LanceDB and ClickHouse are two popular vector databases designed to efficiently store and query high-dimensional vectors, which encode complex information such as semantic meaning of text or product attributes. LanceDB is an open-source serverless vector database with a focus on AI applications, offering flexible indexing, scalability, and cost-effectiveness. It supports both exhaustive k-nearest neighbors (kNN) search and approximate nearest neighbor (ANN) search using an IVF_PQ index. ClickHouse, on the other hand, is an open-source column-oriented database that integrates vector search functionality through its SQL capabilities, allowing seamless combination with traditional filtering and aggregation. ClickHouse excels at handling large-scale datasets, offers high-speed parallelized processing, and supports robust security features. When choosing between LanceDB and ClickHouse, consider AI-first projects requiring efficient vector similarity search, hybrid capabilities, and developer-centric design (LanceDB), or analytics heavy workflows combining vector operations with traditional SQL queries on large datasets (ClickHouse). Thorough benchmarking with your own datasets and query patterns will be key to making a decision between these two powerful but different approaches.