Architecture

Vector Database

Definition

A specialised database designed to store and efficiently search high-dimensional embedding vectors using approximate nearest-neighbour algorithms. Vector databases are the infrastructure backbone of RAG systems and semantic search applications.

Examples

Pinecone
Weaviate
Milvus
pgvector

Related Terms

Embedding

A numerical representation of data (text, images, etc.) in a high-dimensional vector space where semantically similar items are mathematically close together. Embeddings are the foundational building block for semantic search, RAG pipelines, and recommendation systems.

Retrieval-Augmented Generation (RAG)

A technique that enhances LLM responses by retrieving relevant information from external knowledge sources before generating a response. RAG improves accuracy, reduces hallucinations, and enables LLMs to access up-to-date information without retraining.

Semantic Search

A search approach that retrieves results based on the meaning and intent of a query rather than exact keyword matches. Semantic search is powered by embeddings and vector databases, enabling far more relevant enterprise knowledge retrieval.

Related Services

Pilot To Production

Knowing the Terms Is Step One. Applying Them Is Step Two.

Book a discovery call to discuss how these AI concepts translate to your specific industry and business challenges.