Compare the Top Data Lineage Tools that integrate with SQL as of July 2025

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

What are Data Lineage Tools for SQL?

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 SQL currently available using the table below. This list is updated regularly.

  • 1
    AnalyticsCreator

    AnalyticsCreator

    AnalyticsCreator

    Enhance data governance with comprehensive lineage tracking capabilities, offering clear visibility into the origin and transformations of your data. This improved transparency ensures compliance with auditable lineage trails and facilitates faster root cause analysis for data quality issues. Quickly identify and resolve data quality problems with actionable insights. With AnalyticsCreator, improve transparency, compliance, and data trust by providing a detailed lineage trail for your entire data ecosystem. Empower teams to perform impact analysis and make informed decisions faster with a visual overview of data dependencies and flow.
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  • 2
    Databricks Data Intelligence Platform
    The Databricks Data Intelligence Platform allows your entire organization to use data and AI. It’s built on a lakehouse to provide an open, unified foundation for all data and governance, and is powered by a Data Intelligence Engine that understands the uniqueness of your data. The winners in every industry will be data and AI companies. From ETL to data warehousing to generative AI, Databricks helps you simplify and accelerate your data and AI goals. Databricks combines generative AI with the unification benefits of a lakehouse to power a Data Intelligence Engine that understands the unique semantics of your data. This allows the Databricks Platform to automatically optimize performance and manage infrastructure in ways unique to your business. The Data Intelligence Engine understands your organization’s language, so search and discovery of new data is as easy as asking a question like you would to a coworker.
  • 3
    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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