benja1972 / vectordb

Vector databases experimentation for the Knowledge Graphs and sentenceBERT embedding

Vector Databases experiments

Overview

List of vectorstores

We will experiment with two databases

Chroma

Chroma is the open-source embedding database. Chroma makes it easy to build LLM apps by making knowledge, facts, and skills pluggable for LLMs. Chroma gives you the tools to:

• store embeddings and their metadata
• embed documents and queries
• search embeddings

Chroma prioritizes:

• simplicity and developer productivity
• analysis on top of search
• it also happens to be very quick

Qdrant

Qdrant is powering the next generation of AI applications with advanced and high-performant vector similarity search technology.

Qdrant is a vector database & vector similarity search engine. 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!

• Easy to Use API. Provides the OpenAPI v3 specification to generate a client library in almost any programming language. Alternatively utilize ready-made client for Python or other programming languages with additional functionality.
• Fast and Accurate. Implement a unique custom modification of the HNSW algorithm for Approximate Nearest Neighbor Search. Search with a State-of-the-Art speed and apply search filters without compromising on results.
• Filtrable. Support additional payload associated with vectors. Not only stores payload but also allows filter results based on payload values. Unlike Elasticsearch post-filtering, Qdrant guarantees all relevant vectors are retrieved.

Use-cases

• Chroma DB for taxonomy embedding
• Chroma DB for Matching KG
• Qdrant DB for Matching KG