What’s the Difference Between a Distributed System and a Parallel System?

In modern system development you’ll run into two similar but not identical concepts: a distributed system and a parallel system. Both describe a situation where “several things work at the same time,” but they do so for different reasons, in different ways, and at different levels of complexity.

To understand the difference - it’s enough to understand the essence of each.

Parallel System - Several Tasks Running Together on the Same Machine

A Parallel System uses several cores or several threads on the same computer to perform tasks in parallel.

For example:

• Image processing across several cores
• Running an algorithm that splits work between several threads
• A GPU performing many computations in parallel

The key characteristic: everything happens on one piece of hardware, in shared memory.

Why Is This Good?

• Faster execution of heavy computations
• Utilizing the resources of a single machine
• Relatively simple coordination (since everything is on the same computer)

An Analogy

Think of a single chef in a kitchen - they can perform different tasks: chopping, mixing, and sautéing in parallel. But they’re still one person in that same kitchen.

Distributed System - Several Components Working Together in Different Places

In a Distributed System, there are several different computers, each with its own memory, its own communication, its own role - and they need to communicate to form one complete system.

For example:

• A web service spread across several servers
• A cloud system
• A distributed database
• A chain of services each running on a different machine

The key characteristic: the components don’t sit together - they must communicate.

Why Is This Good?

• Can grow by tens or hundreds of times
• No single point of failure
• Load can be spread out
• Suitable for services with millions of users

An Analogy

Think of a huge restaurant with many different workers: chef, waiter, host, delivery, management… Each does a different part - and together they form one system.

The Common Mistake: “If Several Things Run in Parallel - It’s Distributed”

Not true.

Key difference:

Characteristic	Parallel System	Distributed System
How many computers?	One computer	Several computers
Memory	Shared	Separate
Communication	Internal, high-speed	Over a network, relatively slow
Design difficulty	Moderate	High (failures, message ordering, sync, consistency)
Goal	Computational speedup	Growth, reliability, division of roles

In short: Parallel = performance Distributed = architecture

An Example That Sums It All Up

Suppose we have a heavy task: processing thousands of images.

Parallel system: One computer, 8 cores. The task is split between the cores - each core processes part of the images.

Distributed system: 20 different computers, each processing part of the images. You need to:

• Send them the images
• Collect the results
• Handle out-of-order arrivals
• Withstand failures
• Merge everything back together

Parallel system = internal division within a computer. Distributed system = external division between different computers.

When Do You Use Which?

Parallel System - When You Need to “Do It Faster”

• Image processing
• Machine learning
• Simulations
• Heavy mathematics

Distributed System - When You Need to “Operate at Scale and Survive Failures”

• Cloud
• Web systems
• Services with many users
• Large databases
• Real-time systems

Summary

Both systems deal with “multiplicity” - but each solves a different problem:

• A parallel system solves problems of speed.
• A distributed system solves problems of scale, reliability, and organization.

And when building a truly large system - sometimes both are used together:

• Every computer in a distributed system → works in a parallel way
• And many computers working together → a distributed system