![Hithesh P.](/assets/transparent-ad5be28fbcd25b7b08d2cebe1d957125437fb5407d75ee717965ad22c8808791.gif "Hithesh P.")
HP

Hithesh P.

Data Engineer

Mid-Market (51-1000 emp.)

4/29/2026

"dbt Streamlines Data Pipelines with Powerful Incremental and SCD2 Features"

5/5

What do you like best about dbt?

dbt simplifies the process of building a solid data pipeline by offering a lot of features that would be difficult to implement from scratch. In particular, the SCD2 and incremental functionality helps remove a lot of overhead for developers and makes ongoing maintenance easier. There are also many other features that are great and contribute to a smoother overall workflow. Review collected by and hosted on G2.com.

What do you dislike about dbt?

There’s nothing I dislike about it, but I do have one suggestion:adding a feature for backfilling data (historical loads) will help a lot. Right now this can be done using a macro, but having an inbuilt option similar to incremental would make it much easier and help a lot. Review collected by and hosted on G2.com.

What problems is dbt solving and how is that benefiting you?

DBT is like a framework for data engineering. Building ETL using a traditional approach is very time-consuming and error-prone things like dependency issues, documentation, and testing all require extra precautions and a lot of manual effort.

That’s where dbt comes in as a lifesaver. It helps us build pipelines by providing features like lineage, auto-generated documentation, testing, macros, integrated Jinja, and more, which makes the overall process much easier to manage. Review collected by and hosted on G2.com.

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