List of the Top 15 Free Metadata Management Software in 2025

Clarifai stands out as a prominent AI platform adept at processing image, video, text, and audio data on a large scale. By integrating computer vision, natural language processing, and audio recognition, our platform serves as a robust foundation for developing superior, quicker, and more powerful AI applications. We empower both enterprises and public sector entities to convert their data into meaningful insights. Our innovative technology spans various sectors, including Defense, Retail, Manufacturing, and Media and Entertainment, among others. We assist our clients in crafting cutting-edge AI solutions tailored for applications such as visual search, content moderation, aerial surveillance, visual inspection, and intelligent document analysis. Established in 2013 by Matt Zeiler, Ph.D., Clarifai has consistently been a frontrunner in the realm of computer vision AI, earning recognition by clinching the top five positions in image classification at the prestigious 2013 ImageNet Challenge. With its headquarters located in Delaware, Clarifai continues to drive advancements in AI, supporting a wide array of industries in their digital transformation journeys.

data.world is a cloud-based platform meticulously crafted for modern data ecosystems, facilitating effortless management of updates, migrations, and ongoing maintenance. The straightforward setup process is enhanced by a growing array of pre-built integrations compatible with all leading cloud data warehouses. When quick results are paramount, teams should focus on tackling real business issues instead of wrestling with complicated data management tools. data.world streamlines the experience for all users, not just data specialists, equipping them to obtain clear, accurate, and timely responses to a wide range of business questions. Our platform boasts a cloud-native data catalog that links disparate and distributed data to familiar business concepts, creating an accessible, cohesive knowledge base for everyone. Additionally, in addition to our enterprise offerings, data.world nurtures the largest collaborative open data community worldwide, where participants work together on various projects, including social bot detection and prestigious data journalism endeavors, fostering innovation and collective learning. This vibrant environment not only promotes knowledge sharing but also empowers users to harness data in inventive and meaningful ways, ultimately driving impactful solutions across different sectors.

Facilitate effective data utilization for AI and analytics in a business-centric way through intelligent cataloging, reinforced by proactive governance of metadata and policies. The IBM Watson® Knowledge Catalog emerges as an essential resource for uncovering data, models, and additional assets, significantly improving the self-service exploration experience. Functioning as a cloud-based storage solution for enterprise metadata, it enables the activation of information for applications in AI, machine learning (ML), and deep learning. Users can conveniently access, curate, categorize, and share data and knowledge assets, along with their interrelations, from any location. By effectively organizing, defining, and managing enterprise data, organizations can guarantee that they possess the necessary context to create value for diverse purposes, including meeting regulatory requirements and pursuing data monetization initiatives. Moreover, it maintains data integrity, monitors compliance and audit readiness, and builds client trust through diligent policy management and the adaptive masking of sensitive information. Featuring intuitive dashboards and workflows that can be easily shared with team members or integrated with analytical tools, businesses can efficiently consume and transform data to align with their operational needs. By harnessing these capabilities, organizations can significantly elevate their decision-making processes and foster innovation throughout their operations. Ultimately, this comprehensive approach not only streamlines data management but also empowers teams to respond agilely to market changes.

Hackolade stands at the forefront of data modeling for NoSQL and multi-model databases, offering an extensive array of tools suitable for a wide range of NoSQL databases and APIs. As the sole data modeling solution for platforms such as MongoDB, Neo4j, Cassandra, ArangoDB, BigQuery, Couchbase, Cosmos DB, Databricks, DocumentDB, DynamoDB, Elasticsearch, EventBridge Schema Registry, Glue Data Catalog, HBase, Hive, Firebase/Firestore, JanusGraph, MariaDB, MarkLogic, MySQL, Oracle, PostgreSQL, Redshift, ScyllaDB, Snowflake, SQL Server, Synapse, TinkerPop, YugabyteDB, and others, Hackolade clearly dominates the market. Additionally, it extends its visual modeling capabilities to Avro, JSON Schema, Parquet, Protobuf, Swagger, and OpenAPI, and is continuously expanding its offerings for its physical data modeling engine. Designed with user-friendliness in mind, the software combines simplicity with powerful visualizations, facilitating the adoption of NoSQL technology for users. Its tools empower functional analysts, designers, architects, and DBAs working with NoSQL technology to achieve enhanced transparency and control, which ultimately leads to shorter development cycles, improved application quality, and diminished risks in execution throughout the organization. Furthermore, Hackolade's commitment to innovation ensures that users stay ahead in the rapidly evolving landscape of data management.

Neptune.ai is a powerful platform designed for machine learning operations (MLOps) that streamlines the management of experiment tracking, organization, and sharing throughout the model development process. It provides an extensive environment for data scientists and machine learning engineers to log information, visualize results, and compare different model training sessions, datasets, hyperparameters, and performance metrics in real-time. By seamlessly integrating with popular machine learning libraries, Neptune.ai enables teams to efficiently manage both their research and production activities. Its diverse features foster collaboration, maintain version control, and ensure the reproducibility of experiments, which collectively enhance productivity and guarantee that machine learning projects are transparent and well-documented at every stage. Additionally, this platform empowers users with a systematic approach to navigating intricate machine learning workflows, thus enabling better decision-making and improved outcomes in their projects. Ultimately, Neptune.ai stands out as a critical tool for any team looking to optimize their machine learning efforts.

Decube is an all-encompassing platform for data management tailored to assist organizations with their needs in data observability, data cataloging, and data governance. By delivering precise, trustworthy, and prompt data, our platform empowers organizations to make more informed decisions. Our tools for data observability grant comprehensive visibility throughout the data lifecycle, simplifying the process for organizations to monitor the origin and movement of data across various systems and departments. Featuring real-time monitoring, organizations can swiftly identify data incidents, mitigating their potential disruption to business activities. The data catalog segment of our platform serves as a unified repository for all data assets, streamlining the management and governance of data access and usage within organizations. Equipped with data classification tools, organizations can effectively recognize and handle sensitive information, thereby ensuring adherence to data privacy regulations and policies. Moreover, the data governance aspect of our platform offers extensive access controls, allowing organizations to oversee data access and usage with precision. Our capabilities also enable organizations to produce detailed audit reports, monitor user activities, and substantiate compliance with regulatory standards, all while fostering a culture of accountability within the organization. Ultimately, Decube is designed to enhance data management processes and facilitate informed decision-making across the board.

Break away from the constraints of isolated applications, excessive budgets, and antiquated skill sets by utilizing our cutting-edge data and analytics platform to boost growth. This advanced platform is specifically designed for efficient data management and comprehensive analytics, enabling smooth scaling across diverse technological landscapes. Its innovative architecture is built to understand the movement and transformation of data throughout its lifecycle, which lays the groundwork for developing resilient enterprise AI applications capable of enduring future obstacles. With a highly modular and versatile design, our platform supports a wide array of components, making integration a breeze. The multi-tenant architecture is intentionally crafted to enhance scalability. Moreover, sophisticated data visualization tools streamline the analysis of complex data structures, fostering the development of enterprise AI applications in a user-friendly, low-code predictive environment. Built on a distinctive hybrid multi-cloud framework that employs open-source community software, our platform is not only adaptable and secure but also cost-efficient, making it the perfect option for organizations striving for efficiency and innovation. Additionally, this platform empowers businesses to effectively leverage their data while simultaneously promoting teamwork across departments, nurturing a culture that prioritizes data-informed decision-making for long-term success.

Google Cloud's Dataplex acts as a sophisticated data fabric that enables businesses to efficiently discover, oversee, monitor, and govern their data across multiple platforms such as data lakes, warehouses, and marts, all while ensuring consistent controls that guarantee access to trustworthy data and support extensive analytics and AI projects. By providing a unified interface for managing data, Dataplex simplifies tasks such as data discovery, classification, and metadata enhancement for a range of data types, including structured, semi-structured, and unstructured data located both within Google Cloud and in external settings. It logically organizes data into business-relevant domains via lakes and data zones, thus facilitating easier data curation, tiering, and archiving processes. The platform's centralized security and governance capabilities allow for effective management of policies, comprehensive monitoring, and detailed auditing across disparate data silos, fostering a sense of distributed data ownership while ensuring overarching control. In addition, Dataplex features automated assessments of data quality and lineage tracking, which bolster the trustworthiness and traceability of data, assuring organizations of the reliability of their data-driven choices. By merging these features, Dataplex not only simplifies the intricacies of data management but also fosters improved collaboration among teams dedicated to analytics and AI, ultimately driving innovation and efficiency. This comprehensive approach equips organizations to harness their data assets more effectively in a rapidly evolving digital landscape.

DataHub stands out as a dynamic open-source metadata platform designed to improve data discovery, observability, and governance across diverse data landscapes. It allows organizations to quickly locate dependable data while delivering tailored experiences for users, all while maintaining seamless operations through accurate lineage tracking at both cross-platform and column-specific levels. By presenting a comprehensive perspective of business, operational, and technical contexts, DataHub builds confidence in your data repository. The platform includes automated assessments of data quality and employs AI-driven anomaly detection to notify teams about potential issues, thereby streamlining incident management. With extensive lineage details, documentation, and ownership information, DataHub facilitates efficient problem resolution. Moreover, it enhances governance processes by classifying dynamic assets, which significantly minimizes manual workload thanks to GenAI documentation, AI-based classification, and intelligent propagation methods. DataHub's adaptable architecture supports over 70 native integrations, positioning it as a powerful solution for organizations aiming to refine their data ecosystems. Ultimately, its multifaceted capabilities make it an indispensable resource for any organization aspiring to elevate their data management practices while fostering greater collaboration among teams.

Ataccama offers a transformative approach to data management, significantly enhancing enterprise value. By integrating Data Governance, Data Quality, and Master Data Management into a single AI-driven framework, it operates seamlessly across both hybrid and cloud settings. This innovative solution empowers businesses and their data teams with unmatched speed and security, all while maintaining trust, security, and governance over their data assets. As a result, organizations can make informed decisions with confidence, ultimately driving better outcomes and fostering growth.

This tool is fundamental for managing metadata effectively. In merely five minutes, you can automatically fill your entire catalog! With Data Discovery, you can locate the data you require from any segment of your data ecosystem, ranging from the database itself to the intricate specifics of each field's values. It offers automated documentation sourced from existing data storage, providing premier support for both unstructured and tabular datasets, along with automated governance actions. Data Lineage is another crucial feature, enabling you to investigate the origins of your data and its eventual trajectory. You can assess the impact of changes made, see how they affect both upstream and downstream processes, and visualize the intricate connections and relationships within your data. New API Access is now available, allowing you to manage your data lineage programmatically and ensure your catalog remains up-to-date. You can seamlessly integrate Data Lineage within CICD pipelines to capture values and descriptions directly in your code while analyzing the consequences of any breaking changes. Additionally, a Data Dictionary is provided to help you understand the essential terminology that drives your business, as well as to clearly define the context and scope of these key terms. By using these robust features, organizations can streamline their data management processes, ultimately leading to improved decision-making.

In the current environment driven by data, the search for relevant information often takes more time than the analysis itself. Azure Data Catalog acts as a versatile metadata repository tailored for organizations, streamlining the identification of data resources. This fully-managed platform accommodates a diverse array of users—including analysts, data scientists, and developers—allowing them to register, improve, locate, understand, and leverage various data sources. You can utilize your preferred tools, as Data Catalog aids in the discovery and use of the data you need. Your data remains securely stored in your chosen locations, while Data Catalog assists in effortless access and management through a user-friendly interface. By encouraging broad usage and promoting ongoing value creation within the data ecosystem, Data Catalog enables users to exchange insights, advice, and best practices, fostering a collaborative environment where everyone can gain advantages. This solution not only democratizes the discovery of data assets but also ensures that all users can participate in the process meaningfully. Such a strategy enhances cooperation and contributes to a richer overall data landscape within organizations, ultimately driving innovation and informed decision-making.

Centralpoint has been recognized by Gartner's Magic Quadrant as a key player in the Digital Experience Platform space, serving over 350 clients globally while extending its capabilities beyond traditional Enterprise Content Management. It provides secure user authentication through various methods such as AD/SAML/OpenID and oAuth, enabling self-service interactions for all users. Centralpoint excels in automatically aggregating data from multiple sources and applying sophisticated metadata management according to your specific rules, thus facilitating genuine Knowledge Management. This functionality empowers users to search and connect diverse datasets from any location. Additionally, Centralpoint's Module Gallery stands out as the most comprehensive option available, offering flexibility for installation in both on-premise and cloud environments. Explore our offerings for Automating Metadata and Retention Policy Management to enhance your organizational efficiency. We also provide innovative solutions that streamline the integration of varied data, leveraging the advantages of AI (Artificial Intelligence). Frequently regarded as a practical alternative to SharePoint, Centralpoint not only simplifies migration tools but also delivers secure portal solutions tailored for public websites, intranets, member areas, and extranets. With its extensive features, Centralpoint continues to redefine how organizations manage and utilize their digital experiences.

The Bulk Object Field Creator (BOFC) is a specialized application within force.com, designed to assist developers and administrators in performing Bulk CRUD operations with optimal efficiency and minimal effort. In contrast to traditional Salesforce methods, this app facilitates bulk metadata tasks, providing a more effective approach for the mass creation, deletion, updating, and cloning of objects and fields. By reducing the amount of manual processes required from users, it greatly improves productivity levels. Furthermore, its intuitive interface ensures a smooth user experience, making it an essential resource for handling extensive datasets. This innovative tool not only saves time but also empowers users to focus on more strategic tasks.

Aim functions as an all-encompassing platform designed for documenting every aspect of AI metadata, encompassing experiments and prompts, while providing a user-friendly interface for comparison and analysis, along with a software development kit for executing programmatic queries. This open-source, self-hosted tool is specifically engineered to efficiently handle vast numbers of tracked metadata sequences, numbering in the hundreds of thousands. The primary uses of AI metadata revolve around experiment tracking and prompt engineering, which are essential for optimizing AI performance. Furthermore, Aim features a visually appealing and high-performance interface that not only simplifies the exploration but also enhances the comparison of various training runs and prompt sessions, thereby improving the overall user experience in the field of AI development. With its robust capabilities and user-centric design, Aim emerges as an indispensable asset for professionals working on cutting-edge AI initiatives. Its comprehensive features cater to the diverse needs of AI practitioners, making it a favorite choice in the community.