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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Helped 921,523 peers since 2012

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

"Being able to capture different business metrics and organize them in different catalogs is most valuable. We can organize these metrics into sales-related metrics, customer-related metrics, supply chain-related metrics, etc."

"The data management is, obviously, key in understanding where the data is and what the data is. And the governance can be done at multiple levels. You have the governance of the code sets versus the governance of the business terms and the definitions of those business terms. You have the governance of the business data models and how those business data models are driving the physical implementation of the actual databases. And, of course, you have the governance of the mapping to make sure that source-to-target mapping is done and is being shared across the company."

"The automated data lineage and impact analysis being driven from the mapping documents are astounding in reducing the time to research impact analysis from six to 16 weeks down to minutes, because it's a couple of clicks with a mouse."

"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."

"We use the codeset mapping quite a bit to match value pairs to use within the conversion as well. Those value pair mappings come in quite handy and are utilized quite extensively. They then feed into the automation of the source data extraction, like the source data mapping of the source data extraction, the code development, forward engineering using the ODI connector for the forward automation."

"The solution saves time in data discovery and understanding our entire organization's data."

"Data Intelligence allows us to automate multiple tasks we had previously done manually, such as restructuring the metadata for our purposes, setting up ETL flows, and defining the data tables we create. It also enables us to standardize our approach and our technical processes."

"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."

More Quest Data Intelligence pros

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

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

"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."

"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."

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

Cons

"Another area where it can improve is by having BB-Graph-type databases where relationship discovery and relationship identification are much easier."

"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."

"There may be some opportunities for improvement in terms of the user interface to make it a little bit more intuitive. They have made some good progress. Originally, when we started, we were on version 9 or 10. Over the last couple of releases, I've seen some improvements that they have made, but there might be a few other additional areas in UI where they can make some enhancements."

"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."

"It's a little bit clunky. I think a lot of these features were bolted on, and they don't necessarily transition smoothly in the interface. I would like to see a little more cohesion."

"In my opinion, the analytics part of erwin Data Intelligence is not satisfactory."

"There is room for improvement with respect to the connector and how to connect to the structured and unstructured database."

"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."

More Quest Data Intelligence cons

"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 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."

"The company has everything offshore."

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

Pricing and Cost Advice

"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."

"The solution is aggressively priced."

"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 price is too high."

"We operate on a yearly subscription and because it is an enterprise license we only have one. It is not dependent on the number of users."

"The price is reasonable, and a subscription is required."

"The price is reasonable and competitive. When you get into forward and reverse-engineering, the cost could go up. However, if you are a large organization, you would probably be able to access different packages. If, however, you don't need forward and reverse-engineering, then the price is relatively cheap."

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%

Construction Company

Financial Services Firm

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 ...

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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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