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ETL Solutions Transformation Manager vs dbt comparison

 

Comparison Buyer's Guide

Executive SummaryUpdated on Dec 19, 2024

Review summaries and opinions

We asked business professionals to review the solutions they use. Here are some excerpts of what they said:
 

Categories and Ranking

dbt
Ranking in Data Integration
11th
Average Rating
8.0
Reviews Sentiment
6.6
Number of Reviews
11
Ranking in other categories
Data Quality (5th)
ETL Solutions Transformatio...
Ranking in Data Integration
52nd
Average Rating
9.0
Reviews Sentiment
6.8
Number of Reviews
3
Ranking in other categories
No ranking in other categories
 

Mindshare comparison

As of June 2026, in the Data Integration category, the mindshare of dbt is 1.4%, down from 1.7% compared to the previous year. The mindshare of ETL Solutions Transformation Manager is 1.0%, up from 0.3% compared to the previous year. It is calculated based on PeerSpot user engagement data.
Data Integration Mindshare Distribution
ProductMindshare (%)
dbt1.4%
ETL Solutions Transformation Manager1.0%
Other97.6%
Data Integration
 

Featured Reviews

Harshwardhan Gullapalli - PeerSpot reviewer
AI Engineer at a educational organization with 51-200 employees
Data pipelines have improved financial accuracy and now build transparent audit-ready reports
As for something I wish we had, dbt's native support for Python transformations came later, and we did some complex financial classification calculations that felt clunky in pure SQL. We ended up writing Python in our n8n workflows and then fed the results back into dbt, which created a bit of a split-brain situation. If we would have had dbt Python models earlier, we could have kept that logic unified. Managing multiple reporting standards was our biggest operational pain point with dbt. We were running UAE corporate tax compliance and IFRS disclosure workflows simultaneously for different clients, and dbt does not have a native concept of multi-tenant or multi-standard project organization. Everything lives in one flat structure, so we had to build more conventions: separate schema folders for IFRS models versus UACT models, custom macros to tag models by compliance regime, and environment variables to control which set of transformations run for which client.
Vijayraj Amin - PeerSpot reviewer
Global Growth Strategist at MAIORA
User-friendly and accessible for anyone with computer knowledge and logical thinking
There is room for improvement in the solution's visualization tool. Currently, it provides basic reports and the ability to create graphs and dashboards, but I'm looking forward to more robust analytics. The plan is to enhance this feature in 2024, around Q2 or Q3, which would save us from relying on external tools like Power BI for insights.

Quotes from Members

We asked business professionals to review the solutions they use. Here are some excerpts of what they said:
 

Pros

"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."
"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."
"I would say the best feature or the most desirable feature for dbt is the ability to write everything in code."
"Overall, I find dbt to be optimized compared to other tools."
"dbt has positively impacted my organization by allowing us to expand the ceiling of complexity because once we have written the SQL, we can manage significantly more complexity since we are not spending all of our time doing it ourselves."
"From a developer point of view, I find the ease of development and the code to be the most useful capabilities of dbt."
"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."
"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."
"Transformation Manager is the backbone of every data pipeline these days because the solution has been on the market for 20 to 30 years, and we use it for various industries, including financial services, manufacturing, healthcare, etc."
"It is a reliable solution."
"It is among the best, even if not widely known."
"Back in the day, we could only get reports and analyze what happened after the fact, but today now we can generate real-time insights. Transformation Manager feeds your data science projects. We generate models and then give them to the clients, so they can come up with real-time predictions and recommendations in addition to reporting."
 

Cons

"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."
"If you compare the cost of those packages with dbt alone, it is more expensive to use dbt alone."
"The solution must add more Python-based implementations."
"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."
"Managing multiple reporting standards was our biggest operational pain point with dbt."
"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."
"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."
"The initial setup of dbt is somewhat complex."
"Transformation Manager reporting could be better. There are better options for reporting tools these days. We use Microsoft BI sometimes, but Tableau is becoming too expensive. Microsoft BI's visualization features are maturing."
"There is room for improvement in the solution's visualization tool."
"We get decent support. It's okay but not great."
"They should build a functional architecture based on queuing."
 

Pricing and Cost Advice

"The solution’s pricing is affordable."
"It is an expensive solution."
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Top Industries

By visitors reading reviews
Financial Services Firm
17%
Insurance Company
7%
Manufacturing Company
7%
Comms Service Provider
7%
Construction Company
13%
Computer Software Company
12%
Outsourcing Company
12%
Retailer
7%
 

Company Size

By reviewers
Large Enterprise
Midsize Enterprise
Small Business
By reviewers
Company SizeCount
Small Business2
Midsize Enterprise3
Large Enterprise6
No data available
 

Questions from the Community

What is your experience regarding pricing and costs for dbt?
My experience with pricing, setup cost, and licensing for dbt is that dbt is open source for its core modules, so the pricing, setup, and everything was really good.
What needs improvement with dbt?
dbt can be improved by introducing Python. Ideally, I would want to be able to orchestrate across the DAG and have both Python and SQL combined. The last time I used it, it was not able to visualiz...
What is your primary use case for dbt?
My main use case for dbt is data pipelines. I build data transformations and usually construct analytics pipelines.
Ask a question
Earn 20 points
 

Also Known As

No data available
Transformation Manager
 

Overview

 

Sample Customers

Information Not Available
Honda, BNP Paribas, RBS, JPMorgan, Volkswagen, Thorn Lighting, OpenSpirit, Rolls-Royce, Ulster Bank
Find out what your peers are saying about ETL Solutions Transformation Manager vs. dbt and other solutions. Updated: June 2026.
900,644 professionals have used our research since 2012.