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  1. Stackups
  2. DevOps
  3. Version Control
  4. Version Control System
  5. Docker Cloud vs Plastic SCM

Docker Cloud vs Plastic SCM

OverviewComparisonAlternatives

Overview

Plastic SCM
Plastic SCM
Stacks40
Followers75
Votes17
Docker Cloud
Docker Cloud
Stacks78
Followers127
Votes11

Docker Cloud vs Plastic SCM: What are the differences?

What is Docker Cloud? A hosted service for Docker container management and deployment. Docker Cloud is the best way to deploy and manage Dockerized applications. Docker Cloud makes it easy for new Docker users to manage and deploy the full spectrum of applications, from single container apps to distributed microservices stacks, to any cloud or on-premises infrastructure.

What is Plastic SCM? A distributed version control with strong merging, great GUIs and support for huge files. Plastic SCM is a distributed version control designed for big projects It excels on branching and merging, graphical user interfaces, and can also deal with large files and even file-locking (great for game devs).

It includes "semantic" features like refactor detection to ease diffing complex refactors..

Docker Cloud can be classified as a tool in the "Containers as a Service" category, while Plastic SCM is grouped under "Version Control System".

Some of the features offered by Docker Cloud are:

  • Simplify Docker Provisioning
  • Deploy Apps Anywhere
  • Automate Your Developer Workflows

On the other hand, Plastic SCM provides the following key features:

  • Distributed version control system
  • Branch Explorer
  • Semantic Version Control

"Easy to use" is the top reason why over 7 developers like Docker Cloud, while over 6 developers mention "Wanna do Branch per Task Dev? Plastic rocks it" as the leading cause for choosing Plastic SCM.

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Detailed Comparison

Plastic SCM
Plastic SCM
Docker Cloud
Docker Cloud

Plastic SCM is a distributed version control designed for big projects. It excels on branching and merging, graphical user interfaces, and can also deal with large files and even file-locking (great for game devs). It includes "semantic" features like refactor detection to ease diffing complex refactors.

Docker Cloud is the best way to deploy and manage Dockerized applications. Docker Cloud makes it easy for new Docker users to manage and deploy the full spectrum of applications, from single container apps to distributed microservices stacks, to any cloud or on-premises infrastructure.

Distributed version control system;Branch Explorer;Semantic Version Control;Locking;Huge files;Big projects;GitSync;Super strong merging;Partial replica;ACL security;Database backends
Simplify Docker Provisioning;Deploy Apps Anywhere;Automate Your Developer Workflows;Manage Apps Anywhere
Statistics
Stacks
40
Stacks
78
Followers
75
Followers
127
Votes
17
Votes
11
Pros & Cons
Pros
  • 8
    Wanna do Branch per Task Dev? Plastic rocks it
  • 4
    No Size limite
  • 2
    Simple, easy to use interfaces. Resilient and solid
  • 2
    File Locking
  • 1
    Very fast
Cons
  • 1
    Adds files with only changed timestamp to pending
  • 1
    Always uses automatic conflict resolution first
  • 1
    Doesn't have file staging
  • 1
    No dark theme
  • 1
    Can't place windows next to each other to save space
Pros
  • 9
    Easy to use
  • 2
    Seamless transition from docker compose
Integrations
Gluon
Gluon
TeamCity
TeamCity
Jenkins
Jenkins
Visual Studio Code
Visual Studio Code
Visual Studio
Visual Studio
Docker
Docker

What are some alternatives to Plastic SCM, Docker Cloud?

Git

Git

Git is a free and open source distributed version control system designed to handle everything from small to very large projects with speed and efficiency.

Amazon EC2 Container Service

Amazon EC2 Container Service

Amazon EC2 Container Service lets you launch and stop container-enabled applications with simple API calls, allows you to query the state of your cluster from a centralized service, and gives you access to many familiar Amazon EC2 features like security groups, EBS volumes and IAM roles.

Mercurial

Mercurial

Mercurial is dedicated to speed and efficiency with a sane user interface. It is written in Python. Mercurial's implementation and data structures are designed to be fast. You can generate diffs between revisions, or jump back in time within seconds.

Google Kubernetes Engine

Google Kubernetes Engine

Container Engine takes care of provisioning and maintaining the underlying virtual machine cluster, scaling your application, and operational logistics like logging, monitoring, and health management.

SVN (Subversion)

SVN (Subversion)

Subversion exists to be universally recognized and adopted as an open-source, centralized version control system characterized by its reliability as a safe haven for valuable data; the simplicity of its model and usage; and its ability to support the needs of a wide variety of users and projects, from individuals to large-scale enterprise operations.

Containerum

Containerum

Containerum is built to aid cluster management, teamwork and resource allocation. Containerum runs on top of any Kubernetes cluster and provides a friendly Web UI for cluster management.

Pijul

Pijul

Pijul is a free and open source (AGPL 3) distributed version control system. Its distinctive feature is to be based on a sound theory of patches, which makes it easy to learn and use, and really distributed.

Azure Container Service

Azure Container Service

Azure Container Service optimizes the configuration of popular open source tools and technologies specifically for Azure. You get an open solution that offers portability for both your containers and your application configuration. You select the size, the number of hosts, and choice of orchestrator tools, and Container Service handles everything else.

Amazon EKS

Amazon EKS

Amazon Elastic Container Service for Kubernetes (Amazon EKS) is a managed service that makes it easy for you to run Kubernetes on AWS without needing to install and operate your own Kubernetes clusters.

DVC

DVC

It is an open-source Version Control System for data science and machine learning projects. It is designed to handle large files, data sets, machine learning models, and metrics as well as code.

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