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Intermediate10 min readData Storage & Databases

Object Storage

Highly scalable flat object spaces (Amazon S3) accessed via unique ID HTTP requests.

What you'll learn

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

TL;DR

Highly scalable flat object spaces (Amazon S3) accessed via unique ID HTTP requests.

Visual System Topology

Object Storage Storage Partition Layout

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

Concept Overview

Object Storage is a core state-management component designed to guarantee transaction safety, coordinate replica consensus, and preserve structural durability under massive write loads. Highly scalable flat object spaces (Amazon S3) accessed via unique ID HTTP requests.

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