Best Data Lineage Tools for Apache Superset

Compare the Top Data Lineage Tools that integrate with Apache Superset as of October 2025

This a list of Data Lineage tools that integrate with Apache Superset. Use the filters on the left to add additional filters for products that have integrations with Apache Superset. View the products that work with Apache Superset in the table below.

What are Data Lineage Tools for Apache Superset?

Data lineage tools are software solutions designed to track and visualize the flow of data through various stages of its lifecycle, from origin to destination. These tools help organizations understand the data's journey, transformations, and dependencies across different systems and processes. They offer features such as data mapping, impact analysis, and auditing to ensure data accuracy, compliance, and governance. By providing detailed insights into data movement and transformations, data lineage tools enable better decision-making, troubleshooting, and optimization of data workflows. They are essential for maintaining data integrity and transparency in complex data environments. Compare and read user reviews of the best Data Lineage tools for Apache Superset currently available using the table below. This list is updated regularly.

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    Dremio

    Dremio

    Dremio

    Dremio delivers lightning-fast queries and a self-service semantic layer directly on your data lake storage. No moving data to proprietary data warehouses, no cubes, no aggregation tables or extracts. Just flexibility and control for data architects, and self-service for data consumers. Dremio technologies like Data Reflections, Columnar Cloud Cache (C3) and Predictive Pipelining work alongside Apache Arrow to make queries on your data lake storage very, very fast. An abstraction layer enables IT to apply security and business meaning, while enabling analysts and data scientists to explore data and derive new virtual datasets. Dremio’s semantic layer is an integrated, searchable catalog that indexes all of your metadata, so business users can easily make sense of your data. Virtual datasets and spaces make up the semantic layer, and are all indexed and searchable.
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