This notebook guides you step by step on using PolarDB-PG as a vector database for OpenAI embeddings.
This notebook presents an end-to-end process of:
- Using precomputed embeddings created by OpenAI API.
- Storing the embeddings in a cloud instance of PolarDB-PG.
- Converting raw text query to an embedding with OpenAI API.
- Using PolarDB-PG to perform the nearest neighbour search in the created collection.
PolarDB-PG is a high-performance vector database that adopts a read-write separation architecture. It is a cloud-native database managed by Alibaba Cloud, 100% compatible with PostgreSQL, and highly compatible with Oracle syntax. It supports processing massive vector data storage and queries, and greatly improves the efficiency of vector calculations through optimization of underlying execution algorithms, providing users with fast, elastic, high-performance, massive storage, and secure and reliable vector database services. Additionally, PolarDB-PG also supports multi-dimensional and multi-modal spatiotemporal information engines and geographic information engines.At the same time, PolarDB-PG is equipped with complete OLAP functionality and service level agreements, which has been recognized and used by many users;