Best Data Engineering Tools

Compare the Top Data Engineering Tools as of December 2025

What are Data Engineering Tools?

Data engineering tools are designed to facilitate the process of preparing and managing large datasets for analysis. These tools support tasks like data extraction, transformation, and loading (ETL), allowing engineers to build efficient data pipelines that move and process data from various sources into storage systems. They help ensure data integrity and quality by providing features for validation, cleansing, and monitoring. Data engineering tools also often include capabilities for automation, scalability, and integration with big data platforms. By streamlining complex workflows, they enable organizations to handle large-scale data operations more efficiently and support advanced analytics and machine learning initiatives. Compare and read user reviews of the best Data Engineering tools currently available using the table below. This list is updated regularly.

  • 1
    Looker

    Looker

    Google

    Looker, Google Cloud’s business intelligence platform, enables you to chat with your data. Organizations turn to Looker for self-service and governed BI, to build custom applications with trusted metrics, or to bring Looker modeling to their existing environment. The result is improved data engineering efficiency and true business transformation. Looker is reinventing business intelligence for the modern company. Looker works the way the web does: browser-based, its unique modeling language lets any employee leverage the work of your best data analysts. Operating 100% in-database, Looker capitalizes on the newest, fastest analytic databases—to get real results, in real time.
  • 2
    Xtract Data Automation Suite (XDAS)
    Xtract Data Automation Suite (XDAS) is a comprehensive platform designed to streamline process automation for data-intensive workflows. It offers a vast library of over 300 pre-built micro solutions and AI agents, enabling businesses to design and orchestrate AI-driven workflows with no code environment, thereby enhancing operational efficiency and accelerating digital transformation. Key components of XDAS include Bot Studio, which allows users to create custom bots and scripts; Scrape Studio, for effortless web data extraction; GenAI Studio, for developing AI agents that process unstructured data; HITL Studio, which integrates human oversight into data workflows; and XRAG Studio, for building advanced AI systems using retrieval-augmented generation techniques. By leveraging these tools, XDAS helps businesses ensure compliance, reduce time to market, enhance data accuracy, and forecast market trends across various industries.
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