Graph Query Languages 101 Simplicity & Speed
By Ricky Sun, Jason Zhang, and Victor Wang
We have learned that relational databases use SQL and two-dimensional tables to model after the world, this is in deep contrast to how graph databases address the problem. In short, graph databases use high-dimensional data modeling strategies to 100% resemble the world – and because the real-world is highly dimensional, graph is considered 100% natural. This naturalness comes with a challenge, especially for people who are accustomed to the trade-off hypothesis or the zero-sum game theories. The challenge is that you have to be brave enough and smart enough to think out of the box and the limiting belief that 'There is no better way of modeling the real-world problems beyond SQL or RDBMS'.
In our previous essay on The Evolution of Database Query Languages, we depicted the evolution of SQL and NoSQL, and their advantages and disadvantages. In today’s business world, we are seeing more and more businesses relying on graph analytics and graph computing to empower their business decisions.
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