ClickHouse has become "lazier" with the introduction of lazy materialization, which defers reading column data until needed, resulting in faster queries. The new feature is accompanied by CPU slot scheduling and improved quality-of-life updates. Microsoft Clarity chose ClickHouse as a solution for its free analytics tool due to its scalability and performance issues with the original Elasticsearch and Spark setup. AgentHouse, a chat-based demo environment, allows users to interact with ClickHouse datasets using natural language processing. CloudQuery solved the problem of handling large batches of data in ClickHouse by developing an "Insert-Splitter" algorithm that breaks up inserts into smaller chunks based on UUID ranges. The MySQL CDC connector for ClickHouse is now available in private preview. Bootstrapping statistical algorithms with ClickHouse led to a successful trial-and-error process using native functions and Python user-defined functions. Vimeo built a sophisticated retention analytics system using ClickHouse, tracking viewing patterns by recording changes and using window functions to calculate cumulative views at each second. The company also developed an AI-powered insights layer to generate concise, actionable insights about viewer engagement patterns. Various videos were shared on topics such as adopting ClickHouse for test analytics, observability challenges and solutions, Model Context Protocol, backfilling materialized views, querying Apache Iceberg tables via AWS Glue catalog, and explaining ClickHouse's JSON data type.