The number of NoSQL database options is vast, and distinct product categories occupy separate niches. That makes it imperative to understand what works best for specific applications when evaluating NoSQL software. NoSQL databases are designed to address processing issues created by expanding data volumes and diversity, particularly in big data applications. But there’s no lack of either volume or diversity in the ranks of NoSQL technologies, leaving IT and data managers with lots of alternatives to sort through when evaluating technology options. “There are so many NoSQL databases today — I think we’re challenged by two or three on a daily basis,” quipped Michael Simone, global head of CitiData platform engineering at Citigroup Inc., during a presentation at the 2014 MongoDB World conference in New York. In reality, Citi currently has limited itself to using the MongoDB database as a NoSQL alternative to relational software in a small number of applications, Simone said. But his joke pointed to the need for organizations considering NoSQL products to focus on finding the one that can best solve their application problems.
Trofymenko and his team use Neo4j, from Neo Technology Inc., to do such mappings. “We can get a lot of information in a graph database,” he said. “Say a user is very interested in diabetes or exercise — you see it.” That’s valuable for a site that seeks to take millions of free-text searches, relate them to relevant health terms and build a data platform that helps users find information about possible treatment and assistance.

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