LanceDB is a columnar vector database optimized for real-time AI use cases and analytics workloads, providing efficient vector storage and fast similarity search.
ClickHouse is an open-source column-oriented database that supports vectorized computation and now offers vector search features. Its architecture enables efficient real-time analytics and vector operations, making it a relevant choice for vector database use cases.
KDB.AI is a proprietary vector database and search engine designed for real-time AI applications. It offers advanced vector search, integrates with popular ML tools, and supports temporal and semantic context for embeddings. KDB.AI Server is a high-performance vector database and search engine from KX, designed for real-time analytics and AI applications requiring rapid similarity search.
SingleStore (also known as SingleStoreDB) is a real-time data platform offering integrated vector search capabilities for building intelligent applications with high-throughput requirements. It is a relational database platform with built-in support for vector search, enabling high-performance similarity queries alongside structured SQL-based analytics.
AstraDB (also known as Astra DB by DataStax) is a cloud-native vector database built on Apache Cassandra, supporting real-time AI applications with scalable vector search. It is designed for large-scale deployments and features a user-friendly Data API, robust vector capabilities, and automation for AI-powered applications.
Deep Lake is a vector database designed as a data lake for AI, capable of storing and managing vector embeddings, text, images, and videos. It utilizes a tensor format for efficient querying and integration with AI algorithms, making it suitable for similarity search and machine learning workflows. It is open-source and tailored for handling unstructured and multimodal data, with seamless integration with frameworks like PyTorch and TensorFlow.
LanceDB is an open source, developer-friendly columnar vector database optimized for real-time AI use cases and analytics workloads. It is designed to efficiently store vectors and provide fast similarity search, making it suitable for multimodal AI applications.