Hadoop’s ability to cost-effectively store and manage huge quantities of unstructured data makes it extremely attractive to data-driven enterprises. But tapping its power has required costly MapReduce programming talent. Until now. RedPoint Data Management for Hadoop overcomes this obstacle, enabling you to realize the full promise of Hadoop with ease.
No specialized skills required
RedPoint is the only pure-YARN data quality and data integration application on the market today. No MapReduce skills are required and no MapReduce code is generated “behind the scenes.” RedPoint enables DBAs and business analysts without specialized programming skills to easily access and manipulate data directly within the Hadoop cluster.
In benchmark testing, projects that required hours to build and execute in MapReduce took just minutes in RedPoint, using its intuitive graphical user interface with no programming required.
Complete data quality and integration capabilities
RedPoint delivers more than 350 data quality and data integration functions on Hadoop data, with no limitations — ETL, cleansing, matching, de-duping, merging/purging, householding, parsing, standardizing, and more.
No need to move data
RedPoint executes its data quality and data integration tasks “inside” Hadoop, without data movement. There’s no wasted time or additional storage or computing expense, and RedPoint leverages the intrinsic scalability of Hadoop. And with a zero footprint install, RedPoint doesn’t compete for computing resources in the cluster.
Gain greater control over your data
Enjoy centralized control over your data projects, including detailed version control and multi-server job distribution and monitoring.
RedPoint Data Management was ranked #1 in an industry analyst survey of customers for processing speed, match quality, ease of use, and customer data management.
The RedPoint Difference
- Absolutely no MapReduce is involved, and no MapReduce skills are needed
- All data quality and data integration functions can be performed in the Hadoop cluster
- Data quality and integration processes execute as efficiently—in many cases more efficiently—with RedPoint than with MapReduce-based solutions
- Data doesn’t need to be moved out of Hadoop for processing, analytics, reporting or other action
- No software is installed in the cluster itself, and RedPoint respects YARN’s task prioritization rather than competing for computing resources in the cluster
- Manage data in both traditional and Hadoop repositories with a single product, even bringing together data from separate environments or migrating data from one to the other – such as when building a data lake