LSM Trees

LSM Trees (Log-Structured Merge Trees) are a data structure and algorithm used in storage systems to optimize write-heavy workloads by batching writes into sequential, append-only logs and periodically merging them into sorted files. They are commonly implemented in modern NoSQL databases and key-value stores to achieve high write throughput and efficient disk usage. This design reduces random I/O operations, making it suitable for applications with frequent insertions and updates.

Also known as: Log-Structured Merge Trees, LSM-Tree, LSM, Log Structured Merge Tree, LSM Tree

Why learn LSM Trees?

Developers should learn about LSM Trees when building or working with systems that require high write performance, such as time-series databases, logging systems, or real-time analytics platforms. They are particularly useful in scenarios where data is written much more frequently than it is read, as they minimize disk seeks and leverage sequential writes. Understanding LSM Trees is essential for optimizing storage engines in databases like Apache Cassandra, RocksDB, or LevelDB.

Learning Resources

• docs: The Log-Structured Merge-Tree (LSM-Tree) - Original Paper
• tutorial: LSM-Tree Explained - Baeldung
• video: LSM Trees - System Design Interview
• book: Designing Data-Intensive Applications - Chapter 3
• docs: RocksDB Documentation - LSM-Based Storage