As of June 2024, the most popular open-source database management system (DBMS) in the world was MySQL, with a ranking score of ****. Oracle was the most popular commercial DBMS at that time, with a ranking score of ****.

Open-Source Database Software Market size was valued at USD 10.00 Billion in 2024 and is projected to reach USD 35.83 Billion by 2032, growing at a CAGR of 20% during the forecast period 2026-2032.

Global Open-Source Database Software Market Drivers

The market drivers for the Open-Source Database Software Market can be influenced by various factors. These may include:

Cost-Effectiveness: Compared to proprietary systems, open-source databases frequently have lower initial expenses, which attracts organizations—especially startups and small to medium-sized enterprises (SMEs) with tight budgets. Flexibility and Customisation: Open-source databases provide more possibilities for customization and flexibility, enabling businesses to modify the database to suit their unique needs and grow as necessary. Collaboration and Community Support: Active developer communities that share best practices, support, and contribute to the continued development of open-source databases are beneficial. This cooperative setting can promote quicker problem solving and innovation. Performance and Scalability: A lot of open-source databases are made to scale horizontally across several nodes, which helps businesses manage expanding data volumes and keep up performance levels as their requirements change. Data Security and Sovereignty: Open-source databases provide businesses more control over their data and allow them to decide where to store and use it, which helps to allay worries about compliance and data sovereignty. Furthermore, open-source code openness can improve security by making it simpler to find and fix problems. Compatibility with Contemporary Technologies: Open-source databases are well-suited for contemporary application development and deployment techniques like microservices, containers, and cloud-native architectures since they frequently support a broad range of programming languages, frameworks, and platforms. Growing Cloud Computing Adoption: Open-source databases offer a flexible and affordable solution for managing data in cloud environments, whether through self-managed deployments or via managed database services provided by cloud providers. This is because more and more organizations are moving their workloads to the cloud. Escalating Need for Real-Time Insights and Analytics: Organizations are increasingly adopting open-source databases with integrated analytics capabilities, like NoSQL and NewSQL databases, as a means of instantly obtaining actionable insights from their data.

Open-Source Database Software Market size was valued at USD 11250.75 million in 2024 and the revenue is expected to grow at a CAGR of 10.75% from 2025 to 2032

The size of the Open Source Time Series Database 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.

Amazon Web Services (AWS) was the most popular cloud provider for the hosting of open source database management systems (DBMSs) as of 2020. Around 45 percent of DBMSs ran on public cloud at that time, and another ** percent ran on hybrid cloud.

The size of the Open-Source Database 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.

Shared database of videos featuring juvenile and adult male rats and adult male mice exploring stationary objects.This dataset includes wide variety of experimental conditions including genetic, pharmacological, and sensory deprivation interventions to explore how active sensing behavior is modulated by different factors. Database of high speed videos of whisking behavior in freely moving rodents.Open source high speed infrared videography database to study principles of active sensing in freely navigating rodents.

Check Market Research Intellect's Open Source Database Market Report, pegged at USD 15 billion in 2024 and projected to reach USD 30 billion by 2033, advancing with a CAGR of 8.8% (2026-2033).Explore factors such as rising applications, technological shifts, and industry leaders.

The size of the Open Source Database Solution 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.

Discover the booming open-source database market! This in-depth analysis reveals key trends, growth drivers, and leading players shaping the future of database solutions, including cloud adoption, market segmentation, and regional analysis (2019-2033). Explore the potential of open-source databases for your business.

Streaming OSS Data Pipeline Market Outlook

According to our latest research, the global Streaming OSS Data Pipeline market size reached USD 4.35 billion in 2024, reflecting robust adoption across diverse industries. The market is set to maintain a strong growth trajectory, with a projected CAGR of 18.2% from 2025 to 2033. By 2033, the Streaming OSS Data Pipeline market is forecasted to achieve a value of USD 22.62 billion. This remarkable expansion is primarily driven by the escalating need for real-time analytics, data integration, and seamless data flow in modern enterprises, as organizations increasingly rely on open-source software (OSS) solutions to manage complex and high-velocity data streams efficiently.

A significant growth factor in the Streaming OSS Data Pipeline market is the surging demand for real-time data processing and analytics. As organizations grapple with ever-increasing data volumes, the ability to capture, process, and analyze data instantaneously has become a strategic imperative. Real-time analytics enable businesses to make faster and more informed decisions, improve customer experiences, and optimize operations. The proliferation of IoT devices, social media platforms, and connected applications has intensified the need for robust streaming data pipelines that can handle massive data flows with low latency. Companies across sectors such as BFSI, healthcare, and retail are leveraging streaming OSS data pipelines to gain actionable insights, detect anomalies, and respond proactively to market changes, thereby fueling market growth.

Another pivotal driver for the Streaming OSS Data Pipeline market is the widespread adoption of cloud computing and hybrid IT environments. Enterprises are increasingly shifting from traditional on-premises infrastructure to cloud-based solutions to achieve scalability, flexibility, and cost-efficiency. Streaming OSS data pipeline solutions are highly compatible with cloud deployments, enabling seamless integration with various cloud services and platforms. This shift not only accelerates data processing capabilities but also supports distributed architectures, allowing organizations to process data closer to the source. Moreover, the open-source nature of these solutions ensures interoperability and vendor neutrality, empowering organizations to avoid vendor lock-in and customize their data pipelines as per evolving business needs.

The growing emphasis on data security, compliance, and governance is also propelling the Streaming OSS Data Pipeline market. With tightening regulations such as GDPR, HIPAA, and CCPA, organizations are under immense pressure to ensure the secure and compliant handling of sensitive data. Streaming OSS data pipeline solutions are increasingly integrating advanced security features, including data encryption, real-time monitoring, and anomaly detection. These capabilities are especially crucial for industries like finance and healthcare, where data breaches can have severe consequences. The ability to monitor data flows in real time and implement robust access controls is driving the adoption of these solutions, as enterprises seek to safeguard their data assets while maintaining agility and compliance.

From a regional perspective, North America continues to dominate the Streaming OSS Data Pipeline market, owing to the presence of leading technology companies, early adoption of advanced analytics, and substantial investments in digital transformation initiatives. Europe follows closely, driven by stringent data privacy regulations and a rapidly growing ecosystem of open-source software contributors. The Asia Pacific region is experiencing the fastest growth, fueled by rapid digitalization, expanding IT infrastructure, and increasing investments by both global and regional players. Latin America and the Middle East & Africa are also witnessing steady adoption, supported by the modernization of enterprise IT landscapes and the growing need for real-time business intelligence. This global momentum underscores the critical role of streaming OSS data pipelines in shaping the future of data-driven enterprises.

Although ** percent of the respondents reported no use of database as a service (DBaaS) in their organizations in 2020, the use of this cloud database technology appears to have increased from 2019 and is expected to increase significantly in the coming years, as the need for streamlining and commoditizing services grows.

Discover the booming open-source software market! This in-depth analysis reveals key trends, growth drivers, and market segmentation from 2019-2033, highlighting leading players like IBM, Oracle, and Intel. Explore the future of OSS and its impact on various industries.

The Open Source Database Solution market is poised for significant expansion, projected to reach an estimated value of $16 billion by 2025, with a robust Compound Annual Growth Rate (CAGR) of 13%. This impressive trajectory is largely fueled by the increasing adoption of cloud-native architectures and the growing demand for cost-effective, flexible, and scalable data management solutions across enterprises of all sizes. Small and Medium-sized Enterprises (SMEs) are increasingly embracing open-source databases to democratize access to advanced data capabilities, while large enterprises are leveraging them for enhanced agility and to avoid vendor lock-in, particularly within hybrid and private cloud environments. The inherent benefits of open-source, such as community support, transparency, and a wealth of customization options, are compelling factors driving this market's upward momentum. Key applications span a wide spectrum, from operational data management to analytical workloads, underscoring the versatility and adaptability of these solutions. The market's growth is further propelled by the continuous innovation within the open-source database ecosystem, with regular updates and the introduction of new features addressing evolving industry needs. Companies like AWS, Google, and Microsoft are actively contributing to and integrating open-source database technologies into their cloud offerings, further solidifying their position and accessibility. However, challenges such as the need for specialized expertise for deployment and maintenance, and concerns around security and data governance in highly regulated industries, present potential restraints. Despite these hurdles, the overarching trend towards data-driven decision-making and the inherent advantages of open-source solutions are expected to outweigh these limitations, ensuring sustained and dynamic market growth throughout the forecast period of 2025-2033. This report provides an in-depth analysis of the Open Source Database Solution Market, projecting a substantial compound annual growth rate (CAGR) within the multi-million dollar valuation range. The study encompasses a comprehensive Study Period of 2019-2033, with the Base Year and Estimated Year set at 2025, and a Forecast Period from 2025-2033, building upon Historical Period data from 2019-2024. This detailed examination will equip stakeholders with actionable insights to navigate this dynamic and rapidly evolving market.

This is a dataset of Vulnerabilities identified in Open-Source Software and reported to National Vulnerability Database (NVD) since January 1, 2010.

Data is updated automatically every month on the first day.

You can use this dataset for performing data analysis and predicting the vulnerability type based on the descriptions provided, making it an ideal project for beginners and intermediates in NLP.

Common Terminologies 1. CVE: Common Vulnerability Enumeration - A unique identifier for all the vulnerabilities reported to NVD. 2. CWE: Common Weakness Enumeration - A unique identifier for all the types of vulnerabilities that can exist in the source code. [For example, CWE-120 stands for Buffer Overflow] For the entire list of CWEs, visit https://cwe.mitre.org/data/index.html 3. CPE: Common Platform Enumeration - https://en.wikipedia.org/wiki/Common_Platform_Enumeration gives a better explanation.

View the code used to generate the dataset on Github

Global Open Source Database Market is segmented by Application (SQL-based_ NoSQL_ Distributed_ In-memory_ Relational), Type (Data Storage_ Web Development_ Cloud-based Applications_ Big Data_ Analytics), and Geography (North America_ LATAM_ West Europe_Central & Eastern Europe_ Northern Europe_ Southern Europe_ East Asia_ Southeast Asia_ South Asia_ Central Asia_ Oceania_ MEA)

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.

Data Open Source V2

## Overview

Data Open Source V2 is a dataset for object detection tasks - it contains Pest Oj6e annotations for 1,490 images.

## Getting Started

You can download this dataset for use within your own projects, or fork it into a workspace on Roboflow to create your own model.

  ## License

  This dataset is available under the [CC BY 4.0 license](https://creativecommons.org/licenses/CC BY 4.0).