Best Data Validation Tools for Linux of 2025

Find and compare the best Data Validation tools for Linux in 2025

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

  • 1
    DataBuck Reviews
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    Big Data Quality must always be verified to ensure that data is safe, accurate, and complete. Data is moved through multiple IT platforms or stored in Data Lakes. The Big Data Challenge: Data often loses its trustworthiness because of (i) Undiscovered errors in incoming data (iii). Multiple data sources that get out-of-synchrony over time (iii). Structural changes to data in downstream processes not expected downstream and (iv) multiple IT platforms (Hadoop DW, Cloud). Unexpected errors can occur when data moves between systems, such as from a Data Warehouse to a Hadoop environment, NoSQL database, or the Cloud. Data can change unexpectedly due to poor processes, ad-hoc data policies, poor data storage and control, and lack of control over certain data sources (e.g., external providers). DataBuck is an autonomous, self-learning, Big Data Quality validation tool and Data Matching tool.
  • 2
    QuerySurge Reviews
    Top Pick
    QuerySurge is the smart Data Testing solution that automates the data validation and ETL testing of Big Data, Data Warehouses, Business Intelligence Reports and Enterprise Applications with full DevOps functionality for continuous testing. Use Cases - Data Warehouse & ETL Testing - Big Data (Hadoop & NoSQL) Testing - DevOps for Data / Continuous Testing - Data Migration Testing - BI Report Testing - Enterprise Application/ERP Testing Features Supported Technologies - 200+ data stores are supported QuerySurge Projects - multi-project support Data Analytics Dashboard - provides insight into your data Query Wizard - no programming required Design Library - take total control of your custom test desig BI Tester - automated business report testing Scheduling - run now, periodically or at a set time Run Dashboard - analyze test runs in real-time Reports - 100s of reports API - full RESTful API DevOps for Data - integrates into your CI/CD pipeline Test Management Integration QuerySurge will help you: - Continuously detect data issues in the delivery pipeline - Dramatically increase data validation coverage - Leverage analytics to optimize your critical data - Improve your data quality at speed
  • 3
    iceDQ Reviews

    iceDQ

    Torana

    $1000
    iCEDQ, a DataOps platform that allows monitoring and testing, is a DataOps platform. iCEDQ is an agile rules engine that automates ETL Testing, Data Migration Testing and Big Data Testing. It increases productivity and reduces project timelines for testing data warehouses and ETL projects. Identify data problems in your Data Warehouse, Big Data, and Data Migration Projects. The iCEDQ platform can transform your ETL or Data Warehouse Testing landscape. It automates it from end to end, allowing the user to focus on analyzing the issues and fixing them. The first edition of iCEDQ was designed to validate and test any volume of data with our in-memory engine. It can perform complex validation using SQL and Groovy. It is optimized for Data Warehouse Testing. It scales based upon the number of cores on a server and is 5X faster that the standard edition.
  • 4
    Ataccama ONE Reviews
    Ataccama is a revolutionary way to manage data and create enterprise value. Ataccama unifies Data Governance, Data Quality and Master Data Management into one AI-powered fabric that can be used in hybrid and cloud environments. This gives your business and data teams unprecedented speed and security while ensuring trust, security and governance of your data.
  • 5
    OpenRefine Reviews
    OpenRefine, which was formerly known as Google Refine, serves as an exceptional resource for managing chaotic data by enabling users to clean it, convert it between different formats, and enhance it with external data and web services. This tool prioritizes your privacy, as it operates exclusively on your local machine until you decide to share or collaborate with others; your data remains securely on your computer unless you choose to upload it. It functions by setting up a lightweight server on your device, allowing you to engage with it through your web browser, making data exploration of extensive datasets both straightforward and efficient. Additionally, users can discover more about OpenRefine's capabilities through instructional videos available online. Beyond cleaning your data, OpenRefine offers the ability to connect and enrich your dataset with various web services, and certain platforms even permit the uploading of your refined data to central repositories like Wikidata. Furthermore, a continually expanding selection of extensions and plugins is accessible on the OpenRefine wiki, enhancing its versatility and functionality for users. These features make OpenRefine an invaluable asset for anyone looking to manage and utilize complex datasets effectively.
  • 6
    Syniti Knowledge Platform Reviews
    For the first time, it is now possible to capture and retain data attributes such as meaning, usage, lineage, alignment with business outcomes, and ownership, which are often lost after each project, transforming them into valuable knowledge. These essential attributes can be reused effectively to enhance strategic business initiatives that rely on reliable data. By reusing data, you can achieve your objectives more swiftly. Take advantage of the hidden potential within your data to drive success. Unlocking data's potential in relation to your business context can be a game changer. Many of your projects demand similar insights and comprehension of your data, leading to the constant re-creation of the same information. Syniti can provide this critical knowledge at a significantly reduced cost and with improved precision. Rather than discarding your insights, consider unlocking and reapplying the knowledge embedded in your data. By preserving this knowledge, you create a valuable resource for future projects and insights. This approach not only saves time but also enhances overall business intelligence.
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