User:AGEDB

Apache AGE is an open source project developed by the Apache Software Foundation. AGE stands for A Graph Extension, and it is an extension of the PostgreSQL database management system. Apache AGE combines the reliability and stability of PostgreSQL with added features and capabilities of a graph database.

It allows users to store, query, and analyze graph-structured data within the familiar PostgreSQL environment. By leveraging the flexibility and expressiveness of graph data models, Apache AGE enables efficient handling of complex relationships and interconnected data. It provides a wide range of graph query capabilities, including traversal, pattern matching, and graph analytics, making it a tool for various applications such as fraud detection, social network analysis, and recommendation systems.

History
Apache AGE was originally developed by Junseok Yang under a software company, Bitnine Global with the name AGE (Agens Graph Extension) based on their PostgreSQL-forked graph database AgensGraph.

In April 2020, Bitnine donated the project to the Apache Software Foundation and became an Apache Incubator project. AGE then changed its name to Apache AGE standing for A Graph Extension.

In June 2022, Apache AGE was promoted to be a top-level project within the Apache Software Foundation.

Features

 * PostgreSQL Integration Apache AGE is built on top of PostgreSQL, benefiting from its mature ecosystem and community support. It extends PostgreSQL's SQL capabilities by adding new graph-specific functions and operators, enabling users to query and manipulate graph data using familiar SQL syntax. This integration ensures compatibility with existing PostgreSQL deployments and allows for easy integration with other PostgreSQL extensions and tools.
 * Hybrid Query with SQL and Open Cypher Query Languages Apache AGE can simultaneously use SQL queries on tables with OpenCypher queries on Graphs, leading to an efficient data analysis and overall workflow.
 * Queries multiple graphs Apache AGE supports querying multiple graphs and offers a valuable feature that enhances the understanding of data relationship. By analyzing multiple graphs together, users can uncover hidden patterns and gain insights that may not be apparent in a single graph dataset. This capability helps scenarios like social network analysis because graph provide an examination of relationships. With Apache AGE, users can analyze and extract insights from multiple graph datasets within a unified database environment, eliminating the need for switching between different tools or platforms.
 * Label Property on both nodes and edges On Apache AGE, users have the capability to create property indexes on both vertices and edges using SQL syntax. By specifying the desired properties and index type (e.g., B-tree or hash index), users can optimize graph queries that involve searching for specific values within indexed properties. This feature improves query performance and supports the extraction of insights and patterns from graph data while minimizing processing time.