Thanks to a variety of software services, it has never been easier to produce, manage and publish Linked Open Data. But until now, there has been a lack of an accessible overview to help researchers make the right choice for their use case. This dataset release will be regularly updated to reflect the latest data published in a comparison table developed in Google Sheets [1]. The comparison table includes the most commonly used LOD management software tools from NFDI4Culture to illustrate what functionalities and features a service should offer for the long-term management of FAIR research data, including:

• ConedaKOR
• LinkedDataHub
• Metaphacts
• Omeka S
• ResearchSpace
• Vitro
• Wikibase
• WissKI

The table presents two views based on a comparison system of categories developed iteratively during workshops with expert users and developers from the respective tool communities. First, a short overview with field values coming from controlled vocabularies and multiple-choice options; and a second sheet allowing for more descriptive free text additions. The table and corresponding dataset releases for each view mode are designed to provide a well-founded basis for evaluation when deciding on a LOD management service. The Google Sheet table will remain open to collaboration and community contribution, as well as updates with new data and potentially new tools, whereas the datasets released here are meant to provide stable reference points with version control.

The research for the comparison table was first presented as a paper at DHd2023, Open Humanities – Open Culture, 13-17.03.2023, Trier and Luxembourg [2].

[1] Non-editing access is available here: docs.google.com/spreadsheets/d/1FNU8857JwUNFXmXAW16lgpjLq5TkgBUuafqZF-yo8_I/edit?usp=share_link To get editing access contact the authors.

[2] Full paper will be made available open access in the conference proceedings.

Discover the explosive growth of the open-source big data tools market, projected at a 18% CAGR to reach $55.7 billion by 2033. This in-depth analysis explores key drivers, trends, restraints, and regional market shares, highlighting leading companies and applications. Learn how open-source solutions are revolutionizing data management and analysis.

The open-source big data tools market is experiencing robust growth, driven by the increasing need for scalable, cost-effective, and flexible data management and analysis solutions across diverse sectors. The market, estimated at $15 billion in 2025, is projected to exhibit a Compound Annual Growth Rate (CAGR) of 18% from 2025 to 2033. This significant expansion is fueled by several key factors. Firstly, the rising volume and velocity of data generated across industries necessitates sophisticated tools capable of handling massive datasets efficiently. Secondly, the cost-effectiveness of open-source solutions compared to proprietary alternatives is a major attraction for businesses of all sizes, particularly startups and SMEs. Thirdly, the active and collaborative open-source community ensures continuous innovation and improvement in these tools, making them highly adaptable to evolving technological landscapes. The increasing adoption of cloud computing further contributes to market growth, as open-source tools seamlessly integrate with cloud platforms. Growth is segmented across various tools, with data analysis tools experiencing the highest demand due to the growing focus on data-driven decision-making. Key application areas include banking, manufacturing, and government, reflecting the wide applicability of these tools across sectors. While geographical distribution is diverse, North America and Europe currently hold significant market share, though rapid growth is anticipated in the Asia-Pacific region driven by increasing digitalization and adoption of advanced analytics. However, the market faces challenges including the complexity of implementation and maintenance of some open-source tools, requiring specialized expertise, and the need for robust security measures to protect sensitive data. Despite these hurdles, the inherent advantages of cost-effectiveness, flexibility, and community support position the open-source big data tools market for sustained and considerable expansion in the coming years.

The size of the Open Source Container Management Software market was valued at USD XXX million in 2023 and is projected to reach USD XXX million by 2032, with an expected CAGR of XX% during the forecast period.

The open-source project management software market is experiencing robust growth, driven by increasing demand for flexible, customizable, and cost-effective solutions across diverse industries. The market, estimated at $2.5 billion in 2025, is projected to exhibit a Compound Annual Growth Rate (CAGR) of 15% from 2025 to 2033. This growth is fueled by several key factors. Firstly, the rising adoption of agile methodologies and DevOps practices necessitates tools that facilitate collaboration and transparency, aligning perfectly with the collaborative nature of open-source platforms. Secondly, concerns regarding vendor lock-in and data privacy are driving organizations, particularly SMEs, towards open-source alternatives that offer greater control and flexibility. Finally, the extensive community support and continuous development inherent in open-source projects ensure ongoing innovation and improvement, attracting a wide range of users. The SaaS-based segment currently dominates the market due to its ease of deployment and accessibility, while large enterprises are increasingly adopting open-source solutions to manage complex projects and integrate them seamlessly with their existing infrastructure. Geographic distribution shows strong growth across North America and Europe, driven by high technological adoption rates and established IT infrastructure. However, emerging markets in Asia-Pacific and the Middle East & Africa are also witnessing significant growth, fueled by increasing digitalization and a rising number of tech-savvy businesses. This growth is further enhanced by the continual development and refinement of existing platforms and the emergence of innovative features focusing on areas such as AI-powered project planning and predictive analytics. The competitive landscape is characterized by a mix of established players and emerging contenders, with various solutions catering to specific niche requirements. While some platforms like Mattermost and GitHub cater to a broader user base, others such as ProjeQtOr or GanttProject focus on specialized functionality. This fragmentation presents opportunities for new entrants to innovate and fill market gaps with highly specialized open-source project management solutions. The long-term outlook remains positive, as organizations continue to embrace open-source solutions as a reliable and adaptable method of managing their projects, potentially leading to even higher market penetration in the coming years. The increasing complexity of projects and the rising need for greater collaboration will only serve to further enhance the adoption of these software tools.

Discover the booming open-source big data tools market! This comprehensive analysis reveals key trends, growth drivers, and regional insights for 2025-2033, featuring leading companies like MongoDB and Apache. Learn about market segmentation, application areas, and future projections.

We present the data collected as part of the Open-source Complex Ecosystem And Networks (OCEAN) partnership between Google Open Source and the University of Vermont. This includes mailing list emails with standardized format spanning the past three decades from fourteen mailing lists across four different open source communities: Python, Angular, Node.js, and the Go language.This data is presented in the following publication: Warrick, M., Rosenblatt, S. F., Young, J. G., Casari, A., Hébert-Dufresne, L., & Bagrow, J. P. (2022). The OCEAN mailing list data set: Network analysis spanning mailing lists and code repositories. In 2022 IEEE/ACM 19th International Conference on Mining Software Repositories (MSR). IEEE.

The size of the Open Source Project Management Software market was valued at USD XXX million in 2024 and is projected to reach USD XXX million by 2033, with an expected CAGR of XX% during the forecast period.

Open Source Vulnerability Management Market Outlook

According to our latest research, the Open Source Vulnerability Management market size reached USD 1.68 billion globally in 2024, demonstrating a robust growth trajectory. The market is projected to expand at a CAGR of 13.2% from 2025 to 2033, with the total market size forecasted to reach USD 4.66 billion by 2033. This impressive growth is attributed to the escalating adoption of open source software across diverse industries, coupled with the rising sophistication and frequency of cyber-attacks targeting open source vulnerabilities. As organizations increasingly rely on open source components for agility and innovation, the demand for advanced vulnerability management solutions has become a critical priority for ensuring robust cybersecurity postures.

One of the primary growth drivers for the Open Source Vulnerability Management market is the exponential rise in the utilization of open source software within enterprise environments. Open source components now underpin a significant portion of modern software applications, offering flexibility, cost savings, and accelerated development cycles. However, this widespread adoption introduces complex security challenges, as open source libraries and dependencies are frequently targeted by threat actors. The need for effective vulnerability management solutions has become paramount, prompting organizations to invest heavily in tools that can identify, assess, and remediate vulnerabilities in open source codebases. The growing awareness of supply chain risks and regulatory compliance requirements further amplifies the demand for comprehensive open source vulnerability management platforms.

Another significant factor contributing to market growth is the increasing regulatory scrutiny and evolving data protection mandates across various regions. Governments and industry bodies are enacting stringent cybersecurity standards, compelling organizations to enhance their vulnerability management practices. The introduction of regulations such as the General Data Protection Regulation (GDPR), the California Consumer Privacy Act (CCPA), and various sector-specific guidelines has heightened the focus on proactive vulnerability detection and remediation. Enterprises are prioritizing investments in open source vulnerability management solutions to not only safeguard sensitive data but also to avoid costly penalties and reputational damage resulting from breaches. As regulatory landscapes continue to evolve, organizations are expected to further integrate automated vulnerability management tools into their security operations.

The rapid advancement of technologies such as artificial intelligence (AI), machine learning, and automation is also playing a pivotal role in shaping the Open Source Vulnerability Management market. Modern solutions are leveraging AI-driven analytics to provide real-time threat intelligence, predictive risk assessments, and automated remediation workflows. This technological evolution enables organizations to address vulnerabilities at scale, reduce response times, and optimize resource allocation. The integration of AI-powered capabilities is particularly beneficial for large enterprises managing complex IT infrastructures and diverse open source portfolios. As digital transformation initiatives accelerate and cyber threats become more sophisticated, the adoption of next-generation vulnerability management solutions is set to surge, further propelling market expansion.

From a regional perspective, North America continues to dominate the Open Source Vulnerability Management market due to the presence of leading technology companies, a mature cybersecurity ecosystem, and high awareness of open source security risks. Europe is rapidly emerging as a key growth region, driven by stringent data protection regulations and increasing investments in cybersecurity infrastructure. The Asia Pacific region is witnessing significant momentum, fueled by rapid digitalization, expanding IT sectors, and a growing emphasis on securing open source assets. Latin America and the Middle East & Africa are also experiencing steady growth, albeit at a slower pace, as organizations in these regions gradually recognize the importance of proactive vulnerability management in safeguarding their digital assets.

The global Data Base Management Systems market was valued at USD 50.5 billion in 2022 and is projected to reach USD 120.6 Billion by 2030, registering a CAGR of 11.5 % for the forecast period 2023-2030. Factors Affecting Data Base Management Systems Market Growth

Growing inclination of organizations towards adoption of advanced technologies like cloud-based technology favours the growth of global DBMS market

The cloud-based data base management system solutions offer the organizations with an ability to scale their database infrastructure up or down as per requirement. In a crucial business environment data volume can vary over time. Here, the cloud allows organizations to allocate resources in a dynamic and systematic manner, thereby, ensuring optimal performance without underutilization. In addition, these cloud-based solutions are cost-efficient. As, these cloud-based DBMS solutions eliminate the need for companies to maintain and invest in physical infrastructure and hardware. It helps in reducing ongoing operational costs and upfront capital expenditures. Organizations can choose pay-as-you-go pricing models, where they need to pay only for the resources they consume. Therefore, it has been a cost-efficient option for both smaller businesses and large-enterprises. Moreover, the cloud-based data base management system platforms usually come with management tools which streamline administrative tasks such as backup, provisioning, recovery, and monitoring. It allows IT teams to concentrate on more of strategic tasks rather than routine maintenance activities, thereby, enhancing operational efficiency. Whereas, these cloud-based data base management systems allow users to remote access and collaboration among teams, irrespective of their physical locations. Thus, in regards with today's work environment, which focuses on distributed and remote workforces. These cloud-based DBMS solution enables to access data and update in real-time through authorized personnel, allowing collaboration and better decision-making. Thus, owing to all the above factors, the rising adoption of advanced technologies like cloud-based DBMS is favouring the market growth.

Availability of open-source solutions is likely to restrain the global data base management systems market growth

Open-source data base management system solutions such as PostgreSQL, MongoDB, and MySQL, offer strong functionality at minimal or no licensing costs. It makes open-source solutions an attractive option for companies, especially start-ups or smaller businesses with limited budgets. As these open-source solutions offer similar capabilities to various commercial DBMS offerings, various organizations may opt for this solutions in order to save costs. The open-source solutions may benefit from active developer communities which contribute to their development, enhancement, and maintenance. This type of collaborative environment supports continuous innovation and improvement, which results into solutions that are slightly competitive with commercial offerings in terms of performance and features. Thus, the open-source solutions create competition for commercial DBMS market, they thrive in the market by offering unique value propositions, addressing needs of organizations which prioritize professional support, seamless integration into complex IT ecosystems, and advanced features. Introduction of Data Base Management Systems

A Database Management System (DBMS) is a software which is specifically designed to organize and manage data in a structured manner. This system allows users to create, modify, and query a database, and also manage the security and access controls for that particular database. The DBMS offers tools for creating and modifying data models, that define the structure and relationships of data in a database. This system is also responsible for storing and retrieving data from the database, and also provide several methods for searching and querying the data. The data base management system also offers mechanisms to control concurrent access to the database, in order to ensure that number of users may access the data. The DBMS provides tools to enforce security constraints and data integrity, such as the constraints on the value of data and access controls that restricts who can access the data. The data base management system also provides mechanisms for recovering and backing up the data when a system failure occurs....

Discover the booming open-source cloud management platform market! This in-depth analysis reveals key trends, growth drivers, and regional market share projections for 2025-2033, featuring prominent players like OpenStack and Apache CloudStack. Learn about market size, CAGR, and segmentation across deployment models and licensing. Maximize your cloud strategy with this comprehensive guide.

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Government Open Data Management Platform Market Size 2025-2029

The government open data management platform market size is valued to increase by USD 189.4 million, at a CAGR of 12.5% from 2024 to 2029. Rising demand for digitalization in government operations will drive the government open data management platform market.

Market Insights

North America dominated the market and accounted for a 38% growth during the 2025-2029.
By End-user - Large enterprises segment was valued at USD 108.50 million in 2023
By Deployment - On-premises segment accounted for the largest market revenue share in 2023

Market Size & Forecast

Market Opportunities: USD 138.56 million 
Market Future Opportunities 2024: USD 189.40 million
CAGR from 2024 to 2029 : 12.5%

Market Summary

The market witnesses significant growth due to the increasing demand for digitalization in government operations. Open data management platforms enable governments to make large volumes of data available to the public in a machine-readable format, fostering transparency and accountability. The adoption of advanced technologies such as artificial intelligence (AI) and machine learning (ML) in these platforms enhances data analysis capabilities, leading to more informed decision-making. However, data privacy concerns remain a major challenge in the open data management market. Governments must ensure the protection of sensitive information while making data publicly available. A real-world business scenario illustrating the importance of open data management platforms is supply chain optimization in the public sector.
By sharing data related to procurement, logistics, and inventory management, governments can streamline their operations and improve efficiency. For instance, a city government could share real-time traffic data to optimize public transportation routes, reducing travel time and improving overall service delivery. Despite these benefits, it is crucial for governments to address data security concerns and establish robust data management policies to ensure the safe and effective use of open data platforms.

What will be the size of the Government Open Data Management Platform Market during the forecast period?

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The market continues to evolve, with recent research indicating a significant increase in data reuse initiatives among government agencies. The use of open data platforms in the public sector has grown by over 25% in the last two years, driven by a need for transparency and improved data-driven decision making. This trend is particularly notable in areas such as compliance and budgeting, where accurate and accessible data is essential. Data replication strategies, data visualization libraries, and data portal design are key considerations for government agencies looking to optimize their open data management platforms.
Effective data discovery tools and metadata schema design are crucial for ensuring data silos are minimized and data usage patterns are easily understood. Data privacy regulations, such as GDPR and HIPAA, also require robust data governance frameworks and data security audits to maintain data privacy and protect against breaches. Data access logs, data consistency checks, and data quality dashboards are essential components of any open data management platform, ensuring data accuracy and reliability. Data integration services and data sharing platforms enable seamless data exchange between different agencies and departments, while data federation techniques allow for data to be accessed in its original source without the need for data replication.
Ultimately, these strategies contribute to a more efficient and effective data lifecycle, allowing government agencies to make informed decisions and deliver better services to their constituents.

Unpacking the Government Open Data Management Platform Market Landscape

The market encompasses a range of solutions designed to facilitate the efficient and secure handling of data throughout its lifecycle. According to recent studies, organizations adopting data lifecycle management practices experience a 30% reduction in data processing costs and a 25% improvement in ROI. Performance benchmarking is crucial for ensuring optimal system scalability, with leading platforms delivering up to 50% faster query response times than traditional systems. Data anonymization techniques and data modeling methods enable compliance with data protection regulations, while open data standards streamline data access and sharing. Data lineage tracking and metadata management are essential for maintaining data quality and ensuring data interoperability. API integration strategies and data transformation methods enable seamless data enrichment processes and knowledge graph implementation. Data access control, data versioning, and data security protocols

Discover the booming open-source big data tools market! This comprehensive analysis reveals key trends, drivers, and restraints shaping this $15 billion (2025 est.) sector. Explore market segmentation, leading companies, and regional growth projections through 2033. Learn how open-source solutions are transforming data management and analysis across various industries.

Open Source Compliance AI Market Outlook

According to our latest research, the global Open Source Compliance AI market size reached USD 1.42 billion in 2024, with a robust Compound Annual Growth Rate (CAGR) of 21.8% observed over the past year. This market is primarily driven by the exponential growth in open source software adoption, increasing regulatory requirements, and the rising complexity of software supply chains. By leveraging this CAGR, the market is forecasted to attain a value of USD 9.86 billion by 2033, highlighting the significant momentum and transformative potential of AI-driven compliance solutions in the global software ecosystem.

The primary growth factor fueling the Open Source Compliance AI market is the widespread adoption of open source components across diverse industries. As organizations increasingly integrate open source software to accelerate innovation and reduce development costs, the need for robust compliance becomes paramount. Open source licenses come with various obligations, and failure to comply can result in legal and financial repercussions. AI-powered compliance tools automate the discovery, classification, and management of open source components, ensuring that organizations remain compliant with licensing terms. This automation not only reduces manual workloads but also enhances accuracy and scalability, making it an indispensable asset for enterprises managing complex software portfolios.

Another significant driver is the escalating threat landscape associated with open source vulnerabilities. Open source components, while beneficial, often introduce security risks if not properly managed. Recent high-profile breaches have underscored the importance of proactive vulnerability management, driving demand for AI-based solutions that can identify, assess, and remediate security risks in real time. The integration of AI in compliance platforms enables continuous monitoring and rapid response to emerging threats, thereby safeguarding organizational assets and maintaining trust with stakeholders. This proactive approach to security and compliance is becoming a critical differentiator for enterprises operating in regulated environments.

In addition to compliance and security, regulatory pressures are intensifying across industries such as BFSI, healthcare, and government. Governments and regulatory bodies are introducing stringent requirements for software transparency, data privacy, and supply chain security. AI-driven compliance solutions empower organizations to automate audit trails, generate comprehensive reports, and demonstrate adherence to regulatory standards. This capability not only streamlines internal processes but also facilitates smoother interactions with auditors and regulators. As regulatory landscapes evolve, the agility and intelligence offered by Open Source Compliance AI solutions will be crucial for organizations aiming to maintain competitive advantage and operational resilience.

In the realm of Open Source Governance for Security, organizations are increasingly recognizing the importance of structured frameworks to manage and secure open source components. As the adoption of open source software continues to rise, so do the associated security risks. Effective governance involves not only identifying and mitigating vulnerabilities but also ensuring compliance with licensing terms and regulatory requirements. By implementing comprehensive governance strategies, enterprises can safeguard their software supply chains, protect intellectual property, and maintain the integrity of their systems. This approach not only enhances security but also fosters a culture of transparency and accountability, which is crucial in today's digital landscape.

From a regional perspective, North America currently leads the Open Source Compliance AI market, driven by a mature technology ecosystem, early adoption of AI, and a high concentration of software-driven enterprises. Europe follows closely, propelled by rigorous data protection laws such as GDPR and a growing emphasis on digital sovereignty. Meanwhile, the Asia Pacific region is witnessing rapid growth due to increased digital transformation initiatives and expanding software development activities. Latin America and the Middle East & Africa are emerging markets, with increasing awarenes

As of June 2024, the most popular database management system (DBMS) worldwide was Oracle, with a ranking score of *******; MySQL and Microsoft SQL server rounded out the top three. Although the database management industry contains some of the largest companies in the tech industry, such as Microsoft, Oracle and IBM, a number of free and open-source DBMSs such as PostgreSQL and MariaDB remain competitive. Database Management Systems As the name implies, DBMSs provide a platform through which developers can organize, update, and control large databases. Given the business world’s growing focus on big data and data analytics, knowledge of SQL programming languages has become an important asset for software developers around the world, and database management skills are seen as highly desirable. In addition to providing developers with the tools needed to operate databases, DBMS are also integral to the way that consumers access information through applications, which further illustrates the importance of the software.

The study aims to observe different functions, facilities and features of Open source software: Koha and NewGen Lib. Through analyses of both software’s have been done with latest techniques to evaluate their working and make available a suitable choice for various libraries to opt integrated library management software. Both types of software are web-enabled and support library automation, but Koha has more specific characteristics of open source ILMS than New Gen Lib. In such a situation, the Open source software has given the opportunity to cut budgets on their software and spend budgets at other places. This paper discusses the Integrated Library Management System with special reference koha and New Gen Lib open source software.

In view of the ubiquitous mobile-app concept that has taken hold over the past decade, whereby distinct, single purpose, modular applications are developed and deployed in a shared user interface (i.e. the phone in your pocket), we have created open source cyberinfrastructure that mimics this paradigm for developing and deploying environmental web applications using open source tools and cloud computing services. This cyberinfrastructure integrates HydroShare for cloud-based data storage and app cataloging, together with Tethys Platform for Python/Django based app development. HydroShare is an open source web-based data management system for climate and water data that is includes a web-services application programmer interface (API) to allow third party programmers to access and use its data resources. We have created a metadata management structure within HydroShare for cataloging, discovering, and sharing web apps. Tethys Platform is an open source software package based on the Django framework, Python programming language, Geoserver, PostgreSQL, OpenLayers and other open source technologies. The Tethys software development kit allows users to create web apps that are presented in a common portal for visualizing, analyzing and modelling environmental data. We will introduce this new cyberinfrastructure through a combination of architecture design and demonstration, and will provide attendees the essential concepts for building their own web apps using these tools.

This survey investigates Research Data Management (RDM) practices across five Swiss higher education institutions, including EPFL, ETH Zürich, Eawag, FHNW, and DaSCH, with the goal of gathering insights into how researchers manage data and code throughout the lifecycle of their projects, as well as using such findings to inform academic services related to RDM for researchers. Previous surveys, conducted at EPFL in 2017, 2019, and 2021, primarily focused on the planning and publishing stages of the research data lifecycle, such as data management planning and open data dissemination. The 2023 edition expanded to other institutes and places a stronger emphasis on Active Data Management, particularly during research projects, including a range of topics such as:

Storage and backup solutions

Data and code sharing platforms

Documentation and metadata usage

Compliance with legal and ethical standards

Long-term data preservation strategies

Use of open formats and open-source software

Adoption of Data Management Plans (DMPs)

This dataset was collected using the SurveyHero platform in compliance with GDPR and Swiss FADP regulations. enuvo GmbH acted as the data processor under a signed Data Processing Agreement. No personal identifiable information was purposefully collected, and data has been aggregated to further ensure respondents’ privacy.

Included in this dataset:

A CSV and XLSX file with the aggregated, anonymized data from the survey.

Two PDF files containing graphical representations of the survey results, automatically generated by the SurveyHero platform in portrait and landscape mode.

A README file providing context.

This dataset is made openly available under the CC-BY 4.0 license. Users are encouraged to reuse it with appropriate attribution.