List of the Top 3 Metadata Management Software for Redash in 2026

Reviews and comparisons of the top Metadata Management software with a Redash integration


Below is a list of Metadata Management software that integrates with Redash. Use the filters above to refine your search for Metadata Management software that is compatible with Redash. The list below displays Metadata Management software products that have a native integration with Redash.
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    DataHub Reviews & Ratings

    DataHub

    DataHub

    Revolutionize data management with real-time visibility and flexibility.
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    Metadata serves as the essential framework for contemporary data systems, and how well it is managed can significantly impact the clarity or confusion of your operations. DataHub delivers robust, enterprise-level metadata management that can efficiently scale from thousands to millions of entities while ensuring speed and ease of use. You can import metadata from over 100 different sources using adaptable push and pull methods, standardize it into a cohesive graph model, and access it through high-performance APIs. DataHub's metadata structure is designed for expansion—allowing you to incorporate custom attributes, entity types, and relationships without needing to modify the underlying code. Monitor the evolution of metadata with comprehensive versioning and audit trails, gaining insights into changes in schemas, ownership, and policies over time. Furthermore, automatically propagate metadata across interconnected entities; for instance, when you tag a dataset, those tags will seamlessly transfer to associated dashboards.
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    OpenMetadata Reviews & Ratings

    OpenMetadata

    OpenMetadata

    "Centralize, discover, and govern your metadata effortlessly."
    OpenMetadata functions as a holistic, open platform designed to integrate metadata, enhancing data discovery, observability, and governance through a unified interface. Leveraging a Unified Metadata Graph and over 80 pre-built connectors, it consolidates metadata from diverse sources including databases, pipelines, BI tools, and ML systems, which provides teams with a rich context to efficiently search, filter, and visualize their organizational assets. The platform is constructed on an API- and schema-first framework that enables flexible customization of metadata entities and relationships, allowing businesses to define their metadata architecture with accuracy. With just four core system components, OpenMetadata is designed for easy installation and operation, delivering scalable performance that allows both technical and non-technical users to collaborate effectively on tasks related to discovery, lineage tracking, quality assurance, observability, collaboration, and governance without requiring complex infrastructure. This adaptability positions it as an essential asset for organizations striving to maximize the potential of their data resources. Moreover, its user-friendly design fosters a collaborative environment where diverse teams can engage with data insights more intuitively.
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    Acryl Data Reviews & Ratings

    Acryl Data

    Acryl Data

    Transform data management with intuitive insights and automation.
    Address the challenge of neglected data catalogs with Acryl Cloud, which enhances the realization of value through Shift Left strategies tailored for data creators while providing an intuitive interface for users. This platform allows for the immediate identification of data quality concerns, automates anomaly detection to prevent future complications, and supports quick resolutions when issues do crop up. Acryl Cloud supports both push and pull methods for ingesting metadata, simplifying upkeep while ensuring the information remains trustworthy, up-to-date, and thorough. For smooth operations, data should work effortlessly. Go beyond basic visibility by utilizing automated Metadata Tests that continually uncover insights and highlight new avenues for improvement. By establishing clear asset ownership and applying automatic detection, efficient notifications, and temporal lineage for tracing the origins of issues, organizations can reduce confusion and shorten resolution times. Consequently, this leads to a more streamlined and productive data management framework, fostering a culture of continuous improvement and adaptability.
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