Amazon Neptune update: Machine learning, data science, and the future of graph databases

Amazon Neptune update: Machine learning, data science, and the future of graph databases

Amazon Neptune just added another query language, openCypher, to its arsenal. That may not sound like a big deal in and of itself, but coupled with updates in machine learning and data science features, it points towards the future of graph databases.

Data models and query languages are admittedly somewhat dry topics for people who are not in the inner circle of connoisseurs. Although graph data models and query languages are no exception to that rule, we’ve tried to keep track of developments in that area, for one main reason.

Graph is the fastest growing area in the biggest segment in enterprise software — databases. Case in point: A series of recent funding rounds, culminating in Neo4j’s $325 million Series F funding round, brought its valuation to over $2 billion.

Neo4j is among the graph database vendors who have been around the longest, and it now is the best-funded one, too. But that does not mean it’s the only one worth keeping an eye on. Amazon entered the graph database market in 2018 with Neptune, and it has been making lots of progress since.

Today, Amazon is unveiling support for openCypher, the open-source query language based on Neo4j’s Cypher. We take the opportunity to unpack what this means, and how it’s related to the future of graph databases, as well as revisit interesting developments in Neptune’s support for machine learning and data science.

Read the full article on ZDNet


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