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Hadoop is a key data technology for Big Data, as everyone knows. But the question becomes, how can Big Data help make me more competitive, more efficient, and better able to detect fraud, security breaches, and other abuses?
Businesses don't buy technology — they buy solutions to business problems. The technology is a means to that end. Thus there must be a clear path from technology acquisition to expected business improvements. So when we speak of Hadoop, we actually refer to a whole assortment of Apache open source projects that include core Hadoop (which includes HDFS, YARN, and Hadoop MapReduce) and related projects such as Hive, Pig, and Spark.
Sorting through all these projects, as well as other related software and applications, and choosing the right path for the desired outcome are difficult tasks unless you're an expert. Then, depending on the specific needs of the enterprise, some enhancements from the Hadoop provider may be required to achieve an acceptable result. Choosing the right company to provide Hadoop — one that offers ready-to-implement software packages that converge with Hadoop, and the expertise needed to deploy both open source and commercial tools and applications effectively — is critical to success.
MapR is one such firm. What benefits do MapR users realize versus other options? IDC conducted interviews with nine organizations using MapR as a Big Data platform to understand how they are leveraging it to make their Big Data operations more efficient and effective and drive their businesses with Big Data. Our research found that these organizations are achieving strong business value with MapR, with their investments in MapR projected to yield an average three-year return on investment (ROI) of 382%. Other highlights from our survey findings include the following:
- $19.44 million per interviewed organization in average discounted business benefits over three years
- An 8.2-month payback period
- 31% higher data scientist productivity
- 39% higher application developer productivity
- 42% lower cost of operations than alternative Big Data solution
IDC used our standard methodology based on gathering data from current users of MapR as the foundation for the ROI model. On the basis of these interviews, we performed a three-step process to calculate the ROI and payback period. Interviewed organizations noted both the efficient nature of MapR and the positive impact it is having on their application development teams. In particular, the application development teams are benefiting from the quality and speed of queries carried out on the MapR platform. As a result, they spend less time waiting for data and ensuring its quality. This enables them to reduce the time needed per application development cycle and deliver higher-quality applications, which translates to higher productivity for application development teams (see 39% bullet above).
It's clear from our study results that the cases involved enjoyed compelling cost benefits from the use of Apache Hadoop for MapR. However, since nine organizations cannot be considered statistically significant, IDC cannot assert that MapR is a more cost-effective choice over its competitors in all or even most cases. Yet we can say that, based on the cases examined for this study, MapR is capable of delivering considerable cost benefits over the alternatives.
For the full story on how MapR delivers outstanding value to the customers in our study, I invite you to read the IDC white paper, "The Business Value of MapR," sponsored by MapR Technologies.