5 SQL Lineage Tools for MongoDB

Dataedo

https://dataedo.com/product/data-lineage

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.

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

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OvalEdge

https://ovaledge.com

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.

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

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Secoda

https://www.secoda.co/data-lineage

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.

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

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Dremio

https://www.dremio.com/

Dremio is a SQL Lakehouse Platform that offers effective data lineage support, as the relationships between your data sources, virtual datasets, and all your queries are maintained in Dremio’s data graph, telling you exactly where each dataset came from. It provides self-service analytics with unified data access, modern and intuitive U/I, semantic layer, and built for SQL.

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

Go to vendor website

Fivetran

https://www.fivetran.com/data-movement/transformations

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.