Qdrant and ClickHouse are both vector databases designed to store and query high-dimensional vectors, which are numerical representations of unstructured data. They play a crucial role in AI applications, allowing for more advanced data analysis and retrieval. While Qdrant is a purpose-built vector database, ClickHouse is an open-source column-oriented database with vector search capabilities as an add-on. Qdrant excels in performance optimization and can work with high-dimensional vector data, making it a top choice for developers working on AI-driven projects. It offers flexible data modeling, rich query options, and features like automatic sharding and replication to help users scale as their data and query load grow. ClickHouse is great for vector search when you need to combine vector matching with metadata filtering or aggregation, especially for very large vector datasets that need parallel processing and when you combine vector search with SQL-based filtering and aggregation. Both systems have different approaches to vector search and serve different needs. Qdrant is a specialized vector database with optimized search algorithms and full vector operations, perfect for dedicated vector search applications. ClickHouse is a powerful analytical database that brings vector search into the SQL world, great for combining vector operations with broader data analytics. Choose what fits your use case, data volume, search requirements, existing infrastructure, and team expertise.