// MODEL OPTIMIZATION AND PROMPT SYNTAX TERM
Vector Database
A specialized database designed to store and quickly search through 'vector embeddings,' which are numerical representations of data like text or images.
TECHNICAL DEFINITION
A specialized database optimized for storing, managing, and querying high-dimensional vector embeddings, enabling efficient similarity search (e.g., nearest neighbor search) for applications like semantic search, recommendation systems, and RAG architectures.
BACKGROUND
Prompt engineering is the process of structuring natural language inputs to produce specified outputs from a generative artificial intelligence (GenAI) model. Context engineering is the related area of software engineering that focuses on the management of non-prompt contexts supplied to the GenAI model, such as metadata, API tools, and tokens.
READ MORE ON WIKIPEDIASYNONYMS & ALIASES
- Vector store
- embedding database
- similarity search database
USAGE NOTE
Vector databases are crucial for Retrieval-Augmented Generation (RAG) systems to find relevant context.
DEVELOPERS
Organizations developing technology related to Vector Database.
A managed vector database designed for high-performance similarity search, commonly used in AI applications like recommendation systems and semantic search.
An open-source vector database that allows users to store data objects and vector embeddings and perform vector similarity search, with a GraphQL API.
An open-source vector similarity search engine and vector database, providing a production-ready service with a convenient API to store, search, and manage points with custom payloads and vectors.
Zilliz is the company behind Milvus, an open-source vector database built for scalable similarity search and AI applications, handling massive-scale vector datasets.
An open-source embedding database that makes it easy to build LLM applications by providing a simple API to store and query embeddings.
The company behind Elasticsearch, which provides robust vector search capabilities within its distributed search and analytics engine, enabling semantic search and similarity matching.
The company behind Redis, whose Redis Stack includes RedisSearch, offering vector similarity search functionality for real-time AI applications and low-latency use cases.
Provides Astra DB, a cloud-native database built on Apache Cassandra, that integrates vector search capabilities, enabling developers to build generative AI applications with highly scalable and performant vector search.
Offers MongoDB Atlas Vector Search, integrating vector search directly into its NoSQL database platform, allowing developers to combine structured and unstructured data with embeddings for AI applications.