dbt pros and cons

Name: dbt
Brand: dbt Labs
Rating: 3.9 (5 reviews)

Vendor: dbt Labs

3.9 out of 5

5 reviews
100% willing to recommend

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Pros & Cons summary

dbt enhances developer experience, enabling swift data product development in weeks. It boosts operational efficiency and data quality through modular SQL, while version control supports governance. Migration from SSIS cuts refresh times, improving client satisfaction. Challenges include the need for more Python implementation, ineffective co-pilot feature, stability issues, and high licensing costs for smaller companies. Prospective users should weigh these considerations against alternative tools.

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Prominent pros & cons

PROS

dbt is developer-friendly, facilitating data pipeline creation.

It enables rapid data product development in weeks instead of months using existing team skills.

Operational efficiency is achieved alongside improvements in data quality and governance through modular SQL and version control.

Migration from SSIS to dbt reduced full refresh time to approximately four hours.

Client satisfaction increased due to significant reductions in downtime during data refresh.

CONS

dbt needs more Python-based implementations.

The co-pilot feature in dbt is ineffective, leading teams to use alternatives like GitHub.

dbt has experienced several outages, indicating a lack of stability.

Small companies with limited budgets may find dbt's licensing costs prohibitive, as there are similar cheaper tools available.

dbt Pros review quotes

Ninad Magdum

Senior Machine Learning Engineer at Happiest Minds Technologies

Aug 13, 2024

The product is developer-friendly.

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JohnnyHuang

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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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.

Find out what your peers are saying about dbt Labs, Microsoft, Informatica and others in Data Integration. Updated: January 2026.

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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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dbt Cons review quotes

Ninad Magdum

Senior Machine Learning Engineer at Happiest Minds Technologies

Aug 13, 2024

The solution must add more Python-based implementations.

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JohnnyHuang

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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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.

Find out what your peers are saying about dbt Labs, Microsoft, Informatica and others in Data Integration. Updated: January 2026.

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881,082 professionals have used our research since 2012.

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.

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