😎Selection of vector databases
Vector databases are a special type of database designed to organize data based on similarity. To do this, they transform raw data—such as images, text, video, or audio—into mathematical representations known as multidimensional vectors. Each vector can have from tens to thousands of dimensions, depending on the complexity of the source data. At the moment there are such vector databases as:
Chroma is an open source vector database designed to provide developers and organizations of all sizes with the resources they need to build Large Language Model (LLM) based applications. It provides developers with a highly scalable and efficient solution for storing, searching, and retrieving multidimensional vectors.
One of the reasons for Chroma's popularity is its flexibility.
Pinecone - This is a cloud-based managed vector database. Its broad support for high-dimensional vectors makes Pinecone suitable for a variety of use cases, including similarity search, recommender systems, personalization, and semantic search. It also supports single-stage filtering capabilities. And its ability to analyze data in real time makes it an excellent choice for detecting threats and monitoring cybersecurity attacks.
Weviate - A notable feature of this database is that it can be used to store both vectors and objects. This makes it suitable for applications that combine multiple search methods, such as vector search and keyword search.
Milvus - uses the most modern algorithms to speed up the search process, which allows you to quickly find similar vectors even when working with large amounts of data.