ClickHouse's new CoalescingMergeTree table engine, introduced in version 25.6, is designed to efficiently consolidate sparse updates, making it ideal for scenarios where data is incrementally updated, such as IoT device telemetry. Unlike traditional methods that require full row overwrites, CoalescingMergeTree gradually merges sparse records over time, preserving the most recent non-null values for each entity without sacrificing data fidelity. This approach is particularly beneficial in high-throughput environments, where it reduces data redundancy and improves query performance by pre-aggregating data on disk. The engine is optimized for append-only models, making it well-suited for handling fragmented updates from multiple subsystems, such as those found in modern connected vehicles. It offers a more efficient alternative to frequent single-row updates by allowing background merges to handle data consolidation, significantly reducing the number of rows and data scanned during queries. CoalescingMergeTree can also be applied in various other contexts, including user profile enrichment and security audit trails, where it helps reduce storage costs and query latency while maintaining data completeness.