This Week in Neo4j: GenAI Stack, GraphQL, Vectors, Visualisation and more

Welcome to This Week in Neo4j, your weekly fix for news from the world of graph databases!
This is it! NODES 2023 is finally happening this Thursday.
🫵 Do you have signed up already? Running live across time zones around the globe, NODES is featuring over 100 sessions in tracks Application Building, Visualisation as well as AI/ML and an opening keynote by Hannah Fry on “The Joy of Data”. You have to be there!

In other news, we look at how to get started with the GenAI Stack, go into best practices for GraphQL, explain why Vectors and Graph Databases fit together and how to use AI to create Graph Visualisations.

I hope you enjoy this issue,
Alexander Erdl


Elena Kohlwey thrives on making intelligent applications that yield Business benefits. Graph-based applications with Neo4j are just that!
Connect with her on LinkedIn.

Join Elena at NODES 2023. She has been writing user-defined procedures enthusiastically for the last few years. She will demonstrate why and how user-defined procedures can be your knight in shining armour regarding full-graph or big-subgraph traversals. She was also part of a NODES Speaker Roundtable and gave a little teaser of what to expect in her session.

Elena Kohlwey

GenAI STACK: Getting Started with GenAI Stack powered with Docker, LangChain, Neo4j and Ollama
After the launch of the GenAI Stack at DockerCon last week, a lot of people want to get started with it and Ajeet Raina gives an overview of the components that make the GenAI Stack and how to use the stack for building and running AI apps capable of generating text, code, and other creative content.​
GRAPHQL: GraphQL Development Best Practices
GraphQL, on its own, is already a powerful tool with a client-centric approach. In this article, Lidia Zuin shares tips and tricks on making the GraphQL development process more efficient and your product better.
VECTORS: Why Vectors Should Be Stored Together with Knowledge Graph?

Fanghua (Joshua) Yu explains in this article why you should consider architecture principles when choosing a storage technology for vectors, i.e. embeddings of text, image and video produced by machine learning models. This is a crucial step to make solutions based on them ready for production.

VISUALISATION: AI Integration for Data Explorer

Sebastian Müller shares the latest update to Data Explorer, enabling you to engage in a literal conversation with your database, explore content, query and dynamically select elements, highlight specific entities, craft complex queries for future use in your apps and notebooks and automatically generate insightful node visualisations.

Shameless self-plug because we are so looking forward to Hannah Fry!

Don’t forget to share it if you like it!