Neo4j from R

Goals

If you are an R developer or data scientist, this guide provides an overview of options for connecting from R to Neo4j and even using Neo4j from within R-Studio.

Prerequisites

You should be familiar with graph database concepts and the property graph model. You should have created an Neo4j AuraDB cloud instance, or installed Neo4j locally

Intermediate

Neo4j Community Drivers

Members of the each programming language community have invested a lot of time and love to develop each one of the community drivers for Neo4j, so if you use any one of them, please provide feedback to the authors.

The community drivers have been graciously contributed by the Neo4j community. Many of them are fully featured and well-maintained, but some may not be. Neo4j does not take any responsibility for their usability.

Neo4j for R Developers and Data Scientists

Neo4R

The goal of {neo4r} is to provide a modern and flexible Neo4J driver for R.

It’s modern in the sense that the results are returned as tibbles whenever possible, it relies on modern tools, and it is designed to work with pipes. Our goal is to provide a driver that can be easily integrated in a data analysis workflow, especially by providing an API working smoothly with other data analysis ({dplyr} or {purrr}) and graph packages ({igraph}, {ggraph}, {visNetwork}…).

It was developed by ThinkR, led by Colin Fay.

Currently it connects to Neo4j via Http but we plan to integrate it with the C-connector for Bolt, Seabolt.

Author

Colin Fay

Package

Source

https://github.com/neo4j-rstats/neo4r

Neo4j-Rstats

https://github.com/neo4j-rstats/

Neo4j Online Community

https://community.neo4j.com/c/drivers-stacks/r

Docs