Netrics Matching Engine
Accurate
ScalableScalable
Delivers real-time results even for large datasets
Probabilistic matching software uses an enormous amount of computer resources (memory and processing power) when working with large databases: rule sets often drive multiple queries to find a single data record.
“Under the covers”, whether probabilistic or not, advanced matching software needs to handle field-level inexact matching issues somehow. Developers often compensate for the lack of sophisticated matching technology using multiple "wildcard" searches, or testing validity of error-prone algorithms such as Soundex.
More sophisticated algorithms such as "Edit Distance" are highly computationally intensive themselves. Computation increases exponentially with the size of the "edit window" and the number of records being matched.
If you’re not using Netrics, to deliver a solution within acceptable resources, you may have to compromise. For example, you might accept serious constraints on the number of records tested, or the matching window applied, and risk missing matches. Alternatively, you might be forced to accept batch processing, and risk being late with the right answer.
Or you can deploy Netrics.
Netrics' patented bi-partite graph technology is inherently efficient, and scales linearly with the number of records in the database. The technology has been proven in real-time applications for databases as large as 500 million records.
Netrics' embeddable architecture operates independently of your existing applications and DBMS. It can be deployed on separate computer resources, limiting the cost, and minimizing any impact on the responsiveness and throughput of your current applications.
