Shulou(Shulou.com)11/24 Report--

Thanks to CTOnews.com netizen Windelight for the clue delivery! CTOnews.com March 29 news, according to Baidu security official news, recently, Apache HugeGraph (incubating) the first Apache Release version 1.0.0 has been officially released.

HugeGraph is the first open source map database independently developed by Baidu Security in 2017, providing one-stop storage, online query and offline analysis of 100 billion-level large-scale map data, and is widely used in social networks, advertising recommendations, network security, financial risk control, intelligent robots and other scenarios.

HugeGraph opened source in 2018, and officially passed the vote of the world's top open source organization Apache Software Foundation in January 2022, and officially became the world's first map database project to join the Apache incubation with a unanimous vote. In May of the same year, it officially entered Apache to start incubation, promoting the domestic map database to the world.

As of CTOnews.com, HugeGraph has 2200 + Stars on GitHub. In addition, the total number of Contributors of the project exceeds 80, community version downloads exceed 20,000, and more than 100 community users and organizations are using it, including Internet Merchants Bank, NetEase Games, 360Security, Didi, iFLYTEK, Huya TV, CVTE, cargo lesbians and so on.

According to reports, version 1.0.0 of Apache HugeGraph has made a lot of improvements and fixes in terms of performance, practicality and ease of use, including 25000 + lines of Pull Request code change submission:

In terms of system language, components such as graph database and graph computing are upgraded to adapt to Java 11, covering all subprojects, and new support for Cypher graph query language. At present, both Gremlin and Cypher mainstream graph query languages are supported.

Support more built-in graph algorithms on the server, including 16 OLAP algorithms, including LPA, Louvain, PageRank, Betweenness / Closeness / Eigencentrality Centrality, RingsDetect, etc., and 2 OLTP algorithms, including adamic-adar and resource-allocation

On the large-scale parallel graph computing framework (Computer), it supports MPP computing of massive map data, especially space-consuming algorithms such as diffusivity / centrality, supports K8s Standalone (stand-alone) mode, and reserves Yarn interface to realize direct docking.

In the support of big data component, it supports Flink CDC data streaming and synchronous import, Spark batch import data, and Bypass Server mode, which greatly improves the import / export / graph migration performance and convenience of graph database in online / offline scenarios.

In terms of ease of use, it provides one-click Server / Hubble containerization Docker support, and reconstructs the tool chain around the integration map for more than 120 detailed version updates such as HugeGraph Toolchain.

Apache HugeGraph version 1.0.0: click here to view

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