Graph DB图形数据库笔记

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图形数据库是NoSQL中的一种,也可称为面向/基于图的数据库,对应的英文是Graph Database。
图数据库的基本含义是以“图”这种数据结构存储和查询数据,而不是存储图片的数据库。它的数据模型主要是以节点和关系(边)来体现,也可处理键值对。它的优点是快速解决复杂的关系问题。

图数据库善于处理大量的、复杂的、互联的、多变的网状数据,其效率远远高于传统的关系型数据库的百倍、千倍甚至万倍。例如社交网络、实时推荐、银行交易环路、金融征信系统等领域使用图形数据库可以快速在海量对象之间找到关系。

目前市面上有很多图数据库,最具代表的是Neo4j.
Neo4j官方网址:
https://neo4j.com/
https://neo4j.com/why-graph-databases/

图形数据库排行:
https://db-engines.com/en/ranking/graph+dbms

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    • ag

      What Are the Common Use Cases of Graph Databases?

      Today’s enterprise organizations use graph database technology in a diversity of ways:

      #Fraud detection
      #Real-time recommendation engines
      #Master data management (MDM)
      #Network and IT operations
      #Identity and access management (IAM)

      From enterprises like Walmart, eBay and the adidas Group to startups like Cobrain, Zephyr Health and Wanderu and even non-profits like the ICIJ and the World Economic Forum – case studies with graph databases abound with diversity and depth of use.

      • ag

        Why does My Enterprise Need a Graph Database?

        Today’s CIOs and CTOs don’t just need to manage larger volumes of data – they need to generate insight from their existing data. In this case, the relationships between data points matter more than the individual points themselves.

        In order to leverage data relationships, organizations need a database technology that stores relationship information as a first-class entity. That technology is a graph database.

        Ironically, legacy relational database management systems (RDBMS) are poor at handling data relationships. Their rigid schemas make it difficult to add different connections or adapt to new business requirements.

        Not only do graph databases effectively store data relationships; they’re also flexible when expanding a data model or conforming to changing business needs.