In the world of semantic search and retrieval-augmented generation (RAG), vector databases play a crucial role that often goes unnoticed. If you’re exploring applications like large language models or semantic search platforms, choosing the right vector database is essential. To simplify the decision-making process, this article compares the leading vector databases of 2023, including Pinecone, Weviate, Milvus, Qdrant, Chroma, Elasticsearch, and PGvector. The comparison covers various aspects such as open-source availability, self-hosting options, cloud management, developer experience, community strength, performance, scalability, security features, and pricing. Each database has its strengths and weaknesses, so the ideal choice depends on specific project needs and constraints.
https://benchmark.vectorview.ai/vectordbs.html