IBM PureData System for Analytics

The IBM PureData System for Analytics is a relational data warehouse appliance. It is the successor to the Netezza appliance acquired by IBM in 2010. The tag line reads “powered by Netezza technology”. It is a massively parallel processing (MPP) database preinstalled and configured so it works with little or no on-site configuration. This was the differentiator Netezza established very successfully and which prompted the subsequent popularity of appliances or appliance-like products, not just for data warehousing but for other database applications.

IBM delivers the PureData System for Analytics through its global direct sales force. As well as plentiful reference customers in Telecommunications, Finance & Banking, Retail and Marketing Analytics, there does not seem to be any industry that is not penetrated to at least some extent.

Users span a wide set of analytics and reporting use cases, with particular growth in in-database analytics since the introduction of a wide range of analytics capabilities; for example support for R and a partnership with Revolution Analytics for their strong R-based algorithms.

Customers who adopt a ‘logical data warehouse’—an extended data management architecture, comprising data in multiple formats and originating from multiple sources—sometimes describe the role of the PureData System for Analytics as the “relational data lake” in that architecture. Others are using it in more traditional warehousing roles; as data marts, multi-subject-area warehouses, central warehouses and any combination of these.

The major industries for the PureData System for Analytics appear to be Telecommunications, Finance & Banking and Retail, although there are also significant customer references in Marketing Analytics and most industries appear to be penetrated to at least some extent.

IBM is experiencing strong growth within existing large corporate accounts, as data volumes expand and more use cases are implemented. There is also strong growth in new accounts.

This suggests that the basic proposition—faster complex, analytic queries—has resonance in a wide range of situations. While scalability (see Technology) allows support of very large databases, the low entry point (1/4 rack) means that the PureData System for Analytics solution is also available to SMBs. Our research indicates that the 1/4 rack machine was specifically added to appeal in European markets where data volumes are typically lower and there is a greater tendency to start small and incrementally build.

The PureData System for Analytics is shipped in units of 1/4 rack, 1/2 rack, one rack, two racks, four racks and eight racks, which provides capacity for over 700Tb of user data on a single appliance.

The shared-nothing MPP architecture has been refined over a number of generations by IBM, based on the Netezza multi-core processors and patented FPGA (Field Programmable Gate Arrays) co-processor architecture. The FPGAs provide a unique way to stream query results from storage, avoiding pre-loading into memory. This has long been a successful technology for Netezza and, subsequently, IBM.

Recent iterations of the system have added additional performance-enhancing refinements such as columnar compression, snippet result caching, and large memory on processors. The PureData System for Analytics now ships with over 200 in-database analytic functions, including geo-spatial functions (provided by partner ESRI).

One further valuable addition is the ability for users to licence, and pay for, only part of the capacity of an appliance they have installed, so they have expandability built-in and can match investment more closely to their needs, eliminating the ‘chunky’ cost of acquisition. This feature is available from one rack and upwards. The physical 1/2 and 1/4 rack options provide downward scalability.

IBM offers a huge range of services, including application development, analytics, strategy, functional expertise, IT services, outsourcing, hosting and financing.

Since most PureData System for Analytics sales are into organisations with existing, transferable SQL database skills, adoption of the new platform is rarely a major issue.