Apache AGE
Graph Database for PostgreSQL

Apache AGE is a PostgreSQL Graph database compatible with PostgreSQL's distributed assets and leverages graph data structures to analyze and use relationships and patterns in data.

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Apache AGE®, Graph database
Apache AGE® is a PostgreSQL that provides graph database functionality.

The goal of Apache AGE® is to provide graph data processing and analytics capability to all relational databases.

Through Apache AGE, PostgreSQL users will gain access to graph query modeling within the existing relational database.

Users can read and write graph data in nodes and edges. They can also use various algorithms such as variable length and edge traversal when analyzing data.img
Key Updates
ASF PROJECT SPOTLIGHT: APACHE AGE
Read the full blog post now and be a part of shaping the future of graph database technology.

Why do you use Apache AGE?
Give feedback at the GitHub (#1705)

Add graph store implementation for Apache AGE in langchain github
Check out the pull request for the implementation of the GraphStore class for the Apache Age graph database in the LangChain repository.

Proposal: Vector handling with extension(pgvector)
A proposal for applying PGvector to Apache AGE has been posted on GitHub. Please read and leave a comment or opinion if you are interested.

Apache AGE is now compatible with PostgreSQL 16!
Check the changelog for the latest version





This week's article by community

Graph Database in PostgreSQL: Apache AGE

Graph database have gained popularity in recent years due to their ability to handle complex relationships between data. Unlike traditional relational database, which store data in tables, graph database represent data as nodes, edges, and properties. Nodes represent entities, edges represent the relationships between those entities, and properties represent the attributes of both.

PostgreSQL, a popular relational database, can also function as a graph database through the use of an extension called Apache AGE. With Apache AGE, users can leverage the flexibility and scalability of graph database while still utilizing PostgreSQL's advanced SQL querying capabilities and transaction support.

To use Apache AGE, users must first install it as an extension and then model their data as nodes and edges. Apache AGE comes with its own set of SQL extensions, similar to Cypher, that allows users to query their graph database. However, users can also still use SQL to query their graph database if desired.

For those new to graph database, Apache AGE comes with a tutorial to help them get started. Additionally, you may use the #apache-age tag for questions on Stack Overflow, join the project's Discord channel, or open an issue on GitHub, the Apache AGE community is readily available to provide support and answer questions.

Overall, graph database offer a new way of thinking about how to store and query complex relationships between data. With Apache AGE, users can easily transform their PostgreSQL database into a graph database and take advantage of the benefits that come with this type of database.



Last week's article by community





Comparison of Apache AGE, PostGraphile, and Hasura



◾ Apache AGE: Graph Database for PostgreSQL

Apache AGE extends PostgreSQL, transforming it into a graph database. This enables handling complex data relationships and graph structures, supplemented by the power of Cypher queries for graph-specific operations.

    Key Features:
  • Graph & SQL Queries
  • Integration deeply with existing PostgreSQL features, making it a robust and scalable solution for graph data management without the need for external graph databases.
  • Ideal for applications that require complex data relationship analysis,such as social networks, recommendation systems, and knowledge graphs.


    • ◾ PostGraphile: GraphQL API from PostgreSQL Schema

    PostGraphile is a tool for building a GraphQL API on top of an existing PostgreSQL schema.
    It's designed for efficiency in web development, allowing real-time data access and manipulation through GraphQL interface.

      Key Features:
  • Automates the creation of GraphQL APIs from existing PostgreSQL.
  • Offers subscriptions for real-time data updates.
  • Best suited for projects requiring quick development of web or mobile backends with real-time data needs, but without complex graph data management requirements.


    • ◾ Hasura: Real-Time GraphQL Engine for PostgreSQL

    Hasura is a GraphQL server engine that dynamically generates real-time GraphQL APIs from a PostgreSQL database.
    It emphasizes performance and developer productivity, with an easy setup process and tools for managing access and queries.

      Key Features:
  • Provides a user-friendly interface for setting up and managing GraphQL endpoints.
  • Optimized for performance, supporting high-volume traffic.
  • Ideal for developers needing a fast, scalable GraphQL layer over their PostgreSQL databases.


    • ◾ Conclusion

    Apache AGE is ideal for sophisticated graph data tasks within PostgreSQL.
    PostGraphile and Hasura excel in quick GraphQL API deployment for example for web and mobile, complementing AGE's rich graph features.





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