Compare Apache Atlas vs. SAP Data Intelligence in 2025

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Description

Atlas serves as a versatile and scalable suite of essential governance services, empowering organizations to efficiently comply with regulations within the Hadoop ecosystem while facilitating integration across the enterprise's data landscape. Apache Atlas offers comprehensive metadata management and governance tools that assist businesses in creating a detailed catalog of their data assets, effectively classifying and managing these assets, and fostering collaboration among data scientists, analysts, and governance teams. It comes equipped with pre-defined types for a variety of both Hadoop and non-Hadoop metadata, alongside the capability to establish new metadata types tailored to specific needs. These types can incorporate primitive attributes, complex attributes, and object references, and they can also inherit characteristics from other types. Entities, which are instances of these types, encapsulate the specifics of metadata objects and their interconnections. Additionally, REST APIs enable seamless interaction with types and instances, promoting easier integration and enhancing overall functionality. This robust framework not only streamlines governance processes but also supports a culture of data-driven collaboration across the organization.

Description

Transform the chaos of data into meaningful value through the power of data intelligence. By connecting, discovering, enriching, and orchestrating fragmented data resources, organizations can derive actionable insights that drive business success on an enterprise level. SAP Data Intelligence serves as a holistic solution for data management. Acting as the orchestration layer for SAP’s Business Technology Platform, it converts scattered data landscapes into essential insights that foster large-scale innovation. Empower your users with intelligent, relevant, and contextual insights through seamless integration across the entire IT ecosystem. Effectively manage and orchestrate vast volumes of data and streams to enhance operational efficiency. Additionally, streamline processes, operationalize machine learning-driven innovations, and establish robust governance frameworks to mitigate compliance risks with comprehensive metadata management strategies. As data continues to evolve, maintaining a clear focus on actionable insights will be crucial for sustaining enterprise growth.