SAP Data Hub vs erwin Data Intelligence comparison

Quest Software and SAP are both solutions in the Data Governance category. Quest Software is ranked #16 with an average rating of 8.0, while SAP is ranked #31. Quest Software holds a 1.9% mindshare in DG, compared to SAP’s 1.1% mindshare. Additionally, 100% of Quest Software users are willing to recommend the solution, compared to 66% of SAP users who would recommend it.

erwin Data Intelligence

Read 19 erwin Data Intelligence reviews

2,813 Views
2,757 Comparison Views

100% willing to recommend

SAP Data Hub

Read 3 SAP Data Hub reviews

1,254 Views
665 Comparison Views

66% willing to recommend

erwin Data Intelligence

SAP Data Hub

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Executive SummaryUpdated on Nov 23, 2025

SAP Data Hub and erwin Data Intelligence are competing products in data management. SAP Data Hub has the upper hand in managing complex data landscapes, while erwin Data Intelligence is stronger in metadata-driven data governance.

Features: SAP Data Hub offers robust data integration, orchestration capabilities, and cross-system data processing. Erwin Data Intelligence focuses on metadata management, data lineage, and streamlined governance.

Ease of Deployment and Customer Service: SAP Data Hub provides flexible deployment integrated with SAP environments, tailored support, but can be challenging due to system complexity. Erwin Data Intelligence offers easy deployment with SaaS offerings and user-centric support, accessible for diverse IT ecosystems.

Pricing and ROI: SAP Data Hub often has a higher initial setup cost but delivers significant ROI for SAP-centric organizations. Erwin Data Intelligence presents a cost-effective setup with flexible licensing, offering rapid ROI through its governance features.

To learn more, read our detailed SAP Data Hub vs. erwin Data Intelligence Report (Updated: February 2026).

Buyer's Guide

SAP Data Hub vs. erwin Data Intelligence

February 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

erwin Data Intelligence

Ranking in Data Governance

16th

Average Rating

8.4

Reviews Sentiment

7.6

Number of Reviews

Ranking in other categories

AI Governance (3rd)

SAP Data Hub

Ranking in Data Governance

31st

Average Rating

7.6

Reviews Sentiment

6.8

Number of Reviews

Ranking in other categories

Metadata Management (14th)

Mindshare comparison

As of February 2026, in the Data Governance category, the mindshare of erwin Data Intelligence is 1.9%, down from 2.0% compared to the previous year. The mindshare of SAP Data Hub is 1.1%, up from 1.0% compared to the previous year. It is calculated based on PeerSpot user engagement data.

Data Governance Market Share Distribution
Product	Market Share (%)
erwin Data Intelligence	1.9%
SAP Data Hub	1.1%
Other	97.0%

Data Governance

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

"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."

"Overall, DI's data cataloging, data literacy, and automation have helped our decision-makers because when a source wants to change something, we immediately know what the impact is going to be downstream."

"The possibility to write automation scripts is the biggest benefit for us. We have several products with metadata and metadata mapping capabilities. The big difference when we were choosing this product was the ability to run automation scripts against metadata and metadata mappings. Right now, we have a very high level of automation based on these automation scripts, so it's really the core feature for us."

"There is a wide range of widgets that enables the user to find the proper information quickly. The presentation of information is something very valuable."

"The data mapping manager is the most valuable feature."

"We always know where our data is, and anybody can look that up, whether they're a business person who doesn't know anything about Informatica, or a developer who knows everything about creating data movement jobs in Informatica, but who does not understand the business terminology or the data that is being used in the tool."

"It is a central place for everybody to start any ETL data pipeline builds. This tool is being heavily used, plus it's heavily integrated with all the ETL data pipeline design and build processes. Nobody can bypass these processes and do something without going through this tool."

"The solution gives us data lineage which means we can see an impact if we make a change. The ability for us to have that in this company is brilliant because we used to have 49 data stewards from some 23 different groups within six major departments. Each one of those was a silo unto itself. The ability to have different glossaries — but all pointed to the same key terms, key concepts, or key attributes — has made life really simple."

More erwin Data Intelligence pros

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

"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."

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

Cons

"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."

"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."

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

"The data quality assessment requires third-party components and a separate license."

"There are a lot of little things like moving between read screens and edit screens. Those little human interface type of programming pieces will need to mature a bit to make it easier to get to where you want to go to put the stuff in."

"Really huge datasets, where the logical names or the lexicons weren't groomed or maintained well, were the only area where it really had room for improvement. A huge data set would cause erwin to crash. If there were half a million or 1 million tables, erwin would hang."

"The versioning can sometimes be confusing because we use the publishing feature for the mapping. Technical analysts sometimes have two versions, and they should know that the public version is the correct one."

"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."

More erwin Data Intelligence cons

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

"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."

Pricing and Cost Advice

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

"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."

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

"Smart Data Connectors have some costs, and then there are user-based licenses. We spend roughly $150,000 per year on the solution. It is a yearly subscription license that basically includes the cost for Smart Data Connectors and user-based licenses. We have around 30 data stewards who maintain definitions, and then we have five IT users who basically maintain the overall solution. It is not a SaaS kind of operation, and there is an infrastructure cost to host this solution, which is our regular AWS hosting cost."

"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 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 price is too high."

"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."

More erwin 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

14%

Government

10%

Educational Organization

Manufacturing Company

19%

Financial Services Firm

13%

Government

10%

Computer Software Company

Company Size

By reviewers

Large Enterprise

Midsize Enterprise

Small Business

By reviewers
Company Size	Count
Small Business	2
Midsize Enterprise	4
Large Enterprise	14

No data available

Questions from the Community

What needs improvement with erwin Data Intelligence by Quest?

The dashboard in erwin Data Intelligence is customizable, and you can easily create different views. However, you are confined to the widgets that are already provided, so the customization is some...

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

erwin Data Intelligence serves two primary use cases: one is where people use it as a data catalog, which is one of the main ones, and the other is for traceability and lineage.

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

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Comparisons

Collibra Platform vs erwin Data Intelligence

Compared 25% of the time

Microsoft Purview Data Governance vs erwin Data Intelligence

Compared 19% of the time

Informatica Intelligent Data Management Cloud (IDMC) vs erwin Data Intelligence

Compared 10% of the time

Alation Data Catalog vs erwin Data Intelligence

Compared 10% of the time

Microsoft Purview Data Lifecycle Management vs erwin Data Intelligence

Compared 6% of the time

More erwin Data Intelligence Competitors

Microsoft Purview Data Governance vs SAP Data Hub

Compared 15% of the time

Collibra Platform vs SAP Data Hub

Compared 13% of the time

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

Compared 13% of the time

Palantir Foundry vs SAP Data Hub

Compared 10% of the time

Oracle Data Integrator (ODI) vs SAP Data Hub

Compared 7% of the time

More SAP Data Hub Competitors

Product Reports

Buyer's Guide

erwin Data Intelligence

February 2026

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Buyer's Guide

Data Governance

January 2026

Download SAP Data Hub product report

Also Known As

erwin DG, erwin Data Governance

No data available

Overview

Erwin Data Intelligence drives automation, supports data catalog and literacy, and offers Smart Data Connectors for efficient metadata handling. Its customization flexibility and integration facilitate enhanced data governance, visualization, analysis, and compliance.

Erwin Data Intelligence offers automation scripts that accelerate development, integrated data cataloging, data profiling, and lineage analysis to streamline information management. Users appreciate its capability in metadata harvesting, code engineering, and infrastructure integration. The tool provides flexibility to enhance governance and data visualization. While it performs well, users have noted challenges with API robustness and interface complexity, and there are opportunities to improve workflow integration, AI features, and large dataset handling. Companies rely on it for metadata management, automation of metadata mappings, and data governance to support compliance and literacy.

What are the main features of Erwin Data Intelligence?

Automation Scripts: Speeds up development processes through powerful scripts.
Data Catalog: Supports comprehensive data mapping and profiles for better analysis.
Smart Data Connectors: Efficiently handles code engineering and metadata harvesting.
Customization Flexibility: Adapts to existing infrastructure for seamless integration.
Comprehensive Visualization: Empowers data visualization and standardization processes.

What benefits and ROI can users expect?

Increased Development Speed: Automation scripts notably enhance development efficiency.
Improved Data Governance: Streamlines processes, supporting compliance and business definitions.
Effective Integration: Seamlessly fits with ETL tools and existing workflows.
Enhanced Data Literacy: Supports data literacy initiatives with robust cataloging features.
Comprehensive Impact Analysis: Facilitates thorough analysis for informed decision-making.

In industries such as finance, healthcare, and retail, organizations implement Erwin Data Intelligence for efficient metadata management and governance. It assists in automating lineage and mapping, supporting ETL procedures while enhancing compliance and data literacy efforts. Its flexibility and integration support create valuable data insights and governance improvements.

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

Buyer's Guide

SAP Data Hub vs. erwin Data Intelligence

February 2026

Free Report: SAP Data Hub vs. erwin Data Intelligence

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