Welcome to Parallel Graph AnalytiX (PGX)
Graph analysis lets you reveal latent information that is not directly apparent from fields in your data, but is encoded as direct and indirect relationships (metadata) between elements of your data. This connectivity-related information is not obvious to the naked eye, but can have tremendous value once uncovered.
What is PGX?
PGX is a toolkit for graph analysis, supporting both efficient graph algorithms and fast SQL-like graph pattern matching queries.
The tools included as part of the PGX distribution include:
- A Java or Python API to load graphs and perform analysis.
- The PGX shell - an interactive REPL that offers a jshell environment for interactive analysis.
- A large collection of built-in algorithms which are part of the Analyst API - covering domains such as community detection, ranking, partitioning, recommendation generation and more.
- PGX Algorithm: a domain-specific-language for writing graph analysis algorithms in a simple and readable form, which the the PGX runtime can transparently optimize and execute.
- PGQL - Property Graph Query Language - an SQL-like language for graph pattern-matching, which includes both SQL-like value-based constraints and topological constraints.
- A large collection of graph machine learning algorithms.
In addition, PGX offers features for filtering graphs, extracting subgraphs and much more.
How can I get it?
PGX is provided to Oracle customers as part of several products:
Oracle Labs PGX project page