Vector Databases

Vector databases, also known as similarity search engines or vector search engines, are a type of database designed to handle high-dimensional vector data. They enable efficient similarity search and storage of vector data, which is crucial in many machine learning and AI applications.

Mantium currently provides support for two popular vector databases; Redis and Pinecone

Redis

Redis is an open-source, in-memory data structure store that can be used as a database, cache, and message broker. It supports various types of data structures, including strings, hashes, lists, sets, and more.

The use of Redis is fully managed, meaning users don't require any setup to use it. This allows users to focus on their core tasks, making the process of document retrieval more efficient and user-friendly.

When a document is uploaded to Mantium, its vector representation is stored in Redis. When a user queries for a document, Mantium retrieves the most relevant documents from Redis based on their vector similarity. Users can also easily set up their data for use in the ChatGPT OpenAI Plugin with just a few clicks. This ease of setup, combined with the power of the vector database, makes Mantium a powerful tool for document retrieval and interaction with data within the ChatGPT interface.

Pinecone

Pinecone is a managed vector database service optimized for handling high-dimensional vector data, which is crucial for machine learning applications. It enables users to index vectors and perform efficient similarity searches, useful for tasks like recommendation systems and image searches. Mantium uses Pinecone to store vector representations of documents. After a document is uploaded to Mantium, it's preprocessed, transformed into a vector, and stored in Pinecone. This allows for quick and efficient retrieval of the most relevant documents based on vector similarity.

Mantium provides a seamless workflow to import data, generate embeddings for the text, and export them to Pinecone for further analysis or machine learning purposes.

Here is a guide on how to set up your Pinecone destination in Mantium.

Mantium's Use of Vector Databases

In the Mantium Plugin Wizard, users can easily set up their data for use in the ChatGPT OpenAI Plugin. Whether using Mantium's managed Redis or their own user-managed Pinecone vector database, the setup can be completed with just a few clicks. This ease of setup, combined with the power of vector databases, makes Mantium a powerful tool for document retrieval and interaction with data within the ChatGPT interface.

Mantium leverages the power of vector databases like Pinecone and Redis to provide efficient and fast document retrieval. By transforming documents into vector representations and storing them in these databases, Mantium can quickly retrieve the most relevant documents based on vector similarity. This is a significant improvement over traditional keyword-based search methods, which can be slow and less accurate.

Furthermore, Mantium abstracts away the complexities of setting up and managing these vector databases. Users simply upload their documents, and Mantium handles the rest – from preprocessing the documents, transforming them into vectors, storing them in the vector database, and retrieving them when needed. This allows users to focus on their core tasks, making the process of document retrieval more efficient and user-friendly.