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Docker vs Virtual Machine
Updated on 02nd Jun, 23 695 Views

Today, both Docker and Virtual Machines play an important role in helping drive a lot of businesses to success. Many companies have been seen to invest billions of dollars into finding the right containerization tool and virtual machine to make use for their benefit. And, this makes it important to understand what goes on in the comparison between VM vs Docker.

On this Docker vs Virtual Machine blog, we will be taking a look at the following aspects:

Also, make sure to check out the Docker vs Virtual Machine video on our YouTube channel:

What is Docker?

The majority of companies today have a diverse portfolio of cloud-based infrastructures, applications, and even local networks that can cause delays and ruptures in the smooth-flowing data pipelines in the organization.

Docker can easily solve all of these problems as it is a container platform that has the ability to bring about a secure and autonomous supply chain into the daily-used applications and microservices. This can be done across a variety of operating systems, be it Windows, Linux, or any other mainframe machine.

As a product of virtualization technology, Docker makes it very easy to create, manage, and deploy applications by making use of containers. What are the containers? Containers are the pieces of software that are extremely lightweight, stand-alone, and have all of the libraries and other built-in files needed to execute an application.

No matter which machine the application runs on, it runs as if it is a constantly isolated platform irrespective of any dependencies to the local operating system.

One important thing about containers is that they are completely isolated, thereby, providing maximum security features and championing overall data security even with the presence of multiple containers running side-by-side on the host machine.

The software development life cycle for applications is the same throughout all the containers, so the applications can run in the same way, irrespective of the containers. This provides many advantages in terms of software development and efficient functionality.

Look into the Docker Cheat Sheet by Intellipaat.

Following are some of the noteworthy benefits of using containers:

  • Small code to achieve big results in terms of workloads
  • Reduction in the complexity of security updates
  • Huge reduction in the size of OS snapshots
  • Overall drastic reduction in IT resources

What is a Virtual Machine?

Have you installed Ubuntu, or any other software of Linux, while you’re using Windows? Or perhaps, have you ever tried Windows on a Mac? If so, you have already used a Virtual Machine!

Virtual machines came out to be a popular solution to a problem that has existed for a long time. Consider this, if you are running a piece of software that you do not completely trust or are running anything on an unprotected network, there are chances of threats and possibilities of malignant activities on your machine, which could disrupt the organization and let foreign entities get unauthorized access to the confidential data.

With virtual machines, this issue was resolved as the software that runs inside a virtual machine is isolated completely from the rest of the system, and this software or flaws in the network cannot interfere or tamper with the host machine.

This is extremely advantageous as a sandbox as well! Be it in the testing of a virus-infected application or even in the general testing of any operating system, virtual machines make the process easier.

In simple terms, a virtual machine is a snapshot of an operating system that runs as an application over your host operating system. It can be considered as a different operating system inside the host operating system as it is a standalone entity in terms of functioning and operations.

There are four important files that make up a virtual machine:

  • NVRAM settings file
  • Log files
  • Virtual disk snapshot file
  • Configuration files

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Server Virtualization:

Server virtualization is a term that is gaining momentum rapidly since the last decade. But, what is it? It is a setting wherein a single physical server is divided into many individual or unique servers so that they can operate independently.

Also, for each of these machines, virtual hardware is allocated along the lines of CPU, memory, storage disks, and network I/O channels.

Even though it seems absolutely advantageous to use virtual machines, sometimes they are known for their inability to provide a stable environment or consistent performance due to the presence of a large number of entities, dependencies, and even libraries.

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Docker vs Virtual Machine

The following section aims to discuss the difference between Docker and VM:

Docker vs VM: Architecture

Docker vs VM Architecture

Each virtual machine that runs inside a host operating system has its own kernel, irrespective of the host.

With Docker, each container has access to a single physical server that hosts the operating system and eventually shares this operating system with other containers. This ensures that the containers are extremely lightweight and efficient in terms of boot time.

A virtual machine requires multiple or different kernels to run applications across servers. But, with Docker, a single operating system kernel is effectively used to run multiple applications across all containers.

Next up, you have to understand resource usage whenever the difference between VM and Docker is considered.

Docker vs VM: Resource Usage

It is quite clear that a virtual machine is way more resource-intensive than a Docker container on all fronts. This is because of the way Docker is built and how a virtual machine needs to load an entire operating system to even start working.

With a virtual machine, resources such as memory, network, I/O channels, and CPU are not allocated permanently and are static in nature. In the case of containers, resources are provided based on the traffic or load to help maintain high efficiency and overall dynamism.

If the concern lies in terms of the duplication of containers, then note that it is very simple as there is no requirement to install individual operating systems in each container or spend time and effort to individually tune and tweak the containers to get the best performance possible.

Docker vs VM: Data Security

A virtual machine has an edge over the Docker container system concerning client-server-based data security. This is because a virtual machine does not share an operating system, which makes the virtual machine very strong in terms of being isolated from threats. A Docker container, on the other hand, has a shared host kernel, which makes the container a bit susceptible to vulnerabilities.

If there is an attacker who has gained access to one container in a Docker cluster, then they have access to the entire cluster. This is because of the architecture of Docker that allows for shared resources without any namespaces. A virtual machine never provides direct access to resources as there is a hypervisor that controls the usage of resources.

Docker vs VM: Scalability

Scaling a Docker container architecture is exponentially simpler than doing the same in a virtual machine as Docker is purpose-built for rapid expansion across domains.

In a virtual machine, operating systems are isolated and cannot be easily ported onto different platforms unless hours and hours are spent dealing with the compatibility issues that arise while doing so.

Adding on to the last point, the provision of root access to applications with all Docker containers is not recommended as the containers share a common kernel. However, since they are extremely lightweight, they provide numerous advantages that overshadow this downside.

Let us have a look at a few more differences between Docker and VM.

Also Read about: Docker Interview Questions

Difference between Docker and VM

Comparison FactorDockerVirtual Machine
PerformanceVery lightweight and not resource-intensive in terms of CPU, memory, or I/OResource-intensive and needs to preload an entire operating system architecture to function
Operational EngineUses the execution engine of containers to execute tasks and functionsUses a hypervisor to govern the running and execution of tasks
InterferenceDocker architecture is more prone to adversities as there is no isolation in the systemA virtual machine has the least possible interference due to the isolated nature of its architecture when functioning
Boot-up TimeContainers boot up very quickly as they are not resource-heavy function on distributed architectureA virtual machine takes a few minutes to boot as they have to load the image of an entire operating system to function
DeploymentEasy to deploy due to the presence of only a single containerized image across all platformsHave separate instances of working that cause lengthy deployment both in-time and procedure
Ease of LearningComplex to learn due to the presence of lots of Docker-managed mechanisms and toolsEasy to learn and simple to get started with

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Docker Architecture

While Docker’s architecture is also client-server-based, it is a little more complicated than a virtual machine because of the features involved. The Docker architecture consists of four main parts:

  1. Docker Client: It is Docker’s user interface and determines how users interact with containers.
  2. Docker Objects: The two main components of Docker are containers and images. Containers are used for reading and writing. They are a placeholder for software. Container images are read-only and used to create new containers.
  3. Docker Daemon: It is a background process that is responsible for receiving commands and passing them to containers via the command line.
  4. Docker Registry: It is commonly known as Docker Hub, and is used to store and retrieve container images.

Common Use Cases

Now that you have a good understanding of Docker containers and virtual machines, it is also important to understand their use cases. While they have a similar use, which is to develop applications, below we have described how they are used in the real world:

Real-world Use Cases for VMs

One of the most popular real-world use cases of VMs is Starling Bank, a digital bank that was built on VMs in a time span of just one year. This was possible because of the efficiency VMs provide over traditional servers. In addition to such amazing efficiency, using VMs over traditional servers also costs less, just one-tenth of traditional servers.

Real-World Use Cases for Docker

Docker is popularly used by Paypal to drive cost efficiency and adhere to enterprise-grade security for its infrastructure. By making containers and VMs run side-by-side, Paypal reduces the number of VMs.

In the following section, we will discuss how Docker is used for several reasons and what advantages it offers as compared to traditional servers:

  • Application development: Docker is primarily used to package an application’s code and its dependencies. The same container can be shared from Dev to QA and later to IT. This brings in portability to the development pipeline.
  • Running microservices applications: Docker allows you to run each microservice that makes up an application in its own container. This, in turn, helps Docker to enable a distributed architecture.

Also read: Docker Tutorial for Beginners

Next up on this VM vs Docker blog, is to learn what Virtual Machines are.

Advantages of Virtual Machines and Docker Containers

Advantages of Docker Containers

  • While virtual machines can take an average of a few minutes to boot, Docker is very fast and takes about a few milliseconds to a few seconds to start.
  • Docker containers are process-isolated and do not require a hardware hypervisor.
  • Containers are highly portable as they can be shared with multiple team members. This provides much-needed portability across the development pipeline.

Advantages of Virtual Machines

  • The tools related to virtual machines are much easier to access and simpler to work with. Docker has a complicated tooling ecosystem that consists of both Docker-managed and third-party tools.
  • Once you have a virtual machine up and running, you can start a Docker instance within that virtual machine and run a Docker container within the virtual machine. This way, containers and virtual machines coexist and are not mutually exclusive.

Which is the Better Choice: Docker Containers or Virtual Machines?

It is no brainer that speed and efficiency are the key components that a DevOps team looks for. While Docker is better at offering these two crucial components over virtual machines, we still cannot declare it to be a clear winner. As Docker has gained much-needed popularity among major IT giants, the market dynamics are quickly changing for virtual machines. Virtual machines are used in production environments.

To wrap it up, we would say that Docker cannot replace virtual machines and vice versa. Instead, the two will coexist, giving DevOps teams more choices to run their native-cloud applications.So, we leave the choice up to you, pick the one that is better suited to your requirements!


Can there be a solid winner in this comparison between Docker and Virtual Machines? What do you think? Considering all of the above-mentioned points, I am sure you have the clarity that is needed to understand the differences that lie between these two concepts.

To further add to this, it is quite well known that Virtual Machines are still the #1 choice for any production environment. On the other hand, Docker is purpose-built to provide containers that are small, isolated, highly compatible, working well with high performance-intensive tasks, and responding to changes quickly.

It would not be fair to pick a winner as Docker and Virtual Machines are meant for different purposes. In fact, they are two tools that are complementary to each other in terms of usage and the ease of the workload.

Virtual Machines are built for static applications that do not change rapidly over time, while Docker is built to provide more flexibility for applications that require frequent changes and updates.

Has Docker revolutionized the world of virtual computing? Or is it on a steady path to completely replacing how the world looks at Virtual Machines? Do head to the comments section, and let us know your thoughts on the same!

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