Traditionally CMSs use SQL databases that are really fast when you need allthe information stored together in a record row, but are a bad fit when youneed to search for relationship patterns that are not already stored togetherin your database. A significant performance penalty is incurred for everyadditional table that needs to be joined for a query. That is why SQLdatabases are notoriously bad at deducting relationships from datasets. Graphdatabases however are really good at this task. In this talk we discusspotential application areas of graph databases in existing open source CMSslike Drupal. We believe graph databases could make a big difference when used in key areaswhere traditionally CMSs would fail: Explore large non-uniform datasets: Neo4jgot a lot of attention after it was used by investigative journalists to[identify the organisations and individuals involved in offshore tax evasionin the Panama papers leak](https://neo4j.com/blog/analyzing-panama-papers-neo4j/). Recommend content: Media companies like [the Financial Times areusing Neo4j to display relatedcontent](https://www.youtube.com/watch?v=k47aC01Uy64 their website, this helps them to increase engagement with higherclickthrough rates. Personalisation: [Addidas uses the Neo4j graph database tocreate it’s internal metadata service](https://neo4j.com/news/adidas-neo4j-customer-experience/), offering access and searchability to their dataand making sense of complex interdependencies and relationships. We've created a basic integration that makes it possible for non-developers towork with Neo4j. Combined with Drupal’s content modelling capabilities webelieve it could be a powerful tool for people to explore graph databasesusing a GUI. There is also a case to be made for the use of graph databases inthe Drupal ecosystem: sites that already use Drupal could benefit from itscapabilities.