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🕸🐅Over 50 New Graph Algorithms in TigerGraph: Fall 2021 Release
TigerGraph is a popular fast and scalable graph database with massively parallel processing and ACID transaction support, making it the fastest and most scalable graphics platform. Thanks to its efficient data compression and MPP architecture, it can analyze huge amounts of information in real time. And the internal query language GSQL is very similar to standard SQL, familiar to every analyst.
October 2021 release includes 50 new algorithms, for example, embedded graphs node2vec and FastRP, similarity algorithms ("Nearest Neighbor Approximation", "Euclidean Similarity", "Overlap Similarity" and "Pearson Similarity"), structural similarity algorithms for predicting topological relationships and random path algorithms. In the first half of 2022, the developers promise to add neural networks and other ML methods to build analytical pipelines on graphs. Despite the fact that TigerGraph is positioned as a powerful enterprise solution, the source code of this system is open and available for free download from Github.
https://www.tigergraph.com/blogs/about-tigergraph/graph-data-science-library/
https://github.com/tigergraph
TigerGraph TigerGraph Graph Algorithms | Obtain Insights at Scale Graph algorithms are essential building blocks for analyzing your connected data and for AI methods which gain deeper insights from that data
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