The Excellence
Directory Platform Template

The Kafka Connect Milvus Connector is a plugin for Kafka Connect that streams data into and out of Milvus, supporting real-time vector data ingestion pipelines.

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.

LanceDB is a columnar vector database optimized for real-time AI use cases and analytics workloads, providing efficient vector storage and fast similarity search.

Milvus CDC (Change Data Capture) is a component of the Milvus ecosystem that enables data synchronization between Milvus and other systems. It is useful for maintaining up-to-date vector data pipelines and supporting real-time vector search applications.

Redis, while primarily an in-memory data store, offers vector search capabilities through its RediSearch and RedisAI modules, enabling vector similarity searches and deep learning model management for existing Redis users. With the RediSearch module, Redis extends its functionality to support native vector search, indexing, and hybrid queries, making it suitable for real-time AI and semantic search applications.

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.

Vald is an open-source, highly scalable distributed vector search engine known for its asynchronous auto-indexing and ability to efficiently handle large-scale vector data in real time, making it suitable for demanding vector search applications.

Vectorflow is a vector database optimized for real-time vector indexing and search in distributed environments, suitable for AI and machine learning use cases.

Vespa.ai is a scalable open-source platform for real-time big data serving and vector search. It supports vector similarity search and is used for applications like retrieval augmented generation and e-commerce search, making it highly relevant for vector database and vector search use cases.

A multi-model AI database designed for high-throughput vector processing at scale, supporting real-time AI use cases with a patented Hybrid Memory Architecture and efficient infrastructure usage, capable of handling large volumes of data and concurrent users.

Online Product Quantization (O-PQ) is a variant of product quantization designed to support dynamic or streaming data. It enables adaptive updating of quantization codebooks and codes in real-time, making it suitable for vector databases that handle evolving datasets.