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Intermediate10 min readData Storage & Databases

LSM Trees

Inside NoSQL: buffering write logs in MemTables and merging sequential files persistently via SSTables.

What you'll learn

  • Write-Ahead Logging (WAL)
  • Read Replicas & Sync Latency
  • Storage Partitioning (Sharding)

TL;DR

Inside NoSQL: buffering write logs in MemTables and merging sequential files persistently via SSTables.

Visual System Topology

LSM Trees Storage Partition Layout

Active Memory Pool RAM Buffer / MemTable
Metadata Hash Index B+ Tree Page Map
Persistent Disk Block SSTable / WAL Log

Concept Overview

LSM Trees is a core state-management component designed to guarantee transaction safety, coordinate replica consensus, and preserve structural durability under massive write loads. Inside NoSQL: buffering write logs in MemTables and merging sequential files persistently via SSTables.

Choosing and configuring database storage models represents one of the most complex tasks in system design. Engineers must balance consistency models against write availability bounds, partition tables to prevent storage exhaustion, and design replication failovers to withstand hardware crashes. Understanding LSM Trees allows architects to pick the correct engine (SQL vs. NoSQL, LSM vs. B-Tree) to back their active workloads.

Key Architectural Pillars

1

Write-Ahead Logging (WAL)

Writing all state modifications to an append-only log on disk before mutating actual database structures, securing crash durability.

Example: WAL records in transactional databases.
2

Read Replicas & Sync Latency

Decoupling read paths by distributing copy servers, introducing slight data propagation delays (eventual consistency).

3

Storage Partitioning (Sharding)

Splitting massive data tables into independent server shards based on a routing hash to avoid hardware storage walls.

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LSM Trees - Module 3: Data Storage & Databases | System Design | Revise Algo