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BitKeeper

3
18
+ 1
0
Plastic SCM

40
76
+ 1
17
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BitKeeper vs Plastic SCM: What are the differences?

What is BitKeeper? Enterprise-ready version control, now open-source. BitKeeper is a fast, enterprise-ready, distributed SCM that scales up to very large projects and down to tiny ones.

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..

BitKeeper and Plastic SCM belong to "Version Control System" category of the tech stack.

Some of the features offered by BitKeeper are:

  • Simple: An easy to use command line interface.
  • Scalable: Nested Repositories are submodules done right! Version control collections of repositories.
  • Flexible: Hybrid mode for binary files that uses a cloud of server for binaries instead of bloating the source repositories.

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

  • Distributed version control system
  • Branch Explorer
  • Semantic Version Control
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Pros of BitKeeper
Pros of Plastic SCM
    Be the first to leave a pro
    • 8
      Wanna do Branch per Task Dev? Plastic rocks it
    • 4
      No Size limite
    • 2
      File Locking
    • 2
      Simple, easy to use interfaces. Resilient and solid
    • 1
      Very fast

    Sign up to add or upvote prosMake informed product decisions

    Cons of BitKeeper
    Cons of Plastic SCM
      Be the first to leave a con
      • 1
        Always uses automatic conflict resolution first
      • 1
        Adds files with only changed timestamp to pending
      • 1
        Keyboard shortcuts are lacking
      • 1
        Can't place windows next to each other to save space
      • 1
        No dark theme
      • 1
        Doesn't have file staging

      Sign up to add or upvote consMake informed product decisions

      What is BitKeeper?

      BitKeeper is a fast, enterprise-ready, distributed SCM that scales up to very large projects and down to tiny ones.

      What is Plastic SCM?

      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.

      Need advice about which tool to choose?Ask the StackShare community!

      What companies use BitKeeper?
      What companies use Plastic SCM?
        No companies found
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        What tools integrate with BitKeeper?
        What tools integrate with Plastic SCM?

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        What are some alternatives to BitKeeper and Plastic SCM?
        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.
        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.
        Perforce
        Visibility, access control, workflow and code management for Git environments. Flexibility of collaborating on the same codebase and code reviews using any combination of Perforce and Git workflows and tools without compromise.
        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.
        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.
        See all alternatives