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packagecloud VS Conda

Compare packagecloud VS Conda and see what are their differences

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Contents:
  1. » Base Details
  2. » Reviews
  3. » Alternatives

packagecloud logo packagecloud

Free hosted Node.js, Debian, RPM, Java, Python and RubyGem repositories. Chef, Puppet, Jenkins, Buildkite, CircleCI and Travis CI integrations.

Conda logo Conda

Binary package manager with support for environments.
  • packagecloud Landing page
    Landing page //
    2023-03-07

Packagecloud is a cloud-based package repository that allows its users to host npm, python, rubygem, apt, Java/Maven, and yum repositories without having to configure anything first. Being a cloud-based solution, it also allows one to distribute various software packages in a uniform, scalable, and dependable manner without investing in infrastructure.

Regardless of the programming language or OS, you can keep all of the packages that you need to be deployed across your organization’s workstations in one repo. Then, without owning any of the infrastructure required, you may securely and efficiently distribute packages to your devices.

Not present

packagecloud

Website
packagecloud.io
Pricing URL
Official packagecloud Pricing
$ Details
freemium $89.0 / Monthly ("Starter Plan", "20 Gb Transfer", "5 Gb Storage")
Platforms
Cross Platform Linux Windows Mac OSX Cloud
Release Date
2016 January
Edit details

Conda

Website
docs.conda.io
Pricing URL
-
$ Details
-
Platforms
-
Release Date
-
Edit details

packagecloud features and specs

  • Unlimited Users
  • Unlimited Repositories
  • Universal asset management
  • CI/CD Pipeline Orchestration

Conda features and specs

  • Cross-Platform Package Manager
    Conda is a versatile package manager that works across multiple operating systems including Windows, macOS, and Linux, making it a universal solution for environment management.
  • Environment Management
    Conda can create, export, list, remove, and manage environments that contain different versions of Python and/or various packages, enhancing reproducibility and isolation.
  • Wide Range of Packages
    Conda supports a broad spectrum of packages not limited to Python, which means it can install software and their dependencies from the C, C++, FORTRAN, and other ecosystems.
  • Binary Package Delivery
    Packages are delivered as binaries, meaning you don't have to compile anything. This speeds up the installation process and reduces the possibility of errors.
  • Easy Dependency Resolution
    Conda automatically manages dependencies, ensuring that the required packages are installed in the correct versions and reducing compatibility issues.
  • Version Control
    It allows you to manage different versions of software and switch between them seamlessly without conflict, which is crucial for development, testing, and deployment.

Possible disadvantages of Conda

  • Large Disk Space Requirement
    Conda environments can take up a significant amount of disk space due to the inclusion of multiple versions of Python and other binaries.
  • Complexity
    While Conda is powerful, its comprehensive set of features may be overwhelming for beginners who only need simpler package management.
  • Performance Overhead
    The convenience of automated dependency resolution and environment management can sometimes come at the cost of performance, particularly during the first setup.
  • Slower Package Availability
    Newer versions of some packages may take longer to become available on Conda compared to other package managers like pip, leading to potential delays in adopting the latest features.
  • Third-Party Channels
    While Conda has its main channel, many packages are hosted on third-party channels, which can lead to inconsistencies or reliability issues.
  • Not Limited to Python
    Although this is also a strength, for users who are primarily working with Python, Conda might feel over-engineered for their needs.

Analysis of Conda

Overall verdict

  • Yes, Conda is generally regarded as a good tool due to its versatility, efficiency in managing dependencies, and user-friendly features.

Why this product is good

  • Conda is considered good because it is a powerful package manager and environment manager that is language agnostic. It simplifies the installation of packages and dependencies across different programming languages, particularly beneficial for data science and machine learning tasks. It also handles library conflicts with ease, making it a preferred choice for managing complex software environments.

Recommended for

  • Data scientists
  • Machine learning engineers
  • Software developers using Python, R, or any other language needing isolated environments
  • Researchers requiring reproducible scientific environments
  • Anyone who frequently works with packages that have complex dependencies

Category Popularity

0-100% (relative to packagecloud and Conda)

packagecloud

Conda

Package Manager
31 31%
Package Manager
69% 69
Front End Package Manager
0 0%
Front End Package Manager
100% 100
Software Development
100 100%
Software Development
0% 0
Developer Tools
38 38%
Developer Tools
62% 62

User comments

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Reviews

These are some of the external sources and on-site user reviews we've used to compare packagecloud and Conda

packagecloud Reviews

What is Artifactory?
Packagecloud is a cloud-based package repository that allows its users to host npm, python, rubygem, apt, Java/Maven, and yum repositories without having to configure anything first. Being a cloud-based solution, it also allows one to distribute various software packages in a uniform, scalable, and dependable manner without investing in infrastructure. Regardless of the...
Source: blog.packagecloud.io

Conda Reviews

We have no reviews of Conda yet.
Be the first one to post

Social recommendations and mentions

Based on our record, Conda should be more popular than packagecloud. It has been mentiond 32 times since March 2021. We are tracking product recommendations and mentions on various public social media platforms and blogs. They can help you identify which product is more popular and what people think of it.

packagecloud mentions (5)

  • Reports on successful blocks
    Looks like the repository on packagecloud.io don't have the latest version yet, it only lists 0.0.23? I got 0.0.24 from somewhere though. Source: over 2 years ago
  • I tried to switch to the testing branch of Debian and below is my /etc/apt/sources.list:
    Forcing the config can be don manually by modifying the config files that points to different repos in /etc/apt/sources.list.d, or for packages on packagecloud.io, you can use the method that I describe. The latter works because packagecloud.io has a robust strip to create config files based on the detected operating systems or you can force a certain operating system/dist as shown above. Source: over 2 years ago
  • I tried to switch to the testing branch of Debian and below is my /etc/apt/sources.list:
    The error you are seeing is because you probably ran one of the steps that creates a configuration in your system that points to packagecloud.io, so that your system can retrieve packages from https://packagecloud.io/cs50/repo. However since there are no Debian bookworm packages there, you are seeing the error. Source: over 2 years ago
  • Free for dev - list of software (SaaS, PaaS, IaaS, etc.)
    Packagecloud.io — Hosted Package Repositories for YUM, APT, RubyGem and PyPI. Limited free plans, open source plans available via request. - Source: dev.to / almost 4 years ago
  • Need help installing Pi hole
    You have something installed via packagecloud.io which is no longer avalaible. Delete the line from your sources. Source: almost 4 years ago

Conda mentions (32)

  • Say Hello to UV: A Fast Python Package & Project Manager Written in Rust
    If you’ve been managing Python projects long enough, you’ve probably dealt with a mess of tools: pip, pip-tools, poetry, virtualenv, conda, maybe even pdm. - Source: dev.to / about 2 months ago
  • The Simplest Data Architecture
    You can use isolated Python environments like venv or conda. If you do this, you'll have to manage your environments yourself, and also constantly switch between them to run your data engineering code vs dbt. - Source: dev.to / 8 months ago
  • Python's virtual environments
    Conda is an open-source package management system and environment management system that runs on Windows, macOS, and Linux. It is a powerful tool that allows you to create and manage virtual environments, install and update packages, and manage dependencies. Conda is particularly popular in the scientific computing community, as it provides access to a wide range of scientific computing libraries and tools. I... - Source: dev.to / 11 months ago
  • Introducing Flama for Robust Machine Learning APIs
    When dealing with software development, reproducibility is key. This is why we encourage you to use Python virtual environments to set up an isolated environment for your project. Virtual environments allow the isolation of dependencies, which plays a crucial role to avoid breaking compatibility between different projects. We cannot cover all the details about virtual environments in this post, but we encourage... - Source: dev.to / over 1 year ago
  • Ask HN: Package management for multiple modules in C++, Python, Java project?
    Conda https://docs.conda.io/en/latest/ ?? I'm not sure, but I used it to download some Python packages. It's an alternative to pip, but I'm not sure about the details. - Source: Hacker News / over 1 year ago
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What are some alternatives?

When comparing packagecloud and Conda, you can also consider the following products

Cloudsmith - Cloudsmith is the preferred software platform for securely storing and sharing packages and containers. We have distributed millions of packages for innovative companies around the world.

Homebrew - The missing package manager for macOS

Artifactory - The world’s most advanced repository manager.

Python Poetry - Python packaging and dependency manager.

Sonatype Nexus Repository - The world's only repository manager with FREE support for popular formats.

pkgsrc - pkgsrc is a framework for building over 17,000 open source software packages.

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