System Design

Learn System Design

How to Learn System Design?

Scalability

Availability

Latency and Performance

Concurrency and Coordination

Monitoring and Observability

Resilience and Error Handling

Fault Tolerance vs. High Availability

Flashcards Review

Chapter Assessment

HTTP vs. HTTPS

TCP vs. UDP

HTTP: 1.0 vs. 1.1 vs 2.0 vs. 3.0

URL vs. URI vs. URN

What Happens When You Type a URL into the Browser

Flashcards Review

Chapter Assessment

Introduction to Real-Time Communication

What is Long-Polling?

What is WebSocket?

What are Server-Sent Events?

Difference Between Long-Polling, WebSockets, and Server-Sent Events

Flashcards Review

Chapter Assessment

Introduction to DNS

DNS Resolution Process

DNS Load Balancing and High Availability

Flashcards Review

Chapter Assessment

What is a Proxy Server?

Uses of Proxies

VPN vs. Proxy Server

Flashcards Review

Chapter Assessment

Introduction to Load Balancing

Load Balancing Algorithms

Uses of Load Balancing

Load Balancer Types

Stateless vs. Stateful Load Balancing

High Availability and Fault Tolerance

Scalability and Performance

Challenges of Load Balancers

Flashcards Review

Chapter Assessment

Introduction to API Gateway

Usage of API gateway

Advantages and disadvantages of using API gateway

Flashcards Review

Chapter Assessment

What Is an API?

What Are REST APIs?

Resources, Not Actions

HTTP Methods and Their Semantics

URL Design

Request and Response Shapes

Status Codes and Error Design

Pagination from the Consumer's View

Idempotency Keys

Versioning and Backward Compatibility

Concurrency and Conditional Requests

REST vs gRPC vs GraphQL

Flashcards Review

Chapter Assessment

What Is Rate Limiting

Rate Limiting Algorithms

Distributed Rate Limiting

Rate Limiting in Practice

Flashcards Review

Chapter Assessment

Introduction to Caching

Why is Caching Important?

Types of Caching

Cache Replacement Policies

Cache Invalidation

Cache Read Strategies

Cache Coherence and Consistency Models

Caching Challenges

Cache Performance Metrics

Flashcards Review

Chapter Assessment

What is CDN?

Origin Server vs. Edge Server

CDN Architecture

Push CDN vs. Pull CDN

Flashcards Review

Chapter Assessment

Introduction to Data Partitioning

Partitioning Methods

Data Sharding Techniques

Benefits of Data Partitioning

Common Problems Associated with Data Partitioning

Flashcards Review

Chapter Assessment

What is Redundancy?

What is Replication?

Replication Methods

Data Backup vs. Disaster Recovery

Flashcards Review

Chapter Assessment

Introduction to CAP Theorem

Components of CAP Theorem

Trade-offs in CAP Theorem

Examples of CAP Theorem in Practice

Beyond CAP Theorem

System Design Trade-offs in Interviews

Flashcards Review

Chapter Assessment

Introduction to Databases

SQL Databases

NoSQL Databases

SQL vs. NoSQL

ACID vs BASE Properties

Real-World Examples and Case Studies

SQL Normalization and Denormalization

In-Memory Database vs. On-Disk Database

Data Replication vs. Data Mirroring

Database Federation

Flashcards Review

Chapter Assessment

What are Indexes?

How a B-Tree Index Works

Types of Indexes

B-Tree vs. LSM Tree

Indexes in Distributed Systems

Flashcards Review

Chapter Assessment

Introduction to Bloom Filters

Benefits & Limitations of Bloom Filters

Variants and Extensions of Bloom Filters

Applications of Bloom Filters

Flashcards Review

Chapter Assessment

Why Quorum?

What is Quorum?

Flashcards Review

Chapter Assessment

What is Leader and Follower Pattern?

Flashcards Review

Chapter Assessment

What is Heartbeat?

Flashcards Review

Chapter Assessment

What is Checksum?

Uses of Checksum

Flashcards Review

Chapter Assessment

Distributed Messaging System

Introduction to Messaging System

Introduction to Kafka

Messaging patterns

Popular Messaging Queue Systems

RabbitMQ vs. Kafka vs. ActiveMQ

Scalability and Performance

Flashcards Review

Chapter Assessment

What is a Distributed File System?

Architecture of a Distributed File System

Key Components of a DFS

Flashcards Review

Chapter Assessment

What is Security and Privacy?

What is Authentication?

What is Authorization?

Authentication vs. Authorization

OAuth vs. JWT for Authentication

What is Encryption?

What are DDoS Attacks?

Flashcards Review

Chapter Assessment

Batch Processing vs. Stream Processing

XML vs. JSON

Synchronous vs. Asynchronous Communication

Push vs. Pull Notification Systems

Microservices vs. Serverless Architecture

Message Queues vs. Service Bus

Stateful vs. Stateless Architecture

Event-Driven vs. Polling Architecture

Flashcards Review

Chapter Assessment

Quiz

Importance of Discussing Trade-offs

Strong vs Eventual Consistency

Latency vs Throughput

ACID vs BASE Properties in Databases

Read-Through vs Write-Through Cache

Batch Processing vs Stream Processing

Load Balancer vs. API Gateway

API Gateway vs Direct Service Exposure

Proxy vs. Reverse Proxy

API Gateway vs. Reverse Proxy

SQL vs. NoSQL

Primary-Replica vs Peer-to-Peer Replication

Data Compression vs Data Deduplication

Server-Side Caching vs Client-Side Caching

REST vs RPC

Polling vs. Long-Polling vs. WebSockets vs. Webhooks

CDN Usage vs Direct Server Serving

Serverless Architecture vs Traditional Server-based

Stateful vs Stateless Architecture

Hybrid Cloud Storage vs All-Cloud Storage

Token Bucket vs Leaky Bucket

Read Heavy vs Write Heavy System

Quiz

System Design Interviews - A step by step guide

Functional vs. Non-functional Requirements

What are Back-of-the-Envelope Estimations?

Things to Avoid During System Design Interview

System Design Master Template

Quiz

Designing a URL Shortening Service like TinyURL

Quiz - Designing URL Shortner

Designing Pastebin

Quiz - Designing Pastebin

Designing Instagram

Quiz - Designing Instagram

Designing Dropbox

Quiz - Designing Dropbox

Designing Facebook Messenger

Quiz - Designing Facebook Messenger

Designing Twitter

Quiz - Designing Twitter

Designing Youtube or Netflix

Quiz - Designing Youtube

Designing Typeahead Suggestion

Quiz - Designing Typeahead Suggestion

Designing an API Rate Limiter

Quiz - Designing an API Rate Limiter

Designing Twitter Search

Quiz - Designing Twitter Search

Designing a Web Crawler

Quiz - Designing a Web Crawler

Designing Facebook’s Newsfeed

Quiz - Designing Facebook’s Newsfeed

Designing Yelp or Nearby Friends

Quiz - Designing Yelp or Nearby Friends

Designing Uber backend

Quiz - Designing Uber backend

Designing Ticketmaster

Quiz - Designing Ticketmaster

Dynamo: Introduction

High-Level Architecture

Data Partitioning

Replication

Vector Clocks and Conflicting Data

The Life of Dynamo’s put() & get() Operations

Anti-entropy Through Merkle Trees

Gossip Protocol

Dynamo Characteristics and Criticism

Summary: Dynamo

Quiz: Dynamo

Mock Interview: Dynamo

YouTube Likes Counter

Quiz

Cassandra: Introduction

High-level Architecture

Replication

Cassandra Consistency Levels

Gossiper

Anatomy of Cassandra's Write Operation

Anatomy of Cassandra's Read Operation

Compaction

Tombstones

Summary: Cassandra

Quiz: Cassandra

Mock Interview: Cassandra

Messaging Systems: Introduction

Kafka: Introduction

High-level Architecture

Kafka: Deep Dive

Consumer Groups

Kafka Workflow

Role of ZooKeeper

Controller Broker

Kafka Delivery Semantics

Kafka Characteristics

Summary: Kafka

Quiz: Kafka

Mock Interview: Kafka

Chubby: Introduction

High-level Architecture

Design Rationale

How Chubby Works

File, Directories, and Handles

Locks, Sequencers, and Lock-delays

Sessions and Events

Master Election and Chubby Events

Caching

Database

Scaling Chubby

Summary: Chubby

Quiz: Chubby

Mock Interview: Chubby

Hadoop Distributed File System: Introduction

High-level Architecture

Deep Dive

Anatomy of a Read Operation

Anatomy of a Write Operation

Data Integrity & Caching

Fault Tolerance

HDFS High Availability (HA)

HDFS Characteristics

Summary: HDFS

Quiz: HDFS

Mock Interview: HDFS

Google File System: Introduction

High-level Architecture

Single Master and Large Chunk Size

Metadata

Master Operations

Anatomy of a Read Operation

Anatomy of a Write Operation

Anatomy of an Append Operation

GFS Consistency Model and Snapshotting

Fault Tolerance, High Availability, and Data Integrity

Garbage Collection

Criticism on GFS

Summary: GFS

Quiz: GFS

Mock Interview: GFS

BigTable: Introduction

BigTable Data Model

System APIs

Partitioning and High-level Architecture

SSTable

GFS and Chubby

Bigtable Components

Working with Tablets

The Life of BigTable's Read & Write Operations

Fault Tolerance and Compaction

BigTable Refinements

BigTable Characteristics

Summary: BigTable

Quiz: BigTable

Mock Interview: BigTable

Design Reddit

Quiz

Designing a Notification System

Quiz

Design Google calendar (Medium)

Quiz

Design a Recommendation System for Netflix

Quiz

Design Gmail

Quiz

Design Google News, a Global News Aggregator System (Medium)

Quiz

Design Unique ID Generator (Easy)

Quiz

Design Code Judging System like LeetCode (Medium)

Quiz

Design Payment System

Quiz

Design a Flash Sale for an E-commerce Site (Hard)

Quiz

Design a Reminder Alert System

Quiz

Introduction: System Design Patterns

1. Bloom Filters

2. Consistent Hashing

3. Quorum

4. Leader and Follower

5. Write-ahead Log

6. Segmented Log

7. High-Water Mark

8. Lease

9. Heartbeat

10. Gossip Protocol

11. Phi Accrual Failure Detection

12. Split Brain

13. Fencing

14. Checksum

15. Vector Clocks

16. CAP Theorem

17. PACELC Theorem

18. Hinted Handoff

19. Read Repair

20. Merkle Trees

Quiz

RabbitMQ vs. Kafka vs. ActiveMQ

RabbitMQ vs. Kafka vs. ActiveMQ

distributed systems

message queues

messaging patterns

asynchronous communication

+3

hard
·
5 min
·Updated Aug 2026·Credit: System Design Fundamentals

RabbitMQ, Kafka, and ActiveMQ are the three message brokers you will hear about most often. All three move messages between producers and consumers, but they are built on very different ideas. Here is each one in a single sentence:

  • RabbitMQ: a smart broker that routes each message through exchanges into queues, and deletes the message once a consumer acknowledges it.
  • Kafka: a distributed append-only log that keeps messages after delivery, so consumers pull at their own pace and can replay history.
  • ActiveMQ: a classic JMS broker (JMS is the standard Java messaging API) that offers both queues and topics and speaks many protocols.
Image
The three brokers side by side: RabbitMQ routes through exchanges, Kafka appends to a replayable log, and ActiveMQ serves JMS queues and topics

Key Differences

DimensionRabbitMQKafkaActiveMQ
ArchitectureSmart broker, dumb consumer. Routes via exchanges and queues.Distributed commit log. Dumb broker, smart consumer.Classic JMS broker with queues and topics.
Built onErlangScala and Java (JVM)Java (JVM)
Message modelQueue based. Exchanges route to queues.Append only log. Topics split into partitions.JMS queues (point to point) and topics (pub/sub).
Protocol supportAMQP 0.9.1, MQTT, STOMP, HTTPCustom Kafka binary protocol over TCPOpenWire, AMQP, MQTT, STOMP, JMS
ThroughputTens of thousands of messages per second per node.Millions of messages per second across a cluster.Tens of thousands per second. Artemis scales higher.
LatencyVery low. Microseconds to low milliseconds.Low. Optimized for throughput over latency.Low milliseconds.
Message retentionDeleted once acknowledged.Kept for a configurable time or size, even after consumption.Deleted once acknowledged.
ReplayNot natively supported.First class. Consumers reset offsets to replay.Limited. Some support via message stores.
OrderingPer queue, with single consumer.Strict per partition.Per queue. Message groups for finer control.
Consumer modelPush based. Broker delivers to consumers.Pull based. Consumers fetch at their own pace.Push based. Pull also supported.
RoutingRich. Direct, topic, fanout, headers exchanges.Minimal. Partition key on producer side.Selectors, virtual topics, composite destinations.
ScalabilityVertical first. Clustering and quorum queues for HA.Horizontal. Built for distributed scale.Vertical first. Network of brokers for federation.
Delivery guaranteesAt most once, at least once.At most once, at least once, exactly once with transactions.At most once, at least once, exactly once.
Best forTask queues, RPC, complex routing, microservice messaging.Event streaming, log aggregation, analytics pipelines, event sourcing.Enterprise integration, legacy JMS apps, hybrid messaging.
Weak spotSlows when queues grow very large.Heavier ops. Overkill for simple task queues.Lower throughput than Kafka. Less momentum than RabbitMQ.

One term in the table deserves a quick definition. A consumer's current position in a Kafka log is called its offset. Resetting the offset moves the consumer back in the log, so it can read old messages again.

How to Choose

Ask three questions, in order:

  1. Do you need to replay events, keep history, or stream huge volumes of data? If yes, use Kafka. Its append-only log keeps messages after delivery, and nothing else matches its throughput at scale.
  2. Do you need flexible per-message routing or classic task queues? If yes, use RabbitMQ. Its exchanges route messages by rules, and its latency is excellent for job dispatch and RPC.
  3. Are you integrating with enterprise Java or existing JMS applications? Use ActiveMQ. It speaks JMS natively and fits legacy enterprise stacks with the least friction.
Image
Choosing a broker: replay and streaming point to Kafka, routing and task queues point to RabbitMQ, and JMS integration points to ActiveMQ

💡 In a system design interview, do not just name a broker. Tie it to the workload. "Click events must be stored and replayable for analytics, so I would pick Kafka." Or: "Order processing needs per-task routing with retries and low latency, so RabbitMQ fits better." Naming the trade-off is what earns the credit.

Quick Reference

  • RabbitMQ

    • Model: smart broker routes messages through exchanges into queues
    • Retention: message deleted once acknowledged
    • Delivery: push based, very low latency
    • Use it for: task queues, RPC, complex routing, microservice messaging
  • Kafka

    • Model: append-only log, topics split into partitions
    • Retention: messages kept for a configured time or size, replay supported
    • Delivery: pull based, built for massive throughput
    • Use it for: event streaming, log aggregation, analytics pipelines, event sourcing
  • ActiveMQ

    • Model: JMS queues and topics in one broker
    • Retention: message deleted once acknowledged
    • Delivery: push based, pull also supported
    • Use it for: enterprise integration and legacy JMS applications

Conclusion

A quick way to remember it: RabbitMQ is the smart router for traditional messaging, Kafka is the durable log built for streaming and replay, and ActiveMQ is the JMS workhorse for enterprise Java systems. Whichever you pick, it still has to grow with your traffic. The final lesson, Scalability and Performance, shows the techniques that make that possible.

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