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Native parallel graph databases may be useful here. They can dig deep through money trails, going as many levels as needed, 10, 20 or more, across datasets on a global scale. They are designed to traverse unknown paths to find connections, no matter how deep that connection goes. Read more here.
Today’s updates are focused on improving artificial intelligence and machine learning workloads, and include configuration for distributed graphs and replica instances for high availability, plus the ability to leverage elastic file systems for backup and restore. Read more here.
In a series of announcements that are backed by customer growth and unprecedented revenue boost, TigerGraph announced the general availability of TigerGraph Cloud, a new funding round worth $32 million. These are marked with new footprints in Europe with expansions in offices and senior leadership. As part of the expansive drive in its Operations, TigerGraph announced the appointment of Martin Darling as GM for EMEA and Zeljko Dodlek as director of sales for DACH. The company also announced the opening of new offices in Munich, Germany.
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Companies that need the power of a graph database to solve tough analytics challenges in the fields like fraud detection or customer 360 can get up and running quickly with TigerGraph Cloud, a new cloud-based graph analytic service unveiled today by TigerGraph at the Strata Data Conference. The company also announced a $32-million Series B round, bringing its total funding to $65 million.
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