SQL Lineage Tools for Azure Cosmos DB
Dataedo
Dataedo provides SQL lineage tracking by visualizing how data flows through queries, transformations, and databases. This enhances transparency, supports troubleshooting, and ensures data accuracy across SQL-based environments.
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OvalEdge
OvalEdge provides a powerful and automated way to visualize your Data Flow Effortlessly. Its algorithms build the lineage from the most accurate source, source code. It crawls the source code from various connectors. After that, it parses its language like SQL, PL/SQL, XML, etc., and then builds the lineage.
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Secoda
Secoda provides end-to-end data lineage across your entire data stack. It automates column and table level data lineage. In additional, Secoda also brings in tests, events, and ETL into data lineage. All of Secoda's lineage is automated, but users can also manually contribute to lineage using Secoda's API.
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Azure Purview
Microsoft Purview provides a unified data governance solution that offers many capabilities, one of which is showing lineage between datasets created by data processes. It supports automated asset-level lineage for the datasets and processes, while manual lineage allows you to document lineage metadata for sources where automation isn't yet supported without using any code.
Metadata collected in Microsoft Purview from enterprise data systems are stitched across to show an end-to-end data lineage.
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Informatica Data Lineage
Informatica Data Lineage tool provides automated end-to-end data lineage with detailed and summary views of data movement across data pipelines. With Informatica, you can derive lineage from code in SQL scripts, stored procedures and AI/ML code. It streamlines tracking data flow from system- to column-level for detailed impact analysis.
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Fivetran
Fivetran is the automated data movement platform moving data out of, into and across your cloud data platforms. It allows you to monitor data movement, logs, and status from connector extract to successful warehouse load through modeling — all in one data lineage graph (DLGs). DLGs show the dependencies between your dbt models so that you can track the flow of data from your connectors to your destination.
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