Best Data Catalog Software for Okta

Find and compare the best Data Catalog software for Okta in 2026

Use the comparison tool below to compare the top Data Catalog software for Okta on the market. You can filter results by user reviews, pricing, features, platform, region, support options, integrations, and more.

  • 1
    DataHub Reviews
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    A data catalog holds true worth only when it is actively utilized by its users, and achieving that goes beyond mere technical details. DataHub offers a dynamic and engaging catalog that teams depend on in their daily operations. It enables automatic discovery and indexing of data assets across your entire ecosystem—including cloud data warehouses, lakes, databases, business intelligence tools, machine learning platforms, and more—while providing real-time updates as your environment changes. The comprehensive metadata encompasses not only technical schemas but also essential business context such as ownership, documentation, usage trends, interrelations, and quality metrics. With its knowledge graph architecture, DataHub clarifies how data moves through your organization, simplifying impact assessments and root cause analysis. In contrast to static catalogs that quickly become obsolete, DataHub remains up-to-date through automated metadata ingestion and fosters ongoing enhancement via collaborative contributions.
  • 2
    OneTrust Privacy Automation Reviews
    Transparency, choice and control are key to trust. Organizations have the opportunity to leverage these moments to build trust, and provide more valuable experiences. People expect greater control over their data. We offer privacy and data governance automation to help organizations better understand and comply with regulatory requirements. We also operationalize risk mitigation to ensure transparency and choice for individuals. Your organization will be able to achieve data privacy compliance quicker and build trust. Our platform helps to break down silos between processes, workflows, teams, and people to operationalize regulatory compliance. It also allows for trusted data use. Building proactive privacy programs that are rooted in global best practice and not just reacting to individual regulations is possible. To drive mitigation and risk-based decision-making, gain visibility into unknown risks. Respect individual choice and integrate privacy and security by default in the data lifecycle.
  • 3
    Matia Reviews
    Matia serves as a comprehensive DataOps platform aimed at streamlining contemporary data management by merging essential functions into a cohesive system. By integrating ETL, reverse ETL, data observability, and a data catalog, it removes the reliance on various isolated tools, thereby simplifying the challenges associated with managing disjointed data environments. This platform empowers teams to efficiently and reliably transfer data from diverse sources into data warehouses, utilizing sophisticated ingestion features that include real-time updates and effective error management. Furthermore, it facilitates the return of dependable data to operational tools for practical business applications. Matia prioritizes inherent observability throughout the data pipeline, offering capabilities such as monitoring, anomaly detection, and automated quality assessments to maintain data integrity and reliability, ultimately preventing potential issues from affecting downstream processes. As a result, organizations can achieve a more streamlined workflow and enhanced data utilization across their operations.
  • 4
    Acryl Data Reviews
    Bid farewell to abandoned data catalogs. Acryl Cloud accelerates time-to-value by implementing Shift Left methodologies for data producers and providing an easy-to-navigate interface for data consumers. It enables the continuous monitoring of data quality incidents in real-time, automating anomaly detection to avert disruptions and facilitating swift resolutions when issues arise. With support for both push-based and pull-based metadata ingestion, Acryl Cloud simplifies maintenance, ensuring that information remains reliable, current, and authoritative. Data should be actionable and operational. Move past mere visibility and leverage automated Metadata Tests to consistently reveal data insights and identify new opportunities for enhancement. Additionally, enhance clarity and speed up resolutions with defined asset ownership, automatic detection, streamlined notifications, and temporal lineage for tracing the origins of issues while fostering a culture of proactive data management.
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