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.
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What are some alternatives to Pg_vectorize?
The MySQL software delivers a very fast, multi-threaded, multi-user, and robust SQL (Structured Query Language) database server. MySQL Server is intended for mission-critical, heavy-load production systems as well as for embedding into mass-deployed software.
PostgreSQL is an advanced object-relational database management system that supports an extended subset of the SQL standard, including transactions, foreign keys, subqueries, triggers, user-defined types and functions.
MongoDB stores data in JSON-like documents that can vary in structure, offering a dynamic, flexible schema. MongoDB was also designed for high availability and scalability, with built-in replication and auto-sharding.
Microsoft® SQL Server is a database management and analysis system for e-commerce, line-of-business, and data warehousing solutions.
Sentence Transformers, OpenAI, Docker, PostgreSQL are some of the popular tools that integrate with Pg_vectorize. Here's a list of all 4 tools that integrate with Pg_vectorize.