For organizations eager to make Hadoop part of their data ecosystem, but struggling to find people with MapReduce skills, RedPoint has a solution. RedPoint’s top-rated data quality and data integration capabilities are now available for Hadoop.
With RedPoint, the same data analysts and database administrators already working with traditional databases can now work just as easily with data stored in Hadoop. No new skills are required. No MapReduce, no Hive, no Pig – thanks to RedPoint’s graphical user interface and pure YARN architecture (certified on Hadoop 2.0 by Hortonworks).
- All data quality and data integration functions can be performed in the Hadoop cluster – ELT, cleanse, match, de-dupe, merge/purge, householding, parsing, partitioning, appending, address standardization, key creation and maintenance, automation, monitoring, notification
- No MapReduce is involved, and no MapReduce skills are needed
- Data quality and integration processes execute as efficiently – and in many cases more efficiently – with RedPoint as with MapReduce-based solutions
- Data doesn’t need to be moved out of Hadoop for processing, analytics, reporting or other action
- No software needs to be installed in the cluster itself, and RedPoint respects YARN’s task prioritization rather than competing for computing resources in the cluster
- Users can manage data in both traditional and Hadoop repositories with a single product, even bringing together data from separate environments or migrate data from one to the other
For more information, see the resources on the right-hand side of this page.
RedPoint has been rated #1 in user surveys for speed, match quality and ease of use, and generally for customer and third party data management. Contact us to see how RedPoint can make managing data quality and data integration in your Hadoop environment easier, faster, lower-cost and more effective.