Pg_vectorize
What is Pg_vectorize?
It is a Postgres extension that automates the transformation and orchestration of text to embeddings and provides hooks into the most popular LLMs. This allows you to do vector search and build LLM applications on existing data with as little as two function calls.
Pg_vectorize is a tool in the Databases category of a tech stack.
Key Features
Workflows for both vector search and RAGIntegrations with OpenAI's embeddingsAutomated creation of Postgres triggers to keep your embeddings up to date
Pg_vectorize Pros & Cons
Pros of Pg_vectorize
No pros listed yet.
Cons of Pg_vectorize
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Pg_vectorize Alternatives & Comparisons
What are some alternatives to Pg_vectorize?
Milvus
Milvus is an open source vector database. Built with heterogeneous computing architecture for the best cost efficiency. Searches over billion-scale vectors take only milliseconds with minimum computing resources.
Chroma
It is an open-source embedding database. Chroma makes it easy to build LLM apps by making knowledge, facts, and skills pluggable for LLMs.
Qdrant
It is an open-source Vector Search Engine and Vector Database written in Rust. It deploys as an API service providing search for the nearest high-dimensional vectors. With Qdrant, embeddings or neural network encoders can be turned into full-fledged applications for matching, searching, recommending, and much more.
