Have you considered the total cost of ownership and time-to-value while choosing your data warehouse/analytical appliance?

By Rahul Agarwal

In my previous blog post, I mentioned that in a big data world traditional data warehouses are not disappearing but are being modernized to add new workloads, simplify operations and integrate high-performance analytics.

The role of analytical appliances in modernizing your data warehouse

One way to modernize your data warehouse is to use ‘analytical appliances’, integrated systems that pre-configure and pre-integrate servers, storage, networking hardware, middleware, and data management software.  Such integrated systems offer better-optimized performance and faster deployment than conventionally configured databases, servers and disk arrays. An IDC survey of users of such systems, conducted earlier had found that almost half of the users were experiencing improved IT staff efficiency, besides reducing management tools. In addition, the users of these ‘converged’ systems experienced improved business agility and lower total cost of ownership (TCO).

So what parameters can you use to choose the right appliance for your enterprise?

There are numerous analytical appliances on the market, each having unique architecture and technology.  So how do you decide which one is best for you? According to a recently published ITG paper, the choice involves “basic decisions about the nature of organizational informational architectures, and about trade-offs between compatibility with existing software and skills, speed of new application deployment and costs.

This white paper from ITG compares IBM PureData System for Analytics (powered by Netezza) and Oracle Exadata Database machine using cost of ownership and time to value. Results are based on input from 42 companies employing IBM PureData System for Analytics or Oracle Exadata systems in comparable roles.

1. Cost of ownership: This includes acquisition and deployment costs as well as maintenance and support, personnel costs for database, system and storage administration, and facilities costs over a 3-year period.

2. Time to value: An analytics application may deliver substantial business gains almost as soon as it is up and running. Any delay in bringing up the platform may result in lost opportunity in the form of lost revenues and profit opportunities. Greater the time to value, greater the lost opportunity cost.

The report finds “significant variances” between the 2 systems in 2 areas discussed above, as much as 1.8x and 3x cost of ownership and lost opportunity costs respectively.

More details

So if you are in the looking for data warehouse appliance, do keep this report in mind. For more details on the results, methodology and assumptions employed in this report read it here

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About Rahul Agarwal

Rahul Agarwal is a member of the worldwide product marketing team at IBM that focuses on data warehouse and database technology. Rahul has held a variety of business management, product marketing, and other roles in other companies including HCL Technologies and HP before joining IBM.  Rahul studied at the Indian Institute of Management, Kozhikode and holds a bachelor of engineering (electronics) degree from the University of Pune, India. Rahul’s Twitter handle :  @rahulag80


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