Quest Data Intelligence vs SAP Data Hub [EOL] comparison

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Quest Software and SAP are both solutions in the Data Governance category. Additionally, 100% of Quest Software users are willing to recommend the solution, compared to 66% of SAP users who would recommend it.

Quest Data Intelligence

Read 22 Quest Data Intelligence reviews

7,045 Views
5,636 Comparison Views

100% willing to recommend

SAP Data Hub [EOL]

Read 3 SAP Data Hub [EOL] reviews

66% willing to recommend

Quest Data Intelligence

SAP Data Hub [EOL]

Comparison Buyer's Guide

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Executive SummaryUpdated on Jul 16, 2026

SAP Data Hub and erwin Data Intelligence are competing in data management and integration. erwin Data Intelligence has a slight edge due to its comprehensive data governance capabilities.

Features: SAP Data Hub provides strong data orchestration, seamless data pipeline management, and effective integration with SAP's ecosystem. erwin Data Intelligence is known for data governance, lineage tracking, and metadata management.

Ease of Deployment and Customer Service: SAP Data Hub supports streamlined deployment within SAP's landscape with reliable customer service. erwin Data Intelligence offers flexible deployment options compatible with diverse IT architectures and effective customer support.

Pricing and ROI: SAP Data Hub offers a cost-effective pricing structure. erwin Data Intelligence may involve higher initial setup costs but promises higher long-term ROI through enhanced data capabilities.

To learn more, read our detailed Data Governance Report (Updated: October 2026).

Buyer's Guide

Data Governance

October 2026

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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

Quest Data Intelligence

Average Rating

8.4

Reviews Sentiment

7.1

Number of Reviews

Ranking in other categories

Data Governance (15th), Metadata Management (7th), AI Governance (2nd)

SAP Data Hub [EOL]

Average Rating

7.6

Reviews Sentiment

6.8

Number of Reviews

Ranking in other categories

No ranking in other categories

Featured Reviews

Jog Raj

Senior Consultant at a computer software company with 11-50 employees

Automated lineage and business glossaries have improved data understanding and collaboration

I am open to answering a few questions about erwin Data Intelligence and sharing my opinion about the product. Regarding the analytic part of the product, I find it very interesting that erwin Data Intelligence has its own inbuilt reporting toolset, with a new version coming out in January that will be AI-powered. This means you will be able to write analytical reports and questions based on the metadata and data lineage, making it more powerful than the current version, as AI will assist in creating those reports and performing analysis on the metadata. I find that the time taken to realize value from erwin Data Intelligence can be quite long. Creating a data catalog and developing data lineage takes significant time, and I expect that AI will help accelerate the process of creating data products by streamlining the steps involved. I can recommend erwin Data Intelligence to other users. I would rate this review as an eight out of ten overall.

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Vijaya Macherla

GTM Lead at Capgemini

The solution is seamless, but the database sometimes leads to confusion

We used to have multiple different kinds of databases, which internally, had different compliance levels. Retention management is very different now. If the policy is live and the claim has been completed, I couldn't archive the claim. I needed to keep a reference integrity of that claim and understand which policy paid out the claim. With this solution, the policy came in six months ago and qualified for archiving. The claim had been paid and in every environment, the claim had been closed, including the reporting system, the claims system, etc. With the payment set gateway, I can just go and archive. But, we had a hard time during this process. I rate the overall solution a seven out of ten.

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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

"I can estimate that we lowered our time to market by 70 percent right now using these automation scripts, which is a really big thing."

"Data governance is helping us become even a better company because we know our data and how to use it."

"This type of solution was key to moving our entire company in the right direction by getting everyone to think about data governance."

"Data Intelligence creates a single source of truth for all of our metadata. This solution is better for data warehousing, but the metadata features speed up our development work. It's easy to create and manage mappings because we can export them to Informatica and pick up the work where we left off."

"By using the data catalog, we have definitely improved in terms of maturity as a data-driven decision-maker organization, and we are now getting to a level where everybody understands the data, understands how it is organized, and how they can use this data for different business decisions."

"The interface is easy to use. I also like Erwin's automatic data classification and data quality checks."

"This tool has taken us from having nothing to being very efficient."

"The main benefits erwin Data Intelligence provides to me include better decision-making, saving money and time by applying governance policies and procedures on the actual technical data, ensuring decisions are based on KPIs that are governed from source to end, and providing functionality for data classification to prevent unauthorized access through integration with the infrastructure team using DLP methodology."

More Quest Data Intelligence pros

"Its connection to on-premise products is the most valuable. We mostly use the on-premise connection, which is seamless. This is what we prefer in this solution over other solutions. We are using it the most for the orchestration where the data is coming from different categories. Its other features are very much similar to what they are giving us in open source. Their push-down approach is the most advantageous, where they push most of the processing on to the same data source. This means that they have a serverless kind of thing, and they don't process the data inside a product such as Data Hub. They process the data from where the data is coming out. If it is coming from HANA, to capture the data or process it for analytics, orchestration, or management, they go to the HANA database and give it out. They don't process it on Data Hub. This push-down approach increases the processing speed a little bit because the data is processed where it is sitting. That's the best part and an advantage. I have used another product where they used to capture the data first and then they used to process it and give it. In Data Hub, it is in reverse. They process it first and give it, and then they put their own manipulations. They lead in terms of business functions. No other solution has business functions already implemented to perform business analysis. They have a lot of prebuilt business functions for machine learning and orchestration, which we can use directly to get an analysis out from the existing data. Most of the data is sitting as enterprise data there. That's a major advantage that they have."

"Having this solution enables us to approach our clients to upgrade their databases, and we upgrade them according to their business requirements."

"SAP is one of the most seamless ERPs that have integrated SAP archiving within Excel. I have not seen this with any other database."

"The most valuable feature is the S/4HANA 1909 On-Premise"

"They lead in terms of business functions, and no other solution has business functions already implemented to perform business analysis, with a lot of prebuilt business functions for machine learning and orchestration that we can use directly to get an analysis out from the existing enterprise data."

Cons

"There are always ways to improve things. For example, we can use AI to be able to find out something. When we are typing something, if we don't know the exact term, Artificial Intelligence would be useful to find terms that are phonetically or syntactically similar. Instead of having to type in the exact name, they can provide those in the list. So, they can provide AI support for the search because when you have thousands and thousands of terms, it is hard to remember all the names."

"If we are talking about the business side of the product, maybe the Data Literacy could be made a bit simpler. You have to put your hands on it, so there is room for improvement."

"We chose to implement on an Oracle Database because we also had the erwin Data Modeler and Web Portal products in-house, which have been set up on Oracle Databases for many years. Sometimes the Oracle Database installation has caused some hiccups that wouldn't necessarily have been caused if we had used SQL Server."

"We still need another layer of data quality assessments on the source to see if it is sending us the wrong data or if there are some issues with the source data. For those things, we need a rule-based data quality assessment or scoring where we can assess tools or other technology stacks. We need to be able to leverage where the business comes in, defining some business rules and have the ability to execute those rules, then score the data quality of all those attributes. Data quality is definitely not what we are leveraging from this tool, as of today."

"The integration with various metadata sources, including erwin Data Modeler, isn't smooth in the current version. It took some experimentation to get things working. We hope this is improved in the newer version. The initial version we used felt awkward because Erwin implemented features from other companies into their offering."

"The metadata ingestion is very nice because of the ability to automate it. It would be nice to be able to do this ingestion, or set it up, from one place, instead of having to set it up separately for every data asset that is ingested."

"The solution's Arabic language processing is limited. The results are limited when you use the interface in Arabic."

"Improvement is required for the AIMatch feature, which is supposed to help automatically discover relationships in data."

More Quest Data Intelligence cons

"Nowadays there are some inconsistencies in data bases, however, they upgrade and release the versions to market."

"The company has everything offshore."

"In 2018, connecting it to outside sources, such as IoT products or IoT-enabled big data Hadoop, was a little complex. It was not smooth at the beginning. It was unstable. It took a lot of time for the initial data load. Sometimes, the connection broke, and we had to restart the process, which was a major issue, but they might have improved it now. It is very smooth with SAP HANA on-premise system, SAP Cloud Platform, and SAP Analytics Cloud. It could be because these are their own products, and they know how to integrate them. With Hadoop, they might have used open-source technologies, and that's why it was breaking at that time. They are providing less embedded integration because they want us to use their other products. For example, they don't want to go and remove SAP Analytics Cloud and put everything in Data Hub. They want us to use SAP Analytics Cloud somewhere else and not inside the Data Hub. On the integration part, it lacks real-time analytics, and it is slow. They should embed the SAP Analytics Cloud inside Data Hub or support some kind of analysis. They do provide some analysis, but it is not extensive. They are moreover open source. So, we need a lot of developers or data scientists to go in and implement Python algorithms. It would be better if they can provide their own existing algorithms and give some connections and drop-down menus to go and just configure those. It will make things really quick by increasing the embedded integrations. It will also improve the process efficiency and processing power. Its performance needs improvement. It is a little slow. It is not the best in the market, and there are other products that are much better than this. In terms of technology and performance, it is a little slow as compared to Microsoft and other data orchestration products. I haven't used other products, but I have read about those products, their settings, and the milliseconds that they do. In Azure Purview, they say that they can copy, manage, or transform the data within milliseconds. They say that they can transform 100 gigabytes of data within three to five seconds, which is something SAP cannot do. It generally takes a lot of time to process that much amount of data. However, I have never tested out Azure."

"Its performance needs improvement. It is a little slow. It is not the best in the market, and there are other products that are much better than this."

Pricing and Cost Advice

"erwin's pricing was cheaper than its competitors."

"I am not very familiar with its pricing. I know it is not cheap, but it is also not super expensive. It depends on the company size. For a company making $1 million, it is very expensive. For a company making 10 million and above, it might be okay."

"There is an additional fee for the server maintenance."

"The licensing cost was very affordable at the time of purchase. It has since been taken over by erwin, then Quest. The tool has gotten a bit more costly, but they are adding more features very quickly."

"erwin is cheaper than other solutions and this should appeal to other buyers. It has a good price tag."

"Erwin Data Catalog is very expensive."

"You buy a seat license for your portal. We have 100 seats for the portal, then you buy just the development licenses for the people who are going to put the data in."

"The whole suite, not just the DI but the modeling software, the harvester, Mapping Manager — everything we have — is about $100,000 a year for our renewals. That works out to each module being something like $8,000 to $10,000."

More Quest Data Intelligence pricing and cost advice

"The Cloud is very expensive, but SAP HANA previous service is okay."

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Top Industries

By visitors reading reviews

Financial Services Firm

13%

Outsourcing Company

10%

Manufacturing Company

Government

Outsourcing Company

15%

Manufacturing Company

14%

Financial Services Firm

Construction Company

Company Size

By reviewers

Large Enterprise

Midsize Enterprise

Small Business

By reviewers
Company Size	Count
Small Business	3
Midsize Enterprise	4
Large Enterprise	16

No data available

Questions from the Community

What needs improvement with erwin Data Intelligence by Quest?

In my opinion, the analytics part of erwin Data Intelligence is not satisfactory. The name 'Intelligence' is not related specifically to analytics; it is focused on data governance with no advanced...

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What is your primary use case for erwin Data Intelligence by Quest?

My main use case for erwin Data Intelligence is applying it and the DQ Labs in a financial institution.

See all answers

What advice do you have for others considering erwin Data Intelligence by Quest?

The integration of business glossaries has significantly helped improve collaboration in our organization. We define the business glossaries first during meetings with the business, and then we bul...

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Product Reports

Buyer's Guide

Quest Data Intelligence

October 2026

Download Quest Data Intelligence product report

Buyer's Guide

Data Governance

October 2026

Download SAP Data Hub [EOL] product report

Also Known As

erwin DG, erwin Data Governance, erwin Data Catalog

No data available

Overview

erwin Data Intelligence is a comprehensive platform for metadata management, data cataloging, and governance. It enables organizations to gain insights, improve traceability, and streamline compliance through its advanced features.

Focusing on data lineage, metadata repositories, and seamless integrations, erwin Data Intelligence provides a unified perspective of enterprise data. Its robust capabilities include Smart Data Connectors for automation, efficient data visualization with mind maps, and adaptable metadata properties. While the platform integrates well into existing systems, areas for improvement include automation, SDK inconsistencies, and the need for better data quality assessments. Use cases highlight its importance in enhancing business data models and regulatory compliance.

What are the key features of erwin Data Intelligence?

Single Source of Truth: Centralizes data for consistent information across the organization.
Smart Data Connectors: Automate connections to data sources, enhancing efficiency.
Data Lineage: Tracks data pathways for better traceability and understanding.
Business Glossaries: Enables clear definitions and shared vocabulary for all users.
Metadata Management: Streamlines metadata organization and retrieval.
Impact Analysis: Assesses implications of data changes rapidly and accurately.

What benefits should users look for in reviews?

Enhanced Efficiency: Automation scripts reduce manual processes and increase productivity.
Improved Data Visualization: Mind maps facilitate an intuitive understanding of complex data.
Customizable Properties: Adapt metadata attributes to fit specific organizational requirements.
Unified View: Offers a comprehensive perspective of data governance practices.

Industries implementing erwin Data Intelligence often focus on mapping data sources and integrating governance with ETL tools. This supports comprehensive data management strategies, enabling business teams to better locate, understand, and utilize data effectively. Its application in metadata management and automated reporting is particularly valuable in sectors requiring stringent regulatory compliance.

Quest Software

The SAP® Data Hub solution enables sophisticated data operations management. It gives you the capability and flexibility to connect enterprise data and Big Data and gain a deep understanding of data and information processes across sources and systems throughout the distributed landscape. The unified solution provides visibility and control into data opportunities, integrating cloud and on-premise information and driving data agility and business value. Distributed processing power enables greater speed and efficiency.

SAP

Sample Customers

Oracle, Infosys, GSK, Toyota Motor Sales, HSBC

Kaeser Kompressoren, HARTMANN

Find out what your peers are saying about Collibra, Microsoft, Informatica and others in Data Governance. Updated: October 2026.

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