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dbt pros and cons

Vendor: dbt Labs

4.0 out of 5

10 reviews
100% willing to recommend

Pros & Cons summary

dbt streamlines data transformation, reducing full refresh time to around four hours with enhanced orchestration. It accelerates data pipeline creation from months to weeks while improving data quality through modular SQL and version control. dbt's testing layer catches 70% of errors early, benefiting AI models. Though the setup is complex and stability challenged by outages, its value offsets the license cost for larger companies; however, Git migration issues and reporting challenges persist.

Buyer's Guide

Get pricing advice, tips, use cases and valuable features from real users of this product.

Prominent pros & cons

PROS

Since migrating from SSIS to dbt architecture, full refresh completion time was reduced to around four hours, significantly reducing downtime.

dbt allows orchestration of all transformations in one place, increasing convenience for users.

dbt enables faster creation of data pipelines, shortening the time from data ingestion to data product creation from months to weeks using existing skillsets.

Operational efficiency is achieved with modular SQL and version control, improving data quality and governance by reducing data duplication and errors.

dbt's testing layer significantly reduces data errors by catching approximately 70% of issues at the transformation stage, before impacting downstream AI models.

CONS

Since dbt has a license cost, if a company is small and does not have much budget, they can explore other tools because there are other tools that provide the same functionality at a lower cost.

The initial setup of dbt is somewhat complex.

Dbt is not as stable as preferred, experiencing a few outages in the current year, so improvement is needed in the stability.

Migration of code to Git and GitHub sometimes fails and can be confusing for developers during handover.

Managing multiple reporting standards was a significant operational pain point with dbt.

dbt Pros review quotes

Harshwardhan Gullapalli

AI Engineer at a educational organization with 51-200 employees

Apr 7, 2026

The most concrete outcome was a significant reduction in data errors reaching our downstream AI models, and after implementing dbt's testing layer, we caught roughly 70% of those issues at the transformation stage itself, before they ever touched the model.

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AS

Principal Data Engineer at Integrant, Inc.

Mar 2, 2026

I would say the best feature or the most desirable feature for dbt is the ability to write everything in code.

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Surjit-Choudhury

Data Architect at Envision Pharma, Inc.

Apr 30, 2026

Overall, I find dbt to be optimized compared to other tools.

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reviewer2780388

Senior Data Engineer at a pharma/biotech company with 10,001+ employees

Dec 10, 2025

There is operational efficiency achieved, and data quality and governance have also been achieved with modular SQL and version controlling, which reduced duplication of data and data errors.

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Shubham-Agarwal

Manager Projects at Cognizant

Jan 22, 2026

Since we migrated from SSIS to dbt model architecture, it takes around four hours only to complete a full refresh, and the client is now happy because our downtime was drastically reduced when we perform a complete refresh of the data.

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Head of Data & AI engineering at One NZ

Dec 2, 2025

dbt has positively impacted my organization by allowing us to create our data pipelines much faster, going from ingestion of data to creating a data product in weeks instead of months, and we can do it in-house with the skillset we already have.

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JA

JohamAlvarez-Montoya

Data Engineer at Georgia Institute of Technology

Apr 6, 2026

It is very convenient because at the end, I have the opportunity to orchestrate all my transformations in just one single place, rather than having them spread out.

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reviewer2803965

Lead Software Engineer at a computer software company with 51-200 employees

Feb 20, 2026

From a developer point of view, I find the ease of development and the code to be the most useful capabilities of dbt.

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Senior Machine Learning Engineer at Happiest Minds Technologies

Aug 13, 2024

The product is developer-friendly.

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dbt Cons review quotes

Harshwardhan Gullapalli

AI Engineer at a educational organization with 51-200 employees

Apr 7, 2026

Managing multiple reporting standards was our biggest operational pain point with dbt.

Read full review

AS

Principal Data Engineer at Integrant, Inc.

Mar 2, 2026

Every upgrade is a little bit of a risk for us because we do not know if the workarounds that we developed will be available for the next version.

Read full review

Surjit-Choudhury

Data Architect at Envision Pharma, Inc.

Apr 30, 2026

The initial setup of dbt is somewhat complex.

Read full review

Free Report: dbt Reviews and More

Learn what your peers think about dbt. Get advice and tips from experienced pros sharing their opinions. Updated: May 2026.

893,221 professionals have used our research since 2012.

reviewer2780388

Senior Data Engineer at a pharma/biotech company with 10,001+ employees

Dec 10, 2025

Dbt is not as stable as preferred, as it has had a few outages in the current year itself, so improvement should be made in the outages section as it is not stable.

Read full review

Shubham-Agarwal

Manager Projects at Cognizant

Jan 22, 2026

Since dbt has a license cost, if a company is small and does not have much budget, they can explore other tools because there are other tools that provide the same functionality at a lower cost.

Read full review

Head of Data & AI engineering at One NZ

Dec 2, 2025

dbt can be improved as I find the co-pilot in dbt is not very good, and my team has tried using it but opted to move off it and use other co-pilots such as GitHub.

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JA

JohamAlvarez-Montoya

Data Engineer at Georgia Institute of Technology

Apr 6, 2026

If you compare the cost of those packages with dbt alone, it is more expensive to use dbt alone.

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reviewer2803965

Lead Software Engineer at a computer software company with 51-200 employees

Feb 20, 2026

If I needed to name a few areas for improvement, I would mention the migration of code to Git and GitHub, which sometimes fails and can be confusing for developers during handover.

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Senior Machine Learning Engineer at Happiest Minds Technologies

Aug 13, 2024

The solution must add more Python-based implementations.

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Product Categories

Product Categories

Data Integration

Popular Comparisons

Popular Comparisons

Informatica Intelligent Data Management Cloud (IDMC) vs dbt

Teradata vs dbt

Informatica PowerCenter vs dbt

Qlik Talend Cloud vs dbt

Palantir Foundry vs dbt

Azure Data Factory vs dbt

Oracle Data Integrator (ODI) vs dbt

Fivetran vs dbt

SnapLogic vs dbt

Oracle GoldenGate vs dbt

IBM InfoSphere DataStage vs dbt

SAP Data Services vs dbt

Pentaho Data Integration and Analytics vs dbt

See all alternatives

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