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SAP Data Hub vs erwin Data Intelligence comparison

 

Comparison Buyer's Guide

Executive SummaryUpdated on Aug 19, 2025

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
28th
Average Rating
8.6
Reviews Sentiment
7.4
Number of Reviews
18
Ranking in other categories
AI Governance (17th)
SAP Data Hub
Ranking in Data Governance
30th
Average Rating
7.6
Reviews Sentiment
6.8
Number of Reviews
3
Ranking in other categories
Metadata Management (12th)
 

Mindshare comparison

As of October 2025, in the Data Governance category, the mindshare of erwin Data Intelligence is 1.8%, down from 2.5% compared to the previous year. The mindshare of SAP Data Hub is 1.0%, down from 1.2% compared to the previous year. It is calculated based on PeerSpot user engagement data.
Data Governance Market Share Distribution
ProductMarket Share (%)
erwin Data Intelligence1.8%
SAP Data Hub1.0%
Other97.2%
Data Governance
 

Featured Reviews

Roy Pollack - PeerSpot reviewer
The solution provides more profound insights into legacy data movements, lineages, and definitions in the short term.
We have loaded over 300,000 attributes and more than 1000 mappings. The performance is slow, depending on the lineage or search. This is supposed to be fixed in the later versions, but we haven't upgraded yet. 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.
VM
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.

Quotes from Members

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

Pros

"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."
"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."
"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 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."
"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."
"Mind map... is a really good feature because it is very helpful in seeing which column's tables are related. Also, you can flag them with "sensitive data" and other indicators. You can also customize your own features for the mind map. That was another very robust feature."
"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 saves time in data discovery and understanding our entire organization's data."
"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"
"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."
 

Cons

"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 solution's Arabic language processing is limited. The results are limited when you use the interface in Arabic."
"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."
"The technical support could be improved."
"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."
"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."
"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."
"Nowadays there are some inconsistencies in data bases, however, they upgrade and release the versions to market."
"The company has everything offshore."
 

Pricing and Cost Advice

"erwin was at a good price. The federal government wouldn't buy something if the pricing wasn't good."
"erwin's pricing was cheaper than its competitors."
"The licensing cost is around $7,000 for user. This is an estimation."
"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."
"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."
"erwin is cheaper than other solutions and this should appeal to other buyers. It has a good price tag."
"The solution is aggressively priced."
"The price is too high."
"The Cloud is very expensive, but SAP HANA previous service is okay."
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Top Industries

By visitors reading reviews
Computer Software Company
26%
Financial Services Firm
11%
Government
7%
Insurance Company
6%
Manufacturing Company
17%
Financial Services Firm
14%
Government
11%
Computer Software Company
10%
 

Company Size

By reviewers
Large Enterprise
Midsize Enterprise
Small Business
By reviewers
Company SizeCount
Small Business1
Midsize Enterprise4
Large Enterprise14
No data available
 

Questions from the Community

Ask a question
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What do you like most about SAP Data Hub?
SAP is one of the most seamless ERPs that have integrated SAP archiving within Excel. I have not seen this with any other database.
What needs improvement with SAP Data Hub?
We moved from Oracle. If you're aware of your monitoring system, the RPU market, and the managed system, you should move to HANA, which is an innovative database built by SAP itself. However, this ...
What is your primary use case for SAP Data Hub?
I technically handle the database, like cycle management projects. When transaction data comes in, we see it based on the retention periods. We have to move the data to some secure storage rather t...
 

Also Known As

erwin DG, erwin Data Governance
No data available
 

Overview

 

Sample Customers

Oracle, Infosys, GSK, Toyota Motor Sales, HSBC
Kaeser Kompressoren, HARTMANN
Find out what your peers are saying about SAP Data Hub vs. erwin Data Intelligence and other solutions. Updated: September 2025.
869,566 professionals have used our research since 2012.