologies. In-database analytics gives organizations a competitive advantage when time-to-decision issues are paramount. It would be crime if your company did not have those advantages.
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