Graph databases have matured into mainstream technologies and deliver tremendous value to organisations across any industry. They are more flexible than traditional relational databases as they enable us to leverage the relationships in our data in a way relational databases cannot do. In the time of AI and Big Data, this creates opportunities for any organisation.
However, developing with graph databases requires us to overcome plenty of challenges when it comes to data modelling, maintaining consistency of our data among others.
In this talk, we discuss:
- How TypeDB compares to labelled property graphs and how it addresses these challenges. While both technologies share similarities, they are fundamentally different.
- We’ll cover how to read & write data
- How to model complex domains
- TypeDB’s ability to perform machine reasoning at scale