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Advanced Topic 48 of 51 Databases

LSM Trees

Write-optimized structures merging sorted runs.

How it works

A log-structured merge tree optimizes write throughput by buffering writes in an in-memory sorted table, the memtable, and an append-only write-ahead log. When the memtable fills, it is flushed to disk as an immutable sorted file; background compaction merges files into larger sorted runs across levels. Reads check the memtable and then files from newest to oldest, using Bloom filters and indexes to skip files.

Where it is used

RocksDB, LevelDB, Cassandra, HBase, ScyllaDB and InfluxDB use LSM trees, which suit write-heavy workloads and make good use of sequential disk and SSD writes.

Common pitfall

Reads can be slower than in B-trees because several files may be checked, and compaction causes write amplification and background I/O spikes. Deletes use tombstones that linger until compaction. Tune compaction strategy, bloom filters and memory sizes for your workload, and monitor space and read amplification.

Where it fits in the course

LSM Trees is topic 48 of 51 in Databases, rated Advanced. It follows OLTP vs OLAP. The next topic is NewSQL and Distributed SQL.

Practice and explore

How to study this topic

  1. Read the explanation above and restate the definition in your own words.
  2. Open the interactive lesson and answer its mini quiz.
  3. Read the common pitfall, then write a short example that avoids it.
  4. Check your understanding in the Databases quiz, and revisit the topic if you miss a question.

Frequently asked questions

What is LSM Trees?
Write-optimized structures merging sorted runs. It belongs to Databases and is an advanced-level topic.
Where do people use LSM Trees?
RocksDB, LevelDB, Cassandra, HBase, ScyllaDB and InfluxDB use LSM trees, which suit write-heavy workloads and make good use of sequential disk and SSD writes.
What is the most common mistake with LSM Trees?
Reads can be slower than in B-trees because several files may be checked, and compaction causes write amplification and background I/O spikes.
What should I learn before this topic?
Start with OLTP vs OLAP, the topic just before it in Databases.
How can I practice it?
Answer the mini quiz in the interactive lesson, then take the Databases quiz. You can also explore Binary Search Tree in the Visual Lab.
Is LSM Trees hard to learn?
It is an Advanced topic. Expect to read the explanation more than once and to connect it with earlier topics. Working through a small example by hand helps most.
How long does it take to learn LSM Trees?
Most learners can read the explanation and finish the interactive lesson in under an hour. Fluency comes from applying the idea, so plan a few short practice sessions with the quiz.
Which topics are related to LSM Trees?
OLTP vs OLAP, NewSQL and Distributed SQL, Data Warehousing are closely connected. The full list is in the related topics section of this page.
What should I study after LSM Trees?
Continue with NewSQL and Distributed SQL, the next topic in Databases.

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