Digital Financial Reporting

The GQL Manifesto is an international effort to create an industry standard graph query language (GQL).

SQL, or structured query language, is a declarative language that one of the key underpinnings of modern information technology. SQL is the way one interfaces with a relational database management system (RDBMS) which is used to store data.  One of my personal favorite tools that I have made use of during my entire career as an accountant has been Microsoft Access and Microsoft SQL Server.

The international effort to create GQL is an industry attempt to create a similar industry standard for graph databases.  It is highly likely that this effort will be successful and GQL will very likely become an ISO standard GQL.

What would be incredible in my view is if Microsoft were to create a product similar to Microsoft Access or if they were to enhance Microsoft Access to support GQL.  Having this as part of the Microsoft Office suite of products would be a very good thing in my view.

The book Graph Databases that is published by Neo4j provides an excellent explanation of the fundamental difference between a graph database and a relational database.  See Chapter 2, Options for Storing Connected Data, page 11 which is PDF page 29.  Here is my attempt to explain that difference.

In a relational database, information about relationships is not part of the actual relational model.  In a graph database, information about relationships is fundamentally part of the information model.

That statement might seem odd. But it is true.  Relationships are not "first class citizens" in relational databases, but they are in graph databases.  Now, you can absolutely express relationships and even the meaning of relationships in relational databases.  But, you have to do it in the database itself, you cannot do it as part of the database schema.  In a graph database the relationship information is part of the schema rather than added into the data.

Graph databases are fundamentally more powerful that relational databases.