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Update postgreSQL docker image link

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yangdx 2025-11-20 12:34:49 +08:00
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README-zh.md
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@ -881,7 +881,7 @@ rag = LightRAG(
对于生产级场景，您很可能想要利用企业级解决方案。PostgreSQL可以为您提供一站式储解解决方案，作为KV存储、向量数据库（pgvector）和图数据库（apache AGE）。支持 PostgreSQL 版本为16.6或以上。 对于生产级场景，您很可能想要利用企业级解决方案。PostgreSQL可以为您提供一站式储解解决方案，作为KV存储、向量数据库（pgvector）和图数据库（apache AGE）。支持 PostgreSQL 版本为16.6或以上。
* 如果您是初学者并想避免麻烦，推荐使用docker，请从这个镜像开始（请务必阅读概述）：https://hub.docker.com/r/shangor/postgres-for-rag * 如果您是初学者并想避免麻烦，推荐使用docker，请从这个镜像开始（默认帐号密码:rag/rag）：https://hub.docker.com/r/gzdaniel/postgres-for-rag
* Apache AGE的性能不如Neo4j。追求高性能的图数据库请使用Noe4j。 * Apache AGE的性能不如Neo4j。追求高性能的图数据库请使用Noe4j。
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README.md
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@ -845,7 +845,7 @@ see test_neo4j.py for a working example.
For production level scenarios you will most likely want to leverage an enterprise solution. PostgreSQL can provide a one-stop solution for you as KV store, VectorDB (pgvector) and GraphDB (apache AGE). PostgreSQL version 16.6 or higher is supported. For production level scenarios you will most likely want to leverage an enterprise solution. PostgreSQL can provide a one-stop solution for you as KV store, VectorDB (pgvector) and GraphDB (apache AGE). PostgreSQL version 16.6 or higher is supported.
* PostgreSQL is lightweight,the whole binary distribution including all necessary plugins can be zipped to 40MB: Ref to [Windows Release](https://github.com/ShanGor/apache-age-windows/releases/tag/PG17%2Fv1.5.0-rc0) as it is easy to install for Linux/Mac. * PostgreSQL is lightweight,the whole binary distribution including all necessary plugins can be zipped to 40MB: Ref to [Windows Release](https://github.com/ShanGor/apache-age-windows/releases/tag/PG17%2Fv1.5.0-rc0) as it is easy to install for Linux/Mac.
* If you prefer docker, please start with this image if you are a beginner to avoid hiccups (DO read the overview): https://hub.docker.com/r/shangor/postgres-for-rag * If you prefer docker, please start with this image if you are a beginner to avoid hiccups (Default user password:rag/rag): https://hub.docker.com/r/gzdaniel/postgres-for-rag
* How to start? Ref to: [examples/lightrag_zhipu_postgres_demo.py](https://github.com/HKUDS/LightRAG/blob/main/examples/lightrag_zhipu_postgres_demo.py) * How to start? Ref to: [examples/lightrag_zhipu_postgres_demo.py](https://github.com/HKUDS/LightRAG/blob/main/examples/lightrag_zhipu_postgres_demo.py)
* For high-performance graph database requirements, Neo4j is recommended as Apache AGE's performance is not as competitive. * For high-performance graph database requirements, Neo4j is recommended as Apache AGE's performance is not as competitive.