Vector databases have been getting a lot of attention since the developer community realized how they can enhance large language models (LLMs). Weaviate is an open source vector database that enables modern search capabilities, such as vector search, hybrid search, and generative search. With Weaviate, you can build advanced LLM applications, next-level search systems, recommendation systems, and more.
This article explains what vector databases are and highlights key features of the Weaviate vector database. Learn how to install Weaviate on Docker using Docker Compose so you can take advantage of semantic search within your Dockerized environment.
Introducing the Weaviate vector database
The core feature of vector databases is storing vector embeddings of data objects. This functionality is especially helpful with the growing amount of unstructured data (e.g., text or images), which is difficult to manage and process with traditional relational…
