Neo4j Blog

Graph Data Science features are now available in Bloom 2.3! Just select the Graph Data Science icon and choose from the available algorithms. The GDS plugin needs to be installed on the database for self-managed users, or you can use AuraDS. To get an idea of what Bloom and Graph Data... read more

We don’t take breaks at Neo4j – we’re following up GraphConnect with yet another awesome release of the Graph Data Science (GDS) library. Our engineers are constantly raising the bar, and some of the highlights in this release: 🆕 New algorithms: K-means clustering and Leiden... read more

All great things come in pairs: Peanut butter and jelly (or jam, for our international readers) Fish and chips Gin and tonic Simon and Garfunkel And the list goes on... Well, for some time now, Neo4j Bloom has been a great companion to Neo4j Graph Data Science. For example,... read more

I was 11 years old when Harvey Milk gave his famous “Hope” speech on the steps of San Francisco City Hall on Gay Pride Day 1978. I became aware of Milk five months later when he was assassinated – along with San Francisco mayor George Moscone – by Dan White. That was probably the... read more

Back in January, we previewed Neo4j AuraDS and Google Cloud Vertex AI’s partnership and demonstrated how you can build and deploy graph-based machine learning models. AuraDS is graph data science as a service now running as a managed service on top of GCP.   With the Neo4j Graph... read more

A tremendous amount of database science is devoted to the fine art of “normalization” – making your data easier for their databases to digest. Time to ask yourself: Who does normalization actually serve? Graph computing solves problems. It solves them by modeling those problems using... read more