Active Hackathon

Top 6 Open-Source Version Control Tools For Data

Version control systems are the process management systems that keep tracks of every individual modification to the code by every contributor. It helps the developers and the software teams to manage the source code over time. Version control systems are also known as Source Code Management (SCM) tools or Revision Control System (RCS).

In this article, we list down the top 6 open-source version control tools for data science.


Sign up for your weekly dose of what's up in emerging technology.

(The list is in alphabetical order)

1|  Apache Subversion

About: Apache Subversion is an open-source software versioning and revision control system. Some of the features of this version control tool are mentioned below: –

  • In this tool, copying, deleting, and renaming are considered as versioned operations.
  • Free-form versioned metadata – Subversion allows arbitrary metadata (“properties”) to be attached to any file or directory.
  • CVS features – Concurrent Versions System (CVS) is a relatively basic version control system. Apache Subversion has matched or exceeded CVS’s feature set.
  • It includes atomic commits and no part of a commit takes effect until the entire commit has succeeded. 
  • Subversion supports locking files so that users can be warned when multiple people try to edit the same file. 

Know more here.

2| Data Version Control

About: Data Version Control or DVC is an open-source version control system for data science and machine learning projects. The tool is designed to handle large files, data sets, machine learning models, code, etc. and is built to make ML models shareable and reproducible.

Some of the features of DVC are: –

  • This open-source ML tool runs on top of any Git repository
  • DVC guarantees reproducibility by consistently maintaining a combination of input data, configuration, and the code that was initially used to run an experiment.
  • It supports instantaneous Git branching, even with the larger files.
  • This tool has a built-in way to connect ML steps into a directed acrylic graph (DAG) as well as run the full pipeline end-to-end. 

Know more here.

3| Git 

About: 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.

Some of the features include: –

  • Branching and Merging – Git allows you to have multiple local branches that can be entirely independent of each other.
  • With Git, nearly all operations are performed locally.
  • Because of Git’s distributed nature and branching system, an endless number of workflows can be implemented with relative ease.
  • The data model that Git uses ensures the cryptographic integrity of every bit of your project. 
  • Using Git, you can quickly stage some of your files and commit them without committing all of the other modified files in your working directory.

Know more here.

4| Mercurial

About: Mercurial is a free, distributed source control management tool. The tool efficiently handles projects of any size and offers an easy and intuitive interface. Some of the features include: –

  • It is easy to learn.
  • Using this tool, most of the tasks simply work on the first try and without requiring arcane knowledge.
  • It provides every developer with a local copy of the entire development history. 

Know more here.

5| Perforce

About: Perforce is an open-sourced enterprise version management system in which users connect to a shared file repository. Perforce applications are used to transfer files between the file repository and individual users’ workstations. Some of the features are mentioned below: –

  • Branching and Merging
  • Artefact Management
  • Defence in Depth
  • Integrations

Know more here.

6| Pachyderm

About: Pachyderm is a free and complete version control system for data science. The Pachyderm Enterprise is a fully-featured data science platform that is designed for large-scale collaboration in highly secure environments.

Some of its features are: –

  • Containerised: Pachyderm is built on Docker and Kubernetes.
  • Version Control: Pachyderm version controls your data during the processing.
  • Pachyderm can efficiently schedule massively parallel workloads.

Know more here.

7| AWS CodeCommit

About: AWS CodeCommit is a fully-managed source control service that hosts secure Git-based repositories. However, this popular tool is not open-source, but it costs as low as $1 per active user per month. The features of this tool include: –

  • Fully managed: it eliminates the need to host, maintain, back up, and scale source control servers.
  • AWS CodeCommit automatically encrypts the files in transit and at rest. 
  • AWS CodeCommit has a highly scalable, redundant, and durable architecture. 
  • It helps to collaborate on code with teammates via pull requests, branching and merging. 
  • The tool keeps your repositories close to your build, staging, and production environments in the AWS cloud.
  • AWS CodeCommit supports all Git commands and works with your existing Git tools. 

Know more here.

More Great AIM Stories

Ambika Choudhury
A Technical Journalist who loves writing about Machine Learning and Artificial Intelligence. A lover of music, writing and learning something out of the box.

Our Upcoming Events

Conference, Virtual
Genpact Analytics Career Day
3rd Sep

Conference, in-person (Bangalore)
Cypher 2022
21-23rd Sep

Conference, in-person (Bangalore)
Machine Learning Developers Summit (MLDS) 2023
19-20th Jan, 2023

Conference, in-person (Bangalore)
Data Engineering Summit (DES) 2023
21st Apr, 2023

Conference, in-person (Bangalore)
MachineCon 2023
23rd Jun, 2023

3 Ways to Join our Community

Discord Server

Stay Connected with a larger ecosystem of data science and ML Professionals

Telegram Channel

Discover special offers, top stories, upcoming events, and more.

Subscribe to our newsletter

Get the latest updates from AIM

A Case for IT Professionals Switching Jobs Frequently

For Indian companies, the ability to retain employees has become a tight ropewalk between transforming their working models and adopting a hybrid working model successfully. Over 60% respondents in the Qualtrics survey said that they would look for a new job, if forced to return to work from office full time.