Posted on

When Not To Use a Graph Database

The use of graph databases has grown massively in recent years, and they are becoming promising solutions for organizations in any industry. Their increased flexibility makes it easier to leverage relationships and connections in a way that traditional relational databases can't do. But how do you know when to use a graph database? In this article, we explore what to consider if you’re thinking of using a graph database and show how the best approach may be to not use one at all.

What Is a Graph Database?

A graph database is a type of database that uses graph theory as the foundation for its data model. Graph databases consider connectedness as a first-class citizen, making them better suited to represent connected data than more old-school relational databases.

Posted on

Accumulator 101

Motivation

GSQL is a Turing complete Graph Database query language. Compared to other graph query languages, the biggest advantage is its support of Accumulators — global or attachable to each vertex.

In addition to providing the classic pattern match syntax, which is easy to master, GSQL supports powerful run-time vertex attributes (a.k.a local accumulators) and global state variables (a.k.a global accumulators). I have seen users learning and adopting pattern match syntax within ten minutes. However, I also witnessed the uneasiness of learning and adopting accumulators for beginners.

Posted on

What Are the Major Advantages of Using a Graph Database?

A graph database is a data management system software. The building blocks are vertices and edges. To put it in a more familiar context, a relational database is also a data management software in which the building blocks are tables. Both require loading data into the software and using a query language or APIs to access the data.

Relational databases boomed in the 1980s. Many commercial companies (i.e. Oracle, Ingres, IBM) backed the relational model (tabular organization) of data management. In that era, the main data management need was to generate reports.