SAP Analytics Hub vs dbt comparison

dbt Labs and SAP are both solutions in the Data Integration category. dbt Labs is ranked #27 with an average rating of 7.5, while SAP is ranked #50 with an average rating of 6.0. dbt Labs holds a 1.7% mindshare in DI, compared to SAP’s 0.5% mindshare. Additionally, 100% of dbt Labs users are willing to recommend the solution, compared to 71% of SAP users who would recommend it.

dbt

Read 5 dbt reviews

1,642 Views
1,560 Comparison Views

100% willing to recommend

SAP Analytics Hub

Read 8 SAP Analytics Hub reviews

1,198 Views
443 Comparison Views

71% willing to recommend

dbt

SAP Analytics Hub

Comparison Buyer's Guide

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Executive SummaryUpdated on Dec 19, 2024

SAP Analytics Hub and dbt compete in the data visualization and transformation segment. SAP Analytics Hub has an edge in pricing and support, while dbt is preferred for its transformative capabilities.

Features: SAP Analytics Hub offers data visualization, analytics governance, and content sharing capabilities. dbt provides data modeling, transformation, and powerful tools for data development.

Ease of Deployment and Customer Service: SAP Analytics Hub is straightforward in deployment and provides comprehensive customer service, catering to organizations of different sizes. dbt requires more technical expertise for setup, focusing support on its niche user base. The difference is evident in SAP's broader deployment support compared to dbt's technical approach.

Pricing and ROI: SAP Analytics Hub provides competitive setup costs with strong ROI via efficient governance and content sharing. While dbt's initial cost may be higher due to specialized tools, its ROI is significant because of its efficiency in data transformation, highlighting the cost difference with SAP's broader capabilities versus dbt's transformative potential.

To learn more, read our detailed SAP Analytics Hub vs. dbt Report (Updated: December 2025).

Buyer's Guide

SAP Analytics Hub vs. dbt

December 2025

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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

27th

Average Rating

7.8

Reviews Sentiment

7.2

Number of Reviews

Ranking in other categories

Data Quality (17th)

SAP Analytics Hub

Ranking in Data Integration

50th

Average Rating

7.2

Reviews Sentiment

6.5

Number of Reviews

Ranking in other categories

BI (Business Intelligence) Tools (30th)

Mindshare comparison

As of January 2026, in the Data Integration category, the mindshare of dbt is 1.7%, up from 0.7% compared to the previous year. The mindshare of SAP Analytics Hub is 0.5%, up from 0.1% compared to the previous year. It is calculated based on PeerSpot user engagement data.

Data Integration Market Share Distribution
Product	Market Share (%)
dbt	1.7%
SAP Analytics Hub	0.5%
Other	97.8%

Data Integration

Featured Reviews

Shubham-Agarwal

Manager Projects at Cognizant

Incremental data models have cut full refresh time and support trusted executive reporting

I am not very familiar with dbt's version control system. I cannot identify any improvements in dbt because I am still exploring more functionality. I have been working with dbt for only three years, so I am exploring more functionalities and cannot see any limitations or improvement areas at this time. In the past, I used the seed functionality, which is used to load raw files, individual files, or static files into the database. Going forward, if dbt can improve or implement more features on the seed side, that would be beneficial, especially when we have large files available that take time to load the data into Snowflake database.

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Nitesh Agrawal

Director & Co-Owner at InfraBeat Technologies Pvt. Ltd.

Integration and security have improved, but search functionality and clarity of future direction need enhancement

The search function in SAP Analytics Hub is not effective. When speaking about integration with various analytic sources, for example, if I wanted to send the data from SAP BW or B4HANA to a data lake, we used to earlier use the Open Data Hub or Analytics Hub. Nowadays, we are using the Data Sphere integrators available with Amazon, Azure, and Google Cloud. The search capability could be better, and SAP needs to come out with a clear roadmap for the solution going ahead, as they have not yet provided that.

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Quotes from Members

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

Pros

"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 product is developer-friendly."

"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."

"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."

"Data consistency is also a notable feature; the system takes care of data consistency, so you don't need to handle it manually."

"What I like best about this solution is that it is built into the SAP line, making it easier to integrate with other SAP products."

"SAP Analytics Hub offers a user-friendly interface with effortless configuration, seamless updates, and real-time availability of information. It avoids the complexities associated with batch processing, providing a smooth and efficient experience."

"As a partner, I can mention something positive about SAP Analytics Hub: its products are tightly integrated, so the business context of data is retained in the analytics solution, and that's the main advantage."

"For report scheduling, I always prefer SAP because it has the most powerful scheduling features, like sending reports to more than 1,000 customers per day. That option is not as good in Microsoft BI and in Tableau it only exists as an add-on option."

"The platform's main benefit is its integration with SAP ERP data. It’s effective for data integration and integrity."

"This product provides good reports using a single pane of glass."

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."

"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."

"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."

"The interface can be simplified because it is not a user-friendly experience."

"Pricing and support are integrated into the system. However, the support process can be challenging, particularly when navigating the SAP support site, which lacks user-friendliness and ease of access."

"The analytics part of SAP has not been that good up until now. They're still in the infant stage and development is still going on. SAP has some cloud analytics and they're trying to configure it in Lumira, but it's not that good at this point."

"Faster implementation of new functions for the new product is an area of improvement in SAP Analytics Hub."

"The search capability could be better, and SAP needs to come out with a clear roadmap for the solution going ahead, as they have not yet provided that."

"The technical support for Analytics Hub is limited and could be improved."

"The platform could easily integrate with other ERP data solutions. Additionally, it should be faster compared to competitors in the cloud space."

Pricing and Cost Advice

"The solution’s pricing is affordable."

"They are pursuing a highly assertive approach to target businesses of all sizes within the industry."

"The pricing is reasonable."

"The product is expensive."

"It is an expensive solution."

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Top Industries

By visitors reading reviews

Financial Services Firm

14%

Insurance Company

Manufacturing Company

Computer Software Company

Manufacturing Company

15%

Transportation Company

Retailer

Financial Services Firm

Company Size

By reviewers

Large Enterprise

Midsize Enterprise

Small Business

No data available

By reviewers
Company Size	Count
Small Business	2
Midsize Enterprise	3
Large Enterprise	3

Questions from the Community

What is your experience regarding pricing and costs for dbt?

My experience with pricing, setup cost, and licensing was simple enough.

See all answers

What needs improvement with dbt?

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. Additionally, the debugging capab...

See all answers

What is your primary use case for dbt?

My main use case for dbt is for data transformation and data engineering.A specific example of how I use dbt for data transformation and engineering is that we use it to connect and ingest data fro...

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What is your experience regarding pricing and costs for SAP Analytics Hub?

The product is expensive. The cost starts from $1,000,000 per year. Moreover, there are additional costs involved for customization.

See all answers

What needs improvement with SAP Analytics Hub?

See all answers

What advice do you have for others considering SAP Analytics Hub?

When speaking about integration with various analytic sources, for example, if I wanted to send the data from SAP BW or B4HANA to a data lake, we used to earlier use the Open Data Hub or Analytics ...

See all answers

Comparisons

SSIS vs dbt

Compared 20% of the time

Oracle Data Integrator (ODI) vs dbt

Compared 9% of the time

Informatica Intelligent Data Management Cloud (IDMC) vs dbt

Compared 7% of the time

Informatica PowerCenter vs dbt

Compared 7% of the time

Tobiko vs dbt

Compared 7% of the time

More dbt Competitors

SAP Analytics Cloud vs SAP Analytics Hub

Compared 20% of the time

Microsoft Power BI vs SAP Analytics Hub

Compared 17% of the time

SAS Access vs SAP Analytics Hub

Compared 16% of the time

Informatica PowerCenter vs SAP Analytics Hub

Compared 12% of the time

Informatica Intelligent Data Management Cloud (IDMC) vs SAP Analytics Hub

Compared 12% of the time

More SAP Analytics Hub Competitors

Product Reports

Buyer's Guide

Data Integration

January 2026

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Buyer's Guide

SAP Analytics Hub

January 2026

Download SAP Analytics Hub product report

Overview

dbt is a transformational tool that empowers data teams to quickly build trusted data models, providing a shared language for analysts and engineering teams. Its flexibility and robust feature set make it a popular choice for modern data teams seeking efficiency.

Designed to integrate seamlessly with the data warehouse, dbt enables analytics engineers to transform raw data into reliable datasets for analysis. Its SQL-centric approach reduces the learning curve for users familiar with it, allowing powerful transformations and data modeling without needing a custom backend. While widely beneficial, dbt could improve in areas like version management and support for complex transformations out of the box.

What are the most valuable features of dbt?

SQL-Based Development: Facilitates transformations using SQL, streamlining the data modeling process.
Modularity: Encourages reusable components, making projects easier to manage and scale.
Version Control: Integrates with version control systems to track changes and collaborate effectively.
Testing Framework: Ensures data quality through automated tests, increasing trust in data outputs.

What benefits should you expect from using dbt?

Efficiency: Cuts down data processing times, allowing faster access to insights.
Collaboration: Promotes teamwork through shared data models and a common working language.
Scalability: Supports growing data demands by transforming complex data more flexibly and modularly.
Transparency: Provides clear documentation and lineage tracking, aiding in troubleshooting and understanding.

In the finance industry, dbt helps in cleansing and preparing transactional data for analysis, leading to more accurate financial reporting. In e-commerce, it empowers teams to rapidly integrate and analyze customer behavior data, optimizing marketing strategies and improving user experience.

dbt Labs

SAP Analytics Hub simplifies access to analytics scattered across multiple heterogeneous environments. The solution recommends the best analytics to fit personalized needs and grants users with actionable insights without compromising agility.

SAP

Sample Customers

Information Not Available

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Buyer's Guide

SAP Analytics Hub vs. dbt

December 2025

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