I want to take a minute and highlight a new offering that RedPoint recently announced: RedPoint Data Management for Hadoop. Simply put, it’s data management for Big Data – it allows users to perform the same kind of data management functions on Big Data as they are already to do with traditional data – integrate data, clean it, append it, reformat it, etc.
Previously, if someone wanted to perform these data management functions on data stored in a Hadoop cluster, they had two options:
They could use MapReduce, the programming model used with Hadoop. But programming data management processes with MapReduce is complex – it’s real coding, as you can see in this little snippet of MapReduce code. So, it requires new skills that many companies don’t have on staff. And MapReduce, while able to scale and process large volumes of data, isn’t actually a very efficient way to execute data management processes, so it winds up either being slow or being fast and consuming vast computing resources while it executes. So, MapReduce hasn’t been a great option for data management in Hadoop.
The other option was to move data out of Hadoop into a more traditional data store and perform data management procedures there. But this takes extra time and effort, and is expensive because you need to buy the extra (often more expensive) storage on top of what you’ve already spent on Hadoop. Really, this approach defeats the entire purpose of Hadoop, which is to keep the data in Hadoop where it’s the most economical.
But now, with the advent of Hadoop 2.0 and RedPoint Data Management for Hadoop, there’s another option. With RedPoint, you get an easy-to-use interface to perform your data management functions – the same user interface already used and appreciated by many RedPoint Data Management customers. This allows you to leverage your existing data management and data analyst skills, rather than investing in new MapReduce skills. All your data management processes will execute right in Hadoop, using the YARN infrastructure that’s part of Hadoop 2.0. And it’s fast and efficient, since there’s no MapReduce involved.
Even more valuable, it’s possible to use RedPoint Data Management Hadoop to combine the Big Data in Hadoop with your traditional data to create a more complete view of your customers, to increase customer insight and make targeted marketing more relevant and effect.
And by using RedPoint Data Management for Hadoop the data immediately becomes actionable, because RedPoint’s Data Management functionality is connected to RedPoint Interact, our campaign and interaction management software.
All these benefits are only available from RedPoint because RedPoint Data Management for Hadoop is the only pure YARN data management platform.
In summary, RedPoint Data Management for Hadoop makes Hadoop data management easy, fast, low-cost. And it makes Big Data clean, integrated and usable.
YARN: the Key to overcoming the challenges of broad-based Hadoop Adoption
YARN: The Key To Overcoming The
Challenges To Broad Based Hadoop Adoption