Chapter 6. Algorithms

This chapter describes each of the algorithms in the Neo4j Graph Data Science library, including algorithm tiers, execution modes and general syntax.

The Neo4j Graph Data Science (GDS) library contains many graph algorithms. The algorithms are divided into categories which represent different problem classes. The categories are listed in this chapter.

Algorithms exist in one of three tiers of maturity:

Production-quality
- Indicates that the algorithm has been tested with regards to stability and scalability.
- Algorithms in this tier are prefixed with gds.<algorithm>.
Beta
- Indicates that the algorithm is a candidate for the production-quality tier.
- Algorithms in this tier are prefixed with gds.beta.<algorithm>.
Alpha
- Indicates that the algorithm is experimental and might be changed or removed at any time.
- Algorithms in this tier are prefixed with gds.alpha.<algorithm>.

This chapter is divided into the following sections:

Section 6.1, “Syntax overview”
Section 6.2, “Centrality algorithms”
Section 6.3, “Community detection algorithms”
Section 6.4, “Similarity algorithms”
Section 6.5, “Path finding algorithms”
Section 6.6, “Link Prediction algorithms”
Section 6.7, “Node embeddings”
Section 6.8, “Auxiliary procedures”
Section 6.9, “Pregel API”