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Executive Summary

Analytic Platforms: Beyond the Traditional Data Warehouse
By Merv Adrian and Colin White

The once staid and settled database market has been disrupted by an upwelling of new entrants targeting use cases that have nothing to do with transaction processing. Focused on making more sophisticated, real-time business analysis available to more simultaneous users on larger, richer sets of data, these analytic database management system (ADBMS) players have sought to upend the notion that one database is sufficient for all storage and usage of corporate information. They have evangelized and successfully introduced the analytic platform and proven its value.

A dozen or more new products—the majority introduced after 2005—have been launched to join the pioneering analytics-specific offerings, Teradata and Sybase IQ, each of which boasts thousands of installations. Collectively, the newcomers successfully placed an additional thousand instances by the end of the decade, making it clear that the analytic platform has tapped into a significant market need. They have added hundreds of millions of dollars per year to the billions already being spent with the early entrants—and taken share from incumbent “classic data warehouse relational database management system” products.

Analytic platforms provide two key functions: they manage stored data and execute analytic programs against it. We describe them as follows:

An analytic platform is an integrated and complete solution for managing data and generating business analytics from that data, which offers price/performance and time to value superior to non-specialized offerings. This solution may be delivered as an appliance (software-only, packaged hardware and software, virtual image), and/or in a cloud-based software-as-a-service (SaaS) form."

In the survey conducted for this research, some survey respondents, when confronted with this definition, disagreed with it—they consider the “platform” to be the tools they use to perform the analysis. This may be a legacy of client-server days, when analysis was performed outside the database on “rich client” software on desktops. But the increasing requirement for the ADBMS to power the analysis is upending this thinking, and most agreed with our description. We found:
  • The pace of adoption is strong and accelerating. In 2009, thousands of analytic platforms were sold. And 10 or more players with growing sales are competing for an increasing number of use cases, worldwide, in many industries.

  • The promises being made are being met. Adopters of analytic platforms report that they tested difficult problems in proof-of-concept (POC) exercises, and the selected products were equal to the tasks—beating their incumbent DBMSs.

  • The right selection process is essential. Successful POCs require an understanding of the likely analytical workloads—data types and volumes, the nature of the analysis, and the numbers of users likely to be on the system. And real tests separate winners from losers: often, some candidates can’t get it done at all.

Read the entire study.