A Complete Guide to Open Source Software

Jan 8, 2024 by Connie Lin

What Is Open Source Software?

Open source software (OSS) is a type of software whose source code is available to the public. This means that anyone can view, modify, and distribute the software as they see fit. OSS is an alternative to the traditional proprietary software model, where the source code is kept secret and users are restricted in their ability to modify or share the software.

OSS is rooted in the belief that software should be a community resource. Developers from around the world can collaborate on OSS projects, making improvements and adding features that benefit everyone. This collaborative model also allows for rapid innovation, as the combined efforts of many developers can often outpace those of a single company.

However, it's important to note that 'open source' doesn't necessarily mean 'free'. While many OSS projects are available for free, developers can choose to charge for their software if they wish. The key difference is that the source code must be available to users, allowing them to modify and distribute the software as they see fit.

A Brief History of Open Source Software

The concept of open source software may seem like a new phenomenon, but its roots go back several decades. In the early days of computing, software was often shared freely among academics and researchers. The idea was to foster collaboration and accelerate innovation, much like the open source movement today.

However, as the software industry began to take shape in the 1970s and 1980s, companies started to see the value in proprietary software. They began to keep their source code secret, selling licenses to users that allowed them to use the software but not to modify or distribute it. This shift towards proprietary software marked a significant change in the software industry, and it was not without controversy.

In the late 1980s and early 1990s, a group of developers led by Richard Stallman began to push back against this trend. They believed that software should be a communal resource, and they started to develop free software that anyone could modify and distribute. This marked the beginning of the modern open source movement, and it has been growing ever since.

Open Source vs. Closed Source Software

Closed source software (also called custom code or proprietary code) is protected, preventing unauthorized users from using or viewing the source code. Any attempts to modify, delete, or copy closed code components can result in legal repercussions or voiding the warranty.

In contrast, open source software allows users to copy, delete, or modify code components, keeping the code open so that others can include this code in their program, according to the licensing granted by the open source code creators. Let’s explore the key differences between open and closed source software.

Support

Closed source software is typically developed and maintained by a single company or organization. This centralized development structure allows for dedicated customer support teams that can quickly address any issues or concerns that users may encounter. Closed source software often comes with comprehensive documentation, tutorials, and training resources to assist users in maximizing its potential.

On the other hand, open source software is developed by a community of contributors who collaborate to improve and enhance the software. While this distributed development model fosters innovation and creativity, it can sometimes lead to limited support options.

However, open source communities are known for their vibrant and helpful nature. Users can seek assistance from forums, discussion groups, and online communities where experienced developers and enthusiasts are eager to lend a helping hand. Open source software also benefits from continuous updates and improvements driven by a diverse range of contributors.

Usability

Closed source software is often designed with a focus on user-friendliness and intuitive interfaces. Extensive user testing and interface design considerations are conducted to ensure a smooth and seamless user experience. Closed source software tends to have a consistent look and feel, making it easier for users to navigate and accomplish their tasks efficiently.

Open source software, on the other hand, may have varying degrees of usability. Since it is developed by a diverse community, usability can sometimes be a hit or miss. However, many open source projects have made significant strides in improving their user interfaces and overall user experience. Some projects even have dedicated teams focused on enhancing usability.

Moreover, open source software provides users with the freedom to customize and tailor the software to their specific needs, which can greatly enhance usability for those willing to invest time and effort.

Security

Closed source software often benefits from a dedicated team of security experts who identify and patch vulnerabilities. The proprietary nature of closed source software can make it more difficult for malicious actors to exploit security loopholes, as the source code is not freely available for scrutiny. Additionally, closed source software companies often prioritize security audits and regular updates to ensure that their software remains robust against emerging threats.

Open source software involves a different approach to security. The transparency of the source code allows a global community of developers to scrutinize it for vulnerabilities and suggest improvements. This collaborative effort can lead to rapid identification and resolution of security issues.

Open source software communities often have a culture of sharing security best practices and collectively addressing vulnerabilities. However, users must still exercise caution and ensure that they are using official releases from trusted sources, and that the open source projects they are using are regularly maintained.

Cost

Closed source software is typically associated with licensing fees or subscription-based pricing models. These costs can vary greatly depending on the complexity and intended use of the software. While closed source software may require an upfront investment, it often comes bundled with customer support, regular updates, and additional features.

Open source software is generally available for free. Users can download, use, and modify the software without any licensing costs. This makes OSS an attractive option for individuals and organizations with limited budgets. However, it is important to consider the total cost of ownership when evaluating open source software. While the software itself may be free, there may be additional costs associated with implementation, customization, and ongoing support.

Flexibility

Closed source software offers limited flexibility. Users are generally limited to the features and functionalities provided by the software vendor. Customization options may be limited, and users may have to rely on the vendor's roadmap for future enhancements. While closed source software can often meet the needs of a broad range of users, it may not be suitable for those seeking extensive customization or integration capabilities.

By providing users with access to the source code, open source software allows for customization and modification to meet specific needs. This flexibility is particularly valuable for organizations with unique requirements or those seeking to integrate the software with existing systems and workflows. Users can tailor the software to their precise needs, whether it involves adding new features, removing unnecessary ones, or integrating with other software solutions.

What Are Open Source Licenses?

Open source licenses are legal agreements that specify how an OSS can be used, modified, and distributed. These licenses are crucial for maintaining the open nature of OSS. Without them, developers could potentially restrict how their software is used, undermining the whole concept of open source. There are many different types of open source licenses, each with its own set of conditions and permissions. Some licenses are very permissive, allowing users to do almost anything with the software. Others, known collectively as ‘copyleft’ licenses, are more restrictive, placing certain limitations on how the software can be modified or distributed. Including components with copyleft licenses in your software can severely limit your ability to commercialize or monetize the software.

Popular Permissive Licenses

The Apache License

The Apache License is a permissive license created by the Apache Software Foundation. It allows users to use, modify, and distribute the software, provided that they comply with the terms of the license. This includes providing attribution to the original author and including a copy of the license in any distributions.

One of the notable features of the Apache License is its grant of a patent license. This means that contributors automatically grant a license to their patents that would be infringed by the software. This feature helps to protect users and developers from potential patent litigation.

MIT License

The MIT License is named after the Massachusetts Institute of Technology, where it originated. The MIT License is simple and straightforward, allowing users to do whatever they want with the software, as long as they provide attribution and include a copy of the license.

The MIT License does not include a patent license, which differentiates it from the Apache License. However, its simplicity and permissiveness have made it a popular choice for many open source projects.

BSD License

The BSD License originated at the University of California, Berkeley. There are several variations of the BSD License, but they all allow users to use, modify, and distribute the software, provided they meet certain conditions.

These conditions usually involve providing attribution and including a copy of the license. Some versions of the BSD License also include a non-endorsement clause, which prohibits the use of the names of the contributors to endorse or promote products derived from the software.

Popular Copyleft Open Source Licenses

GNU General Public License (GPL)

The GNU General Public License (GPL) was created by Richard Stallman and the Free Software Foundation, and it has been instrumental in the growth of the open source movement. The GPL requires that any derivative works must also be licensed under the GPL. This ensures that the software remains open and free for everyone to use, modify, and distribute. But at the same time, it severely restricts the ability to commercialize any software based on GPL-licensed technology.

Affero GPL (AGPL)

The GNU Lesser General Public License (LGPL) is a less restrictive version of the GPL. It allows developers to use LGPL-licensed code in proprietary software, provided that they make the source code for the LGPL components available. The LGPL is a popular choice for libraries and other software components that are designed to be used in a variety of projects. It provides a balance between openness and flexibility. However, like the GPL, the LGPL is still a copyleft license, which means that it imposes certain restrictions on how the software can be used.

Eclipse Public License (EPL)

The Eclipse Public License (EPL) is used by the Eclipse Foundation for their widely-used Eclipse IDE, among other projects. While the EPL is a copyleft license, it is less restrictive than the GPL. It allows developers to use EPL-licensed code in proprietary software, without requiring that the entire software be EPL-licensed.

Mozilla Public License (MPL)

The Mozilla Public License (MPL) is used by the Mozilla Foundation for their Firefox web browser and other projects. The MPL is similar to the EPL in that it allows for the use of MPL-licensed code in proprietary software. The MPL has a unique feature called the 'file-level copyleft'. This means that modifications to existing MPL-licensed files must be released under the MPL, but new files can be licensed as the developer sees fit.

Business Source Licenses

The Business Source License (BSL) is a type of software license that offers a unique approach to balancing the benefits of open source and proprietary software. It was created by MariaDB Corporation founder Michael "Monty" Widenius. Here are some key features of the BSL:

Time-delayed source code release: Under a BSL license, the source code of the software is eventually made available as open source after a predetermined delay period. This period is typically a few years, after which the software automatically converts to a standard open-source license, such as the General Public License (GPL).
Limited use rights initially: During the delay period, users have limited rights to use, modify, and share the software. The license may impose certain restrictions, such as on the size of the organization that can use it for free, or the types of uses (like non-commercial) that are permitted without a paid license.
Commercial use: The BSL allows the original creators to monetize the software during the delay period. Companies or individuals who wish to use the software for purposes beyond what is allowed for free under the BSL typically need to purchase a commercial license.
Promotion of open source ideals: After the delay period ends and the software becomes open source under a traditional open-source license, the community benefits from access to the source code. This delayed release mechanism promotes open source ideals while allowing the creators to derive commercial benefits initially.

Key Use Cases for Open Source Software

Web Servers and Hosting

Open source plays an important role in the domain of web servers and hosting. The Apache HTTP Server, one of the most prominent OSS projects, has been a cornerstone of the internet, powering a significant portion of the web's sites. Its success is attributed to its robustness, flexibility, and active community support. Additionally, Nginx, another OSS web server, has gained popularity for its high performance, scalability, and efficient handling of concurrent connections, making it an ideal choice for high-traffic websites.

In hosting environments, open source tools like the LAMP stack (Linux, Apache, MySQL, PHP/Python/Perl) enable businesses and developers to deploy web applications efficiently. The stack's components are all open source, ensuring a cohesive and cost-effective platform for web development and hosting.

Database Management

In the realm of database management, OSS offers a range of solutions that cater to different needs, from lightweight databases like SQLite to powerful, enterprise-grade systems like PostgreSQL and MySQL. These open source databases provide users with the ability to handle data effectively, whether for small personal projects or large, complex applications.

Open source databases offer high levels of customization and flexibility, allowing businesses to tailor the database system to their specific requirements. The vibrant communities around these databases contribute to their reliability and security, with regular updates and patches addressing emerging threats or issues.

Cloud Computing and Containerization

In cloud computing, open source technologies have been transformative. Notable examples are OpenStack for cloud infrastructure management, Docker for containerization and Kubernetes for container orchestration. These tools offer organizations the ability to build and manage scalable, flexible cloud environments without being tied to proprietary solutions.

The collaborative nature of open source development accelerates innovation in the cloud computing space, with new features and integrations being developed at a rapid pace. Furthermore, the transparency and modifiability of open source software provide users with greater control over their cloud infrastructure.

Real-Time Operating Systems (RTOS)

Real-Time Operating Systems (RTOS) are crucial for applications requiring immediate processing and response to external events. OSS projects like FreeRTOS and RTLinux provide the foundation for developing real-time applications in areas such as embedded systems, automotive, and IoT devices.

These open source RTOS platforms allow developers to access and modify the source code, enabling them to optimize and customize the operating system according to their project's specific needs. The availability of source code and a community of developers also helps in identifying and fixing bugs and security issues quickly.

Learn more in the detailed guide to RTOS.

Security Tools

The open source community has contributed significantly to cybersecurity, offering a wide array of tools for monitoring, penetration testing, and securing networks. Tools like Wireshark for network protocol analysis, Zed Application Proxy (ZAP) for dynamic application testing, and Metasploit for security vulnerability testing, are indispensable to security professionals.

Open source security tools benefit from the collective expertise of a global community. Additionally, these tools can be customized to suit the unique security needs of each organization.

What Is an Open Source Software Policy?

An open source software policy is a set of rules and guidelines that govern how an organization or individual uses and contributes to open source software. The policy outlines the practices and procedures that need to be followed when dealing with open source software to ensure compliance with licenses, protect intellectual property rights, and maintain the integrity of the software.

The policy also provides guidance on how to contribute to open source projects. This includes how to submit changes, how to handle disputes, and how to acknowledge the work of others. It's important to remember that contributing to open source requires more than writing code. It can also involve reporting bugs, improving documentation, and helping other users.

Keeping an open source software policy helps in managing risks associated with the use of open source software. It ensures that the organization is aware of its responsibilities and obligations when using and distributing open source software. A well-defined policy can also help in decision-making processes, ensuring that the use of open source software aligns with the organization's strategic goals.

Best Practices for Open Source Security and Compliance

Open source security is a growing concern in software development organizations, because most enterprise software projects include thousands of open source components. Here are a few ways to ensure open source software does not compromise the security of your applications.

Monitor for Updates

Securing open source software requires continuous monitoring for security updates. Many open-source projects are updated regularly, and it’s crucial to keep track of these updates and apply them promptly.

Updates often contain security patches that fix known vulnerabilities in the software. Failing to apply these patches can leave your systems exposed to potential threats. Therefore, it is essential to have a system in place that alerts you when new updates or vulnerabilities are detected.

Implement Open Source Vulnerability Scanning

Vulnerability scanning is a proactive approach to identifying security weaknesses in your OSS. It involves using specialized tools to scan your software for known vulnerabilities. These tools compare the components of your software against databases of known vulnerabilities, such as the National Vulnerability Database (NVD).

Open source vulnerability scanning helps you identify and fix vulnerabilities before they can be exploited. Regular scanning can also help you understand your software better, allowing you to make informed decisions about its security. New vulnerabilities are discovered regularly, so continuous scanning is necessary to ensure your software remains secure.

Use a Binary Repository

A binary repository is a storage location where you can keep binary files, the compiled version of your software. Using a binary repository can significantly improve the security of your open source software.

A binary repository allows you to keep track of all the versions of your software. This makes it easier to manage updates and patches, ensuring that you are always using the latest, most secure version of your software.

A binary repository can also help you control access to your software. You can set permissions to determine who can access your software, preventing unauthorized access and potential security threats.

Software Composition Analysis

Software composition analysis (SCA) is a method used to identify open source components within your software and assess their security risks. It provides a comprehensive view of your software's composition, allowing you to understand its security posture better.

SCA tools can identify known vulnerabilities in the open-source components of your software. They can also check for compliance with licensing requirements, ensuring that you are not violating any open-source licenses.

By providing a detailed view of your software's composition, SCA can help you manage your open-source usage effectively. It allows you to make informed decisions about the open-source components you use, enhancing the security and compliance of your software.

Now that we’ve covered the important considerations for using open source software in your projects, let’s review some of the world’s most popular open source software.

Implement GitOps

GitOps is an operational framework that takes DevOps practices a step further, using Git as the single source of truth for managing infrastructure and application configurations. This approach enhances open source security by introducing a more controlled, auditable, and automated deployment process. When implementing GitOps, all changes to the infrastructure and application configurations are made via Git pull requests. These changes are automatically applied to the production environment using continuous deployment (CD) tools. This method ensures that every modification is tracked and reviewed, reducing the risk of unauthorized changes or misconfigurations that could lead to security vulnerabilities. GitOps minimizes the attack surface by limiting direct access to production environments. By enforcing changes through a controlled Git workflow, it ensures that only approved and verified updates are deployed, thereby reducing the chances of introducing vulnerabilities into your software ecosystem.

Learn more in the detailed guide to GitOps

Top Open Source Projects: Content Management Systems

Wordpress

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Official project page: https://wordpress.org/
Repository: https://github.com/WordPress/WordPress
GitHub stars: 18.2K
Run it now in a free Acorn sandbox: Launch Acorn

WordPress is an open source content management system that powers approximately 40% of all websites. It's known for its simplicity, flexibility, and user-friendly interface. With WordPress, you can create any type of website, from a personal blog to a full-fledged e-commerce site.

WordPress has an extensive ecosystem of plugins and themes. With thousands of options to choose from, you can extensively customize your website. And because it's open source, you have the freedom to modify and extend WordPress to suit your specific needs.

Drupal

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Official project page: https://www.drupal.org/
Repository: https://github.com/drupal/drupal
GitHub stars: 4K

Drupal is an open-source content management system (CMS) used to make websites and applications. It's flexible and customizable, allowing you to build and manage different kinds of sites—from simple blogs to complex user communities.

One of the key strengths of Drupal is its scalability. It's designed to handle high-traffic sites and has proven its ability to scale in real-world scenarios at various organizations that manage large volumes of content.

The Drupal community is large and diverse, with hundreds of thousands of active contributors constantly working on enhancing its features and performance. This active participation ensures that Drupal remains a robust platform for web development.

Joomla

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Official project page: https://www.joomla.org/
Repository: https://github.com/joomla/joomla-cms
GitHub stars: 4.4K

Joomla is another open-source CMS that empowers you to create dynamic websites and applications. It offers a balance between ease-of-use and extensibility, making it a popular choice among both beginners and experienced developers.

Joomla offers an application framework that allows developers to create add-ons, extending the power of Joomla beyond a simple CMS. The Joomla community is large and active. They are committed to keeping Joomla user-friendly, powerful, and up-to-date.

Ghost

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Official project page: https://ghost.org/
Repository: https://github.com/TryGhost/Ghost
GitHub stars: 44.4K
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Ghost is an open source blogging platform that's gaining popularity for its focus on simplicity and usability. Unlike WordPress, which has evolved into a full content management system, Ghost remains true to its blogging roots.

Ghost is designed to make blogging as straightforward as possible. Its clean, clutter-free interface lets you focus on your content. And while it may not have as many plugins and themes as WordPress, Ghost offers enough customization options to make your blog distinct.

Strapi

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Official project page: https://strapi.io/
Repository: https://github.com/strapi/strapi
GitHub stars: 57.4K
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Strapi is an open-source headless CMS that allows developers to build, deploy, and manage content-rich applications in a short time. It's built on JavaScript, one of the most popular programming languages, making it a familiar environment for many developers.

As a headless CMS, Strapi decouples the front-end and back-end development. This gives developers the freedom to use any technology stack they prefer for the front-end, while Strapi manages the back-end.

Top Open Source Projects: Container Orchestration

Docker Containers

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Official project page: https://www.docker.com/
Repository: https://github.com/docker/compose
GitHub stars: 31K
Run it now in a free Acorn sandbox: index.docker.io/tybalex/autogptjs-acorn

Docker is an open source platform that automates the deployment of applications inside software containers. It provides an additional layer of abstraction and automation of operating-system-level virtualization on Windows and Linux.

Docker utilizes the resource isolation features of the Linux kernel (such as cgroups and kernel namespaces) and a union-capable file system (like OverlayFS) to allow independent containers to run within a single Linux instance, avoiding the overhead of starting and maintaining virtual machines.

Docker can package and run an application in a loosely isolated environment called a container. This isolation and security allow you to run many containers simultaneously on a given host. Containers are lightweight and contain everything needed to run the application, ensuring that software runs reliably when moved from one computing environment to another.

Learn more in the detailed guide to Docker Containers (coming soon)

Kubernetes

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Official project page: https://kubernetes.io/
Repository: https://github.com/kubernetes/kubernetes
GitHub stars: 103K

Kubernetes is a portable, extensible, open source platform for managing containerized workloads and services. It supports declarative configuration and highly flexible automation. It has a large, rapidly growing ecosystem, with Kubernetes services, support, and tools widely available.

Kubernetes provides a platform for automating deployment, scaling, and operations of application containers across clusters of hosts. Originally developed by Google and donated to the Cloud Native Computing Foundation (CNCF), it offers a solution for container orchestration, increasing the scalability, availability, and efficiency of applications.

**Learn more in these detailed guides:

Openshift Container Platform

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Official project page: https://www.redhat.com/en/technologies/cloud-computing/openshift
Repository: https://github.com/openshift/openshift-docs
GitHub stars: 698

OpenShift is a family of containerization software products developed by Red Hat. Its flagship product is the OpenShift Container Platform—an on-premises platform as a service built around Docker containers, which are orchestrated and managed by Kubernetes on a foundation of Red Hat Enterprise Linux.

OpenShift provides developers with an integrated development environment (IDE) for building and deploying Docker-formatted containers, and then managing them with the open source Kubernetes container orchestration platform. This platform has been built with enterprise requirements like security in mind, offering automated updates and scaling.

Learn more in the detailed guide to the Openshift Container Platform

Rancher

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Official project page: https://www.rancher.com/
Repository: https://github.com/rancher/rancher
GitHub stars: 21.8K

Rancher enables organizations to deploy and manage Kubernetes at scale. It's designed to address the operational and security challenges of managing multiple Kubernetes clusters across different infrastructure providers.

Rancher offers a user-friendly approach to Kubernetes management. It provides a single, consistent interface to deploy and manage all your Kubernetes clusters, regardless of where they are running.

The Rancher community helps make Kubernetes accessible to everyone. Their contributions focus on simplifying the complexities of Kubernetes, making it easier for more organizations to adopt and benefit from this technology.

Top Open Source Projects: Machine Learning and AI

TensorFlow

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Official project page: https://www.tensorflow.org/
Repository: https://github.com/tensorflow/tensorflow
GitHub stars: 179K

TensorFlow is an open source software library for high performance numerical computation. Its flexible architecture allows easy deployment of computation across a variety of platforms (CPUs, GPUs, TPUs), and from desktops to clusters of servers to mobile and edge devices.

Originally developed by researchers and engineers from the Google Brain team, TensorFlow has become popular among developers for machine learning and artificial intelligence projects. It has a broad ecosystem of tools, libraries, and community resources that lets researchers push new experiments in ML/AI and developers build and deploy ML/AI-powered applications.

PyTorch

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Official project page: https://pytorch.org/
Repository: https://github.com/pytorch/pytorch
GitHub stars: 72.8K

PyTorch is an open source machine learning library developed by Facebook's AI Research lab (FAIR). It has gained popularity in the research community for its flexibility, ease of use, and dynamic computational graph. PyTorch's design is intuitive, particularly for those familiar with Python programming, making it a preferred choice for both academic research and development in industrial applications.

One of the key strengths of PyTorch is its user-friendly interface. It offers a straightforward platform for building deep learning models, allowing researchers and developers to focus more on the design aspect of their models rather than the technical intricacies of the library. Its dynamic computational graph, where the graph is built at runtime, offers more flexibility and ease for making changes and debugging. This feature is particularly useful for complex models and novel architectures in research.

Official project page: https://redis.io/
Repository: https://github.com/redis/redis
GitHub stars: 62.3K

Keras

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Official project page: https://keras.io/
Repository: https://github.com/keras-team/keras
GitHub stars: 60.8K

Keras is a high-level neural networks API, written in Python and capable of running on top of TensorFlow, CNTK, or Theano. It was developed with a focus on enabling fast experimentation.

Keras is designed for human beings emphasizing usability and developer experience. Its API is intuitive and easy to experiment with, making it approachable for newcomers while also robust enough for expert practitioners. It provides clear and actionable feedback for user errors and has extensive documentation and developer guides.

OpenCV

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Official project page: https://opencv.org/
Repository: https://github.com/opencv/opencv
GitHub stars: 75.2K

OpenCV (Open Source Computer Vision Library) is an open-source computer vision and machine learning software library. OpenCV was built to provide a common infrastructure for computer vision applications and to accelerate the use of machine perception in commercial products.

The library has more than 2,500 optimized algorithms, which includes a comprehensive set of both classic and state-of-the-art computer vision and machine learning algorithms. These algorithms can be used to detect and recognize faces, identify objects, classify human actions in videos, track camera movements, track moving objects, and extract 3D models of objects.

GPTScript

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Official project page: https://github.com/gptscript-ai/gptscript
Repository: https://github.com/gptscript-ai/gptscript
GitHub stars: 2.4K

GPTScript is a scripting language designed to enable users to automate tasks and interact with a Large Language Model (LLM) using OpenAI. It combines the simplicity of natural language with the power of traditional scripting tools like Bash and Python, as well as the capability to make HTTP service calls. This unique blend allows users to execute a wide range of tasks, from mundane automation to complex database operations, using intuitive language commands.

The language’s primary strength lies in its natural language-based syntax, which significantly reduces the learning curve for new users. This accessibility makes GPTScript an ideal tool for a variety of applications, including retrieval-augmented generation (RAG), task automation, and the creation of agents and assistants. Additionally, it can be used for data analysis and the integration of vision, image, and audio processing tasks into scripts. Another notable feature is its ability to manage memory and construct chatbots.

HuggingFace Transformers

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Official project page: https://huggingface.co/transformers/
Repository: https://github.com/huggingface/transformers
GitHub stars: 124K

HuggingFace Transformers is a library that provides thousands of pre-trained models to perform tasks on texts such as classification, information extraction, question answering, summarization, translation, and text generation in over 100 languages. Its aim is to make state-of-the-art NLP easier to use for everyone.

Transformers provide a straightforward way to use models like BERT, GPT-2, T5, and others. HuggingFace has become a go-to library for anyone working with textual data, thanks to its simplicity, efficiency, and broad community support. Whether you're a researcher, developer, or a company, it offers cutting-edge capabilities with just a few lines of code.

Fast.ai

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Official project page: https://www.fast.ai/
Repository: https://github.com/fastai/fastai
GitHub stars: 25.5K

Fast.ai is a deep learning library that provides high-level components aimed to enable fast experimentation with deep neural networks. It sits on top of PyTorch and is designed to make deep learning more accessible and easier to implement for practitioners.

Fastai's library is structured around best practices with a focus on educational purposes, making it not just a tool for production but also a learning platform for those new to deep learning. It automates many of the tedious aspects of training deep learning models, making the process more intuitive and allowing developers and researchers to move faster through their projects.

Top Open Source Projects: Databases

Redis

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Official project page: https://redis.io/
Repository: https://github.com/redis/redis
GitHub stars: 62.3K\

Redis, which stands for Remote Dictionary Server, is an open source, in-memory data structure store. It is used as a database, cache, and message broker. One of the reasons for Redis's popularity is its versatility. It supports a wide range of data structures, including strings, hashes, lists, and sets.

Redis's in-memory nature allows it to deliver ultra-fast read and write operations. This makes it an appropriate choice for high-performance applications. With numerous contributors from around the world, the Redis community is continually improving and innovating.

PostgreSQL

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Official project page: https://www.postgresql.org/
Repository: https://github.com/postgres/postgres
GitHub stars: 13.6K
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PostgreSQL is an open source relational database system. It is known for its robustness, scalability, and full compliance with SQL standards. PostgreSQL supports a broad array of data types, including complex ones like arrays and hstore (for storing key-value pairs).

One of the key features of PostgreSQL is its extensibility. You can define your own data types, operators, and functions. This allows you to tailor the database system to your specific needs. And like Redis, PostgreSQL has a strong community backing it, ensuring its continuous development and improvement.

MongoDB

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Official project page: https://www.mongodb.com/
Repository: https://github.com/mongodb/mongo
GitHub stars: 24.7K
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MongoDB is an open source NoSQL database that provides high performance, high availability, and easy scalability. It works on the concept of collections and documents, which makes it flexible and adaptable to real-world data.

MongoDB offers the ability to handle large amounts of data with diverse structures. It's suitable for dealing with big data applications and real-time analytics. MongoDB's horizontal scaling capability ensures that as your data grows, your database can grow with it.

MariaDB

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Official project page: https://mariadb.org/
Repository: https://github.com/MariaDB/server
GitHub stars: 5K
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MariaDB is an open source relational database management system that is a fork of MySQL. It was created by the original developers of MySQL after concerns over its acquisition by Oracle Corporation. MariaDB is designed to maintain high compatibility with MySQL, ensuring a drop-in replacement capability with library binary parity and exact matching with MySQL APIs and commands.

MariaDB has a few features that set it apart from MySQL. It includes a variety of storage engines, including high-performance ones like Aria, ColumnStore, and Spider. It also offers advanced replication for scaling.

Cassandra

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Official project page: https://cassandra.apache.org/
Repository: https://github.com/apache/cassandra
GitHub stars: 8.3K

Apache Cassandra is an open source distributed database system designed for managing large amounts of data across many commodity servers, providing high availability with no single point of failure. Cassandra offers robust support for clusters spanning multiple datacenters, with asynchronous masterless replication allowing low latency operations for all clients.

Cassandra's strengths revolve around its ability to handle large amounts of data, its resilient nature, and its exceptional performance. Because it's designed for distributed environments, it's highly scalable and can seamlessly grow with your data.

Top Open Source Projects: Big Data

Hadoop

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Official project page: https://hadoop.apache.org/
Repository: https://github.com/apache/hadoop
GitHub stars: 14K

Apache Hadoop is an open-source framework designed for distributed storage and processing of large data sets across clusters of computers using simple programming models. It is particularly known for its ability to handle petabytes and exabytes of data. Hadoop breaks down big data into smaller pieces to be processed in parallel, significantly speeding up data processing.

A key feature of Hadoop is its Hadoop Distributed File System (HDFS), which allows for high throughput access to application data and is suitable for applications with large data sets. The framework also includes Hadoop YARN, a job scheduling and cluster resource management system, and Hadoop MapReduce, a programming model for large-scale data processing.

Learn more in the detailed guide to Hadoop

Apache Spark

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Official project page: https://spark.apache.org/
Repository: https://github.com/apache/spark
GitHub stars: 37.2K

Apache Spark is an open source, distributed, general-purpose cluster-computing framework. Initially developed at UC Berkeley's AMPLab, Spark provides an interface for programming entire clusters with implicit data parallelism and fault tolerance.

Spark is known for its speed, ease of use, and general-purpose nature. It can run programs up to 100x faster than Hadoop MapReduce in memory, or 10x faster on disk. Spark also supports a wide array of tasks, including SQL queries, streaming data, machine learning, and graph processing.

Learn more in the detailed guides to:

Elasticsearch

Elasticsearch - Strapi - Logos - 1305 x 225px.png Official project page: https://www.elastic.co/elasticsearch/
Repository: https://github.com/elastic/elasticsearch
GitHub stars: 67.3K

Elasticsearch is a highly scalable open-source search engine and analytics engine. It allows you to store, search, and analyze big volumes of data quickly and in near real time. Elasticsearch is generally used as the underlying engine/technology that powers applications with complex search features and requirements.

Elasticsearch uses a document-oriented approach, storing data in JSON format. This makes it easy to store, search, and manage complex data structures. It's built on top of the Apache Lucene library, offering a full-text search engine with a powerful combination of features for search queries.

Elasticsearch is part of the ELK Stack (Elasticsearch, Logstash, Kibana), which is widely used for log analysis in IT environments. This stack provides a powerful platform for searching, analyzing, and visualizing data in real-time.

Note: In 2021 Elasticsearch transitioned from an Apache 2.0 open source license to the SSPL 1.0 license, which is more restrictive. The software is still free and source code is available, but there are some limitations on how it can be deployed in production.

Learn more in the detailed guide to Elasticsearch.

OpenSearch

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Official project page: https://opensearch.org/
Repository: https://github.com/opensearch-project/OpenSearch
GitHub stars: 9.2K

OpenSearch is an open source search and analytics suite derived from Elasticsearch and Kibana. It provides a scalable solution for search, observability, and data analysis across various types of datasets. OpenSearch offers powerful full-text search capabilities, real-time data analysis, and advanced visualization tools.

One of OpenSearch's key strengths is its flexibility and extensibility, allowing users to tailor it to their specific needs. It supports a wide range of plugins and integrations, making it suitable for diverse use cases such as log analytics, security monitoring, and more. The project is actively maintained by a large community, ensuring ongoing improvements and feature additions.

Learn more in the detailed guide to OpenSearch

Kafka

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Official project page: https://kafka.apache.org/
Repository: https://github.com/apache/kafka
GitHub stars: 26.3K

Apache Kafka is an open source streaming platform that provides real-time data feeds. It's designed to handle data streams from multiple sources and deliver them to multiple consumers. Kafka is known for its high throughput, reliability, and replication capabilities, making it a popular choice for big data and real-time analytics applications.

Kafka's distributed architecture ensures that it can handle massive amounts of data. It also provides fault tolerance, ensuring that data feeds remain up and running even in the event of a failure. Kafka's community is active and enthusiastic, continually contributing to its development and refinement.

Splunk

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Official project page: https://www.splunk.com/
Repository: https://github.com/splunk/attack_range
GitHub stars: 1.8K

Splunk is a software platform widely used for monitoring, searching, analyzing, and visualizing machine-generated data in real time. It processes and indexes the data to make it searchable, and then enables users to create graphs, reports, alerts, dashboards, and visualizations.

Although not entirely open source, Splunk offers a free version with limited functionality, popular in the community for data analysis and operational intelligence. It's particularly valued for its ability to make sense of large amounts of unstructured data, providing insights that can drive operational performance and business results.

Learn more in the detailed guide to Splunk Cloud

Slurm

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Official project page: https://www.schedmd.com/
Repository: https://github.com/SchedMD/slurm
GitHub stars: 2.1K

Slurm (Simple Linux Utility for Resource Management) is an open source, fault-tolerant, and highly scalable cluster management and job scheduling system for large and small Linux clusters. Slurm is used by many of the world's supercomputers and computer clusters to manage job scheduling.

Slurm prioritizes scalability and portability. It allocates exclusive and/or non-exclusive access to resources (compute nodes) to users for some duration of time. It also provides a framework for starting, executing, and monitoring work on the set of allocated nodes. Finally, it arbitrates contention for resources by managing a queue of pending work.

Learn more in the detailed guide to Slurm

Top Open Source Projects: Other Notable Mentions

OpenTelemetry

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Official project page: https://opentelemetry.io/
Repository: https://github.com/open-telemetry
GitHub stars: 4K
OpenTelemetry is an open source project that provides a set of APIs, libraries, agents, and instrumentation to enable observability in your applications. It includes tools, APIs, and SDKs that can be used to instrument, generate, collect, and export telemetry data (metrics, logs, and traces) for analysis to understand your software’s performance and behavior.

OpenTelemetry provides a unified standard for telemetry data collection across various programming languages and platforms. This makes it easier for developers to implement observability and maintain consistency in their monitoring practices.

The project supports multiple data sources and export formats, making it adaptable to different monitoring backends such as Prometheus, Jaeger, and Zipkin. It is backed by a large community and achieved Graduated status in the Cloud Native Computing Foundation (CNCF).

Learn more in the detailed guide to the OpenTelemetry.

Zipkin

Official project page: https://zipkin.io/
Repository: https://github.com/openzipkin/zipkin
GitHub stars: 16.9K

Zipkin is an open source distributed tracing system that helps developers monitor and troubleshoot latency issues in microservice architectures. It collects and visualizes trace data, allowing teams to understand the flow of requests through their systems and identify performance bottlenecks.

Zipkin supports various data collection methods and integrates with numerous platforms, making it a versatile tool for observing complex, distributed systems. It provides an intuitive UI for viewing traces and includes powerful features like trace sampling and customizable data storage options. Zipkin is widely used in the industry and is backed by a robust community of contributors.

Learn more in the detailed guide to Zipkin

Vault HashiCorp

Official project page: https://www.vaultproject.io/
Repository: https://github.com/hashicorp/vault
GitHub stars: 30.7K

Vault by HashiCorp is an open source tool designed to securely manage secrets and protect sensitive data. It allows organizations to control access to passwords, API keys, certificates, and other secrets in a centralized and auditable manner. Vault offers robust features like dynamic secrets, encryption as a service, and secret leasing and revocation, making it an essential tool for managing secrets in modern infrastructure.

Vault supports a wide range of authentication methods and provides fine-grained access control through policies. It also offers high availability, scaling to meet the needs of large organizations, and is backed by an active community of contributors and users.

Learn more in the detailed guide to Vault HashiCorp

Additional Guides on Key Open Source Topics

Docker Container

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Complete Guide to Docker Compose
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