5 SQL Lineage Tools for Azure SQL Database

Collibra Data Lineage extracts and maintains lineage automatically from source systems, SQL dialects, ETL tools, and BI tools. It provides detailed technical lineage at the table, column, transformation, and SQL query levels to quickly understand the impact of potential changes. Moreover, its interactive lineage diagram shows a summary of lineage from source to destination.

Automatic discovery:
Data flow visualization:
Environment:	Online
Free edition:
Metadata management:
Version control integration:

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OpenMetadata

https://open-metadata.org/

OpenMetadata is a single place to discover, collaborate and get your data right. It supports a comprehensive lineage for all data assets by capturing the relation between entities. It traces the path of data across tables, pipelines, and dashboards, while the manual lineage helps augment the lineage captured from machine metadata with user knowledge.

Automatic discovery:
Data flow visualization:
Environment:	Online
Free edition:
Metadata management:
Version control integration:

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MANTA

https://manta.io/supported-scanners/microsoft-sql-server

Manta offers a powerful scanner for the Microsoft SQL Server technology. Once configured, Manta can automatically connect to the MS SQL resource for extracting and analyzing the pertinent metadata within the selected databases. This metadata includes but is not limited to tables, views, indexes, SQL procedures, schemas, databases, columns, and triggers. Then, Manta can parse all the SQL programming code and logic stored within. This allows Manta to generate lineage down to the column level while showing all transformation logic associated with individual column elements.

Automatic discovery:
Data flow visualization:
Environment:	On-premises
Free edition:
Metadata management:
Version control integration:

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Azure Purview

https://azure.microsoft.com/en-us/services/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.