Docker vs Pants

Overview

Docker

Stacks194.2K

Followers143.8K

Votes3.9K

Pants

Stacks23

Followers86

Votes30

GitHub Stars3.7K

Forks674

Docker vs Pants: What are the differences?

Introduction:

Docker and Pants are both tools used in the software development process, but they serve different purposes and have distinct features. Here are the key differences between Docker and Pants:

1. Docker's Focus on Containerization: Docker is primarily focused on containerization, allowing developers to package their applications and dependencies into a lightweight, portable container that can run on any system with Docker installed. This streamlined approach makes it easy to build, ship, and run applications consistently across different environments.

2. Pants' Build System with Declarative Configuration: Pants, on the other hand, is a build system that emphasizes a declarative configuration approach, enabling developers to define dependencies, targets, and tasks in a clear and structured manner. This makes it easier to manage complex builds and automate repetitive tasks efficiently.

3. Docker's Platform Independence: Docker is platform-independent, meaning that containers created using Docker can run on any operating system or cloud service that supports Docker. This flexibility makes it a popular choice for developers working in diverse environments and across various infrastructures.

4. Pants' Unique Target Isolation: Pants provides unique target isolation capabilities, allowing developers to build, test, and run specific parts of their projects independently. This granular control over targets helps improve build times and enhances overall project organization, particularly in larger codebases.

5. Docker's Emphasis on Scalability and Orchestration: Docker places a strong emphasis on scalability and orchestration, providing tools like Docker Swarm and Kubernetes for managing large-scale container deployments and orchestrating containerized applications across clusters of nodes. This makes Docker a preferred choice for deploying and managing microservices architectures.

6. Pants' Support for Multiple Languages and Environments: Pants offers support for multiple programming languages and environments, allowing developers to build and manage projects written in languages like Python, Java, and Scala. This versatility makes Pants a versatile build tool for teams working on a diverse range of projects.

In Summary, Docker focuses on containerization and platform independence, while Pants emphasizes declarative configuration and target isolation, catering to different aspects of the software development process.

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Advice on Docker, Pants

Florian

IT DevOp at Agitos GmbH

Oct 22, 2019

Decided

lxd/lxc and Docker aren't congruent so this comparison needs a more detailed look; but in short I can say: the lxd-integrated administration of storage including zfs with its snapshot capabilities as well as the system container (multi-process) approach of lxc vs. the limited single-process container approach of Docker is the main reason I chose lxd over Docker.

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Detailed Comparison

Docker	Pants
The Docker Platform is the industry-leading container platform for continuous, high-velocity innovation, enabling organizations to seamlessly build and share any application — from legacy to what comes next — and securely run them anywhere	Pants is a build system for Java, Scala and Python. It works particularly well for a source code repository that contains many distinct projects.
Integrated developer tools; open, portable images; shareable, reusable apps; framework-aware builds; standardized templates; multi-environment support; remote registry management; simple setup for Docker and Kubernetes; certified Kubernetes; application templates; enterprise controls; secure software supply chain; industry-leading container runtime; image scanning; access controls; image signing; caching and mirroring; image lifecycle; policy-based image promotion	Builds Java, Scala, and Python.;Adding support for new languages is straightforward.;Supports code generation: thrift, protocol buffers, custom code generators.;Resolves external JVM and Python dependencies.;Runs tests.;Spawns Python and Scala REPLs with appropriate load paths.;Creates deployable packages.;Scales to large repos with many interdependent modules.;Designed for incremental builds.;Support for local and distributed caching.;Especially fast for Scala builds, compared to alternatives.;Builds standalone python executables (PEX files);Has a plugin system to add custom features and override stock behavior.;Runs on Linux and Mac OS X.
Statistics
GitHub Stars -	GitHub Stars 3.7K
GitHub Forks -	GitHub Forks 674
Stacks 194.2K	Stacks 23
Followers 143.8K	Followers 86
Votes 3.9K	Votes 30
Pros & Cons
Pros 823 Rapid integration and build up 692 Isolation 521 Open source 505 Testability and reproducibility 460 Lightweight Cons 8 New versions == broken features 6 Documentation not always in sync 6 Unreliable networking 4 Moves quickly 3 Not Secure	Pros 6 Creates deployable packages 4 Scales 4 Runs on Linux 4 Runs on OS X 4 BUILD files
Integrations
Java Docker Compose VirtualBox Linux Amazon EC2 Container Service Docker Swarm boot2docker Kubernetes Docker Machine Vagrant	No integrations available

What are some alternatives to Docker, Pants?

Apache Maven

Maven allows a project to build using its project object model (POM) and a set of plugins that are shared by all projects using Maven, providing a uniform build system. Once you familiarize yourself with how one Maven project builds you automatically know how all Maven projects build saving you immense amounts of time when trying to navigate many projects.

Gradle

Gradle is a build tool with a focus on build automation and support for multi-language development. If you are building, testing, publishing, and deploying software on any platform, Gradle offers a flexible model that can support the entire development lifecycle from compiling and packaging code to publishing web sites.

Bazel

Bazel is a build tool that builds code quickly and reliably. It is used to build the majority of Google's software, and thus it has been designed to handle build problems present in Google's development environment.

LXD

LXD isn't a rewrite of LXC, in fact it's building on top of LXC to provide a new, better user experience. Under the hood, LXD uses LXC through liblxc and its Go binding to create and manage the containers. It's basically an alternative to LXC's tools and distribution template system with the added features that come from being controllable over the network.

LXC

LXC is a userspace interface for the Linux kernel containment features. Through a powerful API and simple tools, it lets Linux users easily create and manage system or application containers.

JitPack

JitPack is an easy to use package repository for Gradle/Sbt and Maven projects. We build GitHub projects on demand and provides ready-to-use packages.

SBT

It is similar to Java's Maven and Ant. Its main features are: Native support for compiling Scala code and integrating with many Scala test frameworks.

rkt

Rocket is a cli for running App Containers. The goal of rocket is to be composable, secure, and fast.

Buck

Buck encourages the creation of small, reusable modules consisting of code and resources, and supports a variety of languages on many platforms.

Apache Ant

Ant is a Java-based build tool. In theory, it is kind of like Make, without Make's wrinkles and with the full portability of pure Java code.

Related Comparisons

Docker vs Pants: What are the differences?

Introduction:

Docker and Pants are both tools used in the software development process, but they serve different purposes and have distinct features. Here are the key differences between Docker and Pants:

Docker vs Pants

Overview