Best Data Engineering Tools for Git

Find and compare the best Data Engineering tools for Git in 2025

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

  • 1
    Prophecy Reviews

    Prophecy

    Prophecy

    $299 per month
    Prophecy expands accessibility for a wider range of users, including visual ETL developers and data analysts, by allowing them to easily create pipelines through a user-friendly point-and-click interface combined with a few SQL expressions. While utilizing the Low-Code designer to construct workflows, you simultaneously generate high-quality, easily readable code for Spark and Airflow, which is then seamlessly integrated into your Git repository. The platform comes equipped with a gem builder, enabling rapid development and deployment of custom frameworks, such as those for data quality, encryption, and additional sources and targets that enhance the existing capabilities. Furthermore, Prophecy ensures that best practices and essential infrastructure are offered as managed services, simplifying your daily operations and overall experience. With Prophecy, you can achieve high-performance workflows that leverage the cloud's scalability and performance capabilities, ensuring that your projects run efficiently and effectively. This powerful combination of features makes it an invaluable tool for modern data workflows.
  • 2
    Iterative Reviews
    AI teams encounter obstacles that necessitate the development of innovative technologies, which we specialize in creating. Traditional data warehouses and lakes struggle to accommodate unstructured data types such as text, images, and videos. Our approach integrates AI with software development, specifically designed for data scientists, machine learning engineers, and data engineers alike. Instead of reinventing existing solutions, we provide a swift and cost-effective route to bring your projects into production. Your data remains securely stored under your control, and model training occurs on your own infrastructure. By addressing the limitations of current data handling methods, we ensure that AI teams can effectively meet their challenges. Our Studio functions as an extension of platforms like GitHub, GitLab, or BitBucket, allowing seamless integration. You can choose to sign up for our online SaaS version or reach out for an on-premise installation tailored to your needs. This flexibility allows organizations of all sizes to adopt our solutions effectively.
  • 3
    Kestra Reviews
    Kestra is a free, open-source orchestrator based on events that simplifies data operations while improving collaboration between engineers and users. Kestra brings Infrastructure as Code to data pipelines. This allows you to build reliable workflows with confidence. The declarative YAML interface allows anyone who wants to benefit from analytics to participate in the creation of the data pipeline. The UI automatically updates the YAML definition whenever you make changes to a work flow via the UI or an API call. The orchestration logic can be defined in code declaratively, even if certain workflow components are modified.
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