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Infosolve Technologies Demonstrates OpenDQ's Massively Scalable Fuzzy Matching Capabilities on a Cloud Platform
Date:5/11/2010

Industry's first zero license cost fuzzy matching solution that matches hundreds of millions of records redefines scalability, price/performance benchmarks in the market.

South Brunswick, NJ (PRWEB) May 11, 2010 -- Infosolve Technologies, industry leading experts in the area of data quality solutions, are pleased to announce the price/performance benchmark results of their massively scalable OpenDQ fuzzy matching solution on the Amazon EC2 cloud platform.

- 100 million records on a 50 node cluster are matched in 40 Minutes at a cost of $25.
- 150 million records on a 50 node cluster are matched in 1 hour 20 Minutes at a cost of $50.
- 200 million records on a 75 node cluster are matched in 2 hours 12 minutes at a cost of $112.50.
- 250 million records on a 75 node cluster are matched in 3 hours 32 minutes at a cost of $150.

- Matching performed on five attributes using the Jaro-Winkler algorithm.
- Each node is an Amazon EC2 M1.Xlarge instance type.
- The cost of each EC2 instance is 50 cents/hour (as of 04/30/2010).
- Benchmarks are performed on a generated test data set; real world data benchmarks may be different.
- Matching can be run on any general purpose cluster of computers.

Record Linkage/Data Matching using fuzzy matching algorithms on data sets that do not have a unique identifier between records is one of the most important process steps in applications such as: single view of the customer, fraud detection, electronic health care records, terrorist and no fly watch lists, auditing and compliance, master data management, data de-duplication, and social media/multi channel marketing programs. These processes impose heavy compute loads on servers and take a considerable amount of time to complete on large data sets. With OpenDQ’s massively scalable data matching solution, organizations now have the ability to match lar
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Infosolve Technologies Demonstrates OpenDQ's Massively Scalable Fuzzy Matching Capabilities on a Cloud Platform 
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