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SAP Information Steward vs dbt comparison

 

Comparison Buyer's Guide

Executive Summary

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 Quality
5th
Average Rating
8.0
Reviews Sentiment
6.6
Number of Reviews
10
Ranking in other categories
Data Integration (9th)
SAP Information Steward
Ranking in Data Quality
17th
Average Rating
7.6
Reviews Sentiment
6.8
Number of Reviews
9
Ranking in other categories
Metadata Management (10th)
 

Mindshare comparison

As of May 2026, in the Data Quality category, the mindshare of dbt is 2.2%, up from 1.7% compared to the previous year. The mindshare of SAP Information Steward is 3.0%, down from 3.2% compared to the previous year. It is calculated based on PeerSpot user engagement data.
Data Quality Mindshare Distribution
ProductMindshare (%)
dbt2.2%
SAP Information Steward3.0%
Other94.8%
Data Quality
 

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.
FranciscoSantos - PeerSpot reviewer
Director at Pixel Studio PTY
Provides accurate data that is validated against a personalized reference tool
For most SAP customers, Information Steward is enough because it is able to build quality data rules to detect issues in the source systems like SAP HANA, Business Warehouse, or other systems. A business user can first organize their data into several data domains. For example, procurement, human resources, and logistics setup. The domains can build data quality dimensions where you can describe the kind of rule that you are going to use. The user then can immediately see if something is wrong with their data using traffic lights. Another great feature of SAP Information Steward is the accuracy that the content is followed by validating against the reference tool. With the solution, you are creating data quality dimensions. Within these dimensions, you are creating business data quality rules that are looking for specific fields. From these rules, you can create a scorecard. The scorecard will highlight the percentage of good data and ensure the user can feel confident that the data is accurate within predetermined limits. SAP tables have field names that are very cryptic, making them hard to understand the meaning of the fields. Metapedia helps describe these fields in business terms.

Quotes from Members

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

Pros

"From a developer point of view, I find the ease of development and the code to be the most useful capabilities of dbt."
"The product is developer-friendly."
"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."
"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."
"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."
"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."
"Overall, I find dbt to be optimized compared to other tools."
"I would say the best feature or the most desirable feature for dbt is the ability to write everything in code."
"The product has improved company efficiency because we're able to categorize the need for user access at the folder level across storage enterprise wide."
"Initial setup was straightforward."
"The solution is user-friendly even for those who are dealing with it for the first time."
"Data insight is the most valuable feature."
"The ability to analyze the data even before we start the transformation of it, and generating the user-friendly interface, giving analytical reports, and helping create the transformation rules before we proceed with the data migration part was the most helpful part of the solution for our company."
"I am very happy with the product."
"The data profiling was excellent, as was the ease of generating the dashboards."
"Data integration is much easier with Information Steward - irrespective of the data sources, integration is very smooth and easy."
 

Cons

"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."
"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 solution must add more Python-based implementations."
"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."
"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."
"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."
"The initial setup of dbt is somewhat complex."
"Managing multiple reporting standards was our biggest operational pain point with dbt."
"SAP Information Steward is an expensive solution compared to others."
"A problem with the solution is that it does not allow us to review the results of Information Stewards for other analogies."
"From a performance perspective, sometimes it behaves weirdly. When we are connecting with the file-based system, it doesn't give us the correct results, or it somehow shows us there is this issue with the data or the file connectivity."
"Granularity could be reduced from an application level to the object level."
"SAP is a bit pricey, and better tools are available for a lower price."
"In some cases they have given extraneous or erroneous information, which is completely useless."
"The user experience of metapedia could be improved."
"Performance could be improved."
 

Pricing and Cost Advice

"The solution’s pricing is affordable."
"I do not know if there were additional costs beyond the standard licensing fees."
"SAP Information Steward is an expensive solution compared to others."
"A bit pricey, and better tools are available for a lower price."
"Smaller-sized organizations may not be able to invest in SAP Information Steward because of the cost."
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Top Industries

By visitors reading reviews
Financial Services Firm
16%
Insurance Company
8%
Manufacturing Company
8%
Comms Service Provider
7%
Manufacturing Company
18%
Government
15%
Comms Service Provider
6%
Healthcare Company
6%
 

Company Size

By reviewers
Large Enterprise
Midsize Enterprise
Small Business
By reviewers
Company SizeCount
Small Business2
Midsize Enterprise3
Large Enterprise5
By reviewers
Company SizeCount
Small Business1
Large Enterprise7
 

Questions from the Community

What is your experience regarding pricing and costs for dbt?
I mentioned the cost as one of the advantages, specifically the license cost.
What needs improvement with dbt?
With AI, everything is advancing so fast, so I would say that the most important thing is to try to integrate with more platforms. As of now, dbt has a strong integration with AWS and with Snowflak...
What is your primary use case for dbt?
I am currently working with dbt and use dbt's modular SQL models.
Ask a question
Earn 20 points
 

Also Known As

No data available
Information Steward, SAP Data Insight
 

Overview

 

Sample Customers

Information Not Available
American Water, Graphic Packaging International, OSRAM Licht AG, Maxim Integrated
Find out what your peers are saying about SAP Information Steward vs. dbt and other solutions. Updated: April 2026.
893,438 professionals have used our research since 2012.