Neo4j Labs is a collection of the latest innovations in graph technology. These projects are designed and developed by the Neo4j team as a way to test functionality and extensions of our product offerings. A project typically either graduates to being maintained as a formal Neo4j project or is deprecated with source made available publicly.
These Labs are supported via the online community. They are actively developed and maintained, but we don’t provide any SLAs or guarantees around backwards compatibility and deprecation.
GraphQL has become a comprehensive stack for API development and consolidation. Our GRANDstack and Neo4j-GraphQL-js offerings combine the most common tools and frameworks: GraphQL, React, Apollo and Neo4j Database.
As the most comprehensive developer toolkit for Neo4j, the APOC library provides a wide range of procedures and functions that make your life as a Neo4j user easier. APOC includes data integration, graph refactoring, data conversion, operational functionality and more.
The Halin Monitoring App allows you to monitor your Neo4j deployment and identify bottlenecks or incorrect configurations, with insights into currently running queries and workloads. The app also provides access to metrics and logs.
Streaming event data is an integral part of most modern data architectures. With Neo4j Kafka Integration you can integrate Neo4j both as a sink or source into your setup. The integration is available as a Kafka Connect plugin and Neo4j Server extension..
Having an easy way of loading data from relational databases into Neo4j is one of the first steps many users take. The Neo4j-ETL Tool makes this easy by inferring a graph model from the relational meta model that you can then adapt to fit your needs. Given that transformation, this tool also handles the actual import for you.
Neosemantics integrates RDF and Linked Data with Neo4j. It allows to import a wide variety of RDF formats and to expose Neo4j property graphs as Linked Data. Ontology and Inference are also partially supported.
Neo4j-Helm is a tool for configuring and deploying Neo4j instances on Kubernetes. By using the Helm package manager for Kubernetes, it makes it simple to specify advanced configurations of Neo4j, both standalone and cluster, and run them with Kubernetes across many cloud platforms.
Current Neo4j Labs projects are being actively worked on by our engineers, and may be rough around the edges, with changing APIs, as they push the edge of the envelope. Therefore, we cannot provide official commercial support for these projects or guarantee longevity. However, some Neo4j customers and users still love the functionality of these projects and choose to continue using them in production environments.
We welcome contributions for those labs which are open source projects. You’ll find links to GitHub repositories - feel free to submit PRs. We’ve also created a discussion category for Labs on community.neo4j.com
The Neo4j Docker containers started off as a Labs project to explore how well Neo4j would run in a containerized environment. They quickly gained popularity and are heavily used by both Neo4j and customers, so we’ve graduated them to be officially part of the Neo4j release distribution.
The Graph Data Science Library started off as the Graph Algorithms Library, a Labs project that was launched in 2017. The library offered highly parallelized implementation that work well with large scale graphs, and graduated in early 2020.
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