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SAP Data Hub vs SSIS comparison

 

Comparison Buyer's Guide

Executive Summary

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

SAP Data Hub
Average Rating
7.6
Reviews Sentiment
6.2
Number of Reviews
3
Ranking in other categories
Data Governance (26th), Metadata Management (8th)
SSIS
Average Rating
7.6
Reviews Sentiment
6.7
Number of Reviews
72
Ranking in other categories
Data Integration (4th)
 

Mindshare comparison

SAP Data Hub and SSIS aren’t in the same category and serve different purposes. SAP Data Hub is designed for Data Governance and holds a mindshare of 1.2%, down 1.4% compared to last year.
SSIS, on the other hand, focuses on Data Integration, holds 8.0% mindshare, up 8.0% since last year.
Data Governance
Data Integration
 

Featured Reviews

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.
BobAmy - PeerSpot reviewer
Robust and does a good job of handling overload conditions
We purchase an add-on called task factory primarily to allow bulk delete, update, and upsert capability. I'd like to see this be part of the standard package. I believe there are ways to build a model and set variables so that it can be a generic process. In my next system, I would like to have a generic process that would handle all the logging and processing in a model that can be modified and enhanced as the need for a better process, or different statistics to be logged is discovered. I'd want this in a way that the model can be changed and all the processes, with their unique parameters, could all be changed with the model upgraded. I believe they should add some features that help to create the code using a model. This would allow for continuous improvement of the model uses and easy replication of all the different programs that use the model.

Quotes from Members

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

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."
"The debugging capabilities are great, particularly during data flow execution. You can look into the data and see what's going on in the pipeline."
"The most valuable features for our company are the flexibility and the quick turn around time in producing simple ETL solutions."
"The setup is straightforward. It's very easy to install."
"We can connect with multiple data sources easily using an external connector in SSIS."
"SSIS is easy to use."
"Overall, it's a good product."
"The most valuable aspect of this solution is that it is simple to use and it offers a flexible custom script task."
"The script component is very powerful, things that you cannot normally do, is feasible through C#."
 

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."
"I have a tool called ZappySys. I need that tool to cut down on the complexity of SSIS. That tool really helps with a quick turnaround. I can do things quickly, and I can do things accurately. I can get better reporting on errors."
"Integration and the user interface are areas with certain shortcomings that require some improvements."
"SSIS is cumbersome despite its drag-and-drop functionality. For example, let's say I have 50 tables with 30 columns. You need to set a data type for each column and table. That's around 1,500 objects. It gets unwieldy adding validation for every column. Previously, SSIS automatically detected the data type, but I think they removed this feature. It would automatically detect if it's an integer, primary key, or foreign key column. You had fewer problems building the model."
"There were some issues when we tried to connect it to data storage. It was a connection issue."
"I come from a coding background and this tool is graphically based. Sometimes I think it's cumbersome to do mapping graphically. If there was a way to provide a simple script, it would be helpful and make it easier to use."
"The solution could improve by having quicker release updates."
"Options for scaling could be improved."
"The solution could improve on integrating with other types of data sources."
 

Pricing and Cost Advice

"The Cloud is very expensive, but SAP HANA previous service is okay."
"People have to opt for a perpetual-based licensing model."
"Our license with SSIS is annual."
"My advice is to look at what your configuration will be because most companies have their own deals with Microsoft."
"Based on my experience and understanding, Talend comes out to be a little bit expensive as compared to SSIS. The average cost of having Talend with Talend Management Console is around 72K per region, which is much higher than SSIS. SSIS works very well with Microsoft technologies, and if you have Microsoft technologies, it is not really expensive to have SSIS. If you have SQL Server, SSIS is free."
"The solution comes free of cost."
"All of my clients have this product included as part of their Microsoft license."
"If you don't want to pay a lot of money, you can go for SSIS, as its open-source version is available. When it comes to licensing, SSIS can be expensive."
"The solution is available at a lesser price than that of Informatica."
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Comparison Review

it_user90069 - PeerSpot reviewer
Feb 20, 2014
Informatica PowerCenter vs. Microsoft SSIS - each technology has its advantages but also have similarities
Technology has made it easier for businesses to organize and manipulate data to get a clearer picture of what’s going on with their business. Notably, ETL tools have made managing huge amounts of data significantly easier and faster, boosting many organizations’ business intelligence operations…
 

Top Industries

By visitors reading reviews
Manufacturing Company
14%
Computer Software Company
14%
Financial Services Firm
14%
Government
10%
Financial Services Firm
18%
Computer Software Company
12%
Government
8%
Healthcare Company
7%
 

Company Size

By reviewers
Large Enterprise
Midsize Enterprise
Small Business
No data available
 

Questions from the Community

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...
Which is better - SSIS or Informatica PowerCenter?
SSIS PowerPack is a group of drag and drop connectors for Microsoft SQL Server Integration Services, commonly called SSIS. The collection helps organizations boost productivity with code-free compo...
What do you like most about SSIS?
The product's deployment phase is easy.
 

Also Known As

No data available
SQL Server Integration Services
 

Overview

 

Sample Customers

Kaeser Kompressoren, HARTMANN
1. Amazon.com 2. Bank of America 3. Capital One 4. Coca-Cola 5. Dell 6. E*TRADE 7. FedEx 8. Ford Motor Company 9. Google 10. Home Depot 11. IBM 12. Intel 13. JPMorgan Chase 14. Kraft Foods 15. Lockheed Martin 16. McDonald's 17. Microsoft 18. Morgan Stanley 19. Nike 20. Oracle 21. PepsiCo 22. Procter & Gamble 23. Prudential Financial 24. RBC Capital Markets 25. SAP 26. Siemens 27. Sony 28. Toyota 29. UnitedHealth Group 30. Visa 31. Walmart 32. Wells Fargo
Find out what your peers are saying about Microsoft, Informatica, Collibra and others in Data Governance. Updated: January 2025.
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