Hadoop-related technologies can save you (lots of) money when it comes to system/infrastructure costs, those cost savings can quickly disappear when you start looking at application/development costs.
It all depends on what analytic data problem youre trying to solve. In this post, well take a look at two big data examples and determine, for each example, which platform the enterprise data warehouse (EDW) or Hadoop will be the most cost-effective over time.
These two examples come from WinterCorp’s Big Data – What Does It Really Cost? special report, which introduces the Total Cost of Data (TCOD) framework. The first example is building an enterprise data warehouse, and the second example is building a data refinery. We’ll first look at the requirements for each example, and then compare the costs. Again, the question we want to answer is: Which platform – the EDW or Hadoop – is the most cost-effective over time?
These results may surprise you. Keep in mind that the results are just estimates (because a lot of assumptions have to be made), but these estimates trump anecdotal guesses any day.
The data warehouse platform ($265 million) is far more cost-effective than a Hadoop solution ($740 million). Choosing the data warehouse platform in this case lowers the overall cost by a factor of 2.8. Further analysis shows that you will get essentially the same result for a data warehouse ranging in size from 50 TB to 2 PB.
The development of complex queries and analytics are the dominant cost factors in the example. Of the $44 million estimated for EDW system cost, $10.8 million is the initial acquisition cost – about 4% of the TCOD.
While it is common to focus on the first major outlay in the project—i.e., the acquisition of a platform—the total cost of the project is far more important, and other factors greatly outweigh all the system costs combined.
The purpose of the TCOD framework is to help organizations estimate the total cost of a big data solution for an analytic data problem. It considers two major platforms for implementing big data analytics – the enterprise data warehouse and Hadoop – and helps you understand where each big data platform architecture works best.
The TCOD framework was developed by Richard Winter and his team at WinterCorp, a consultancy focused on large scale data management challenges. WinterCorp introduced the TCOD framework in a 2013 special report called Big Data – What Does It Really Cost?.
So if you’re ready to roll up your sleeves and do the hard work of figuring out what big data really costs, then the TCOD framework is waiting for you.