Up to this point in this blog series, we’ve covered graph databases in general, only using Neo4j when examples were required. However, when it comes to connecting your application to a graph database, specifics are essential. In this RDBMS & Graphs blog series, we’ll explore how relational... read more
Whether you’re ready to move your entire legacy RDBMS into a graph database, you’re syncing databases for polyglot persistence or you’re just conducting a brief proof of concept, at some point you’ll want to bring a graph database into your organization or architecture. Once you’ve... read more
When it comes to a database query language, linguistic efficiency matters. Querying relational databases is easy with SQL. As a declarative query language, SQL allows both for easy ad hoc querying in a database tool as well as specifying use-case related queries in your code. Even... read more
In some regards, graph databases are like the next generation of relational databases, but with first class support for “relationships,” or those implicit connections indicated via foreign keys in traditional relational databases. Each node (entity or attribute) in a native graph property... read more
We already know that relational databases aren’t always enough for handling the volume, velocity and variety of today’s data, but what’s the clear alternative? There are a lot of other database options out there – including a number of NoSQL data stores – but none of them are... read more
Relational databases are powerful tools. Since the 80s, they have been the power-horse of most software applications and continue to do so today. Relational databases (RDBMS) were initially designed to codify paper forms and tabular structures, and they do that exceedingly well. For the right... read more