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 Vector Databases category of a tech stack.
Pg_vectorize is an open source tool with GitHub stars and GitHub forks. Here’s a link to Pg_vectorize's open source repository on GitHub
Pg_vectorize Integrations
Pg_vectorize's Features
- Workflows for both vector search and RAG
- Integrations with OpenAI's embeddings
- Automated creation of Postgres triggers to keep your embeddings up to date
Pg_vectorize Alternatives & Comparisons
What are some alternatives to Pg_vectorize?
MySQL
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
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
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.
Redis
Redis is an open source (BSD licensed), in-memory data structure store, used as a database, cache, and message broker. Redis provides data structures such as strings, hashes, lists, sets, sorted sets with range queries, bitmaps, hyperloglogs, geospatial indexes, and streams.
Amazon S3
Amazon Simple Storage Service provides a fully redundant data storage infrastructure for storing and retrieving any amount of data, at any time, from anywhere on the web
Related Comparisons
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