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Azure Data Factory vs StreamSets comparison

 

Comparison Buyer's Guide

Executive SummaryUpdated on Dec 19, 2024

Review summaries and opinions

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

ROI

Sentiment score
7.3
Azure Data Factory enhances efficiency, centralizes data, reduces costs, and improves data analysis, offering significant financial and operational benefits.
Sentiment score
8.1
StreamSets speeds up data processing, boosts efficiency and revenue, simplifies tasks, enhances security, and reduces costs significantly.
Our stakeholders and clients have expressed satisfaction with Azure Data Factory's efficiency and cost-effectiveness.
 

Customer Service

Sentiment score
6.5
Azure Data Factory support is responsive but varies in speed, with community resources and documentation aiding user satisfaction.
Sentiment score
6.7
StreamSets support is responsive and knowledgeable, offering effective solutions, though response times and technical handling could improve.
The technical support from Microsoft is rated an eight out of ten.
The technical support is responsive and helpful
The technical support for Azure Data Factory is generally acceptable.
IBM technical support sometimes transfers tickets between different teams due to shift changes, which can be frustrating.
 

Scalability Issues

Sentiment score
7.5
Azure Data Factory excels in scalability, efficiently managing workloads for any size, despite higher costs than alternatives.
Sentiment score
7.6
StreamSets is scalable and flexible, favored for cloud use but could improve auto-scaling for large data migrations.
Azure Data Factory is highly scalable.
 

Stability Issues

Sentiment score
7.8
Azure Data Factory is stable and reliable, but faces integration challenges and requires enhancements to compete with top competitors.
Sentiment score
7.8
StreamSets is praised for stability and reliability, despite minor memory issues, with high user ratings and market competitiveness.
The solution has a high level of stability, roughly a nine out of ten.
 

Room For Improvement

Azure Data Factory needs improved integration, better scheduling, enhanced UI, simplified pricing, more connectors, and responsive support.
StreamSets struggles with integration, real-time processing, clarity in UI, memory issues, security, documentation, and cloud storage performance.
There is a problem with the integration with third-party solutions, particularly with SAP.
When using Git services, there are challenges with linked services and triggers getting overridden when moving between different environments (Dev, UAT, Prod).
Sometimes, the compute fails to process data if there is a heavy load suddenly, and it doesn't scale up automatically.
It would be beneficial if StreamSets addressed any potential memory leak issues to prevent unnecessary upgrades.
 

Setup Cost

Azure Data Factory pricing is usage-based and cost-effective, but large data volumes can lead to increased expenses.
StreamSets provides flexible pricing models, with varied user satisfaction, favoring larger enterprises over smaller companies due to cost.
The pricing is cost-effective.
It is considered cost-effective.
 

Valuable Features

Azure Data Factory provides seamless data integration, robust transformations, scalability, and strong SAP support, praised for its ease of use.
StreamSets offers intuitive interface, extensive connectors, and features accessible to non-technical users for seamless data integration and manipulation.
It connects to different sources out-of-the-box, making integration much easier.
The platform excels in handling major datasets, particularly when working with Power BI for reporting purposes.
The interface of Azure Data Factory is very usable with a more interactive visual experience, making it easier for people who are not as experienced in coding to work with.
It allows a hybrid installation approach, rather than being completely cloud-based or on-premises.
 

Categories and Ranking

Azure Data Factory
Ranking in Data Integration
1st
Average Rating
8.0
Reviews Sentiment
7.0
Number of Reviews
91
Ranking in other categories
Cloud Data Warehouse (2nd)
StreamSets
Ranking in Data Integration
22nd
Average Rating
8.4
Reviews Sentiment
7.0
Number of Reviews
21
Ranking in other categories
No ranking in other categories
 

Mindshare comparison

As of June 2025, in the Data Integration category, the mindshare of Azure Data Factory is 8.4%, down from 12.3% compared to the previous year. The mindshare of StreamSets is 1.6%, up from 1.4% compared to the previous year. It is calculated based on PeerSpot user engagement data.
Data Integration
 

Featured Reviews

Joy Maitra - PeerSpot reviewer
Facilitates seamless data pipeline creation with good analytics and and thorough monitoring
Azure Data Factory is a low code, no code platform, which is helpful. It provides many prebuilt functionalities that assist in building data pipelines. Also, it facilitates easy transformation with all required functionalities for analytics. Furthermore, it connects to different sources out-of-the-box, making integration much easier. The monitoring is very thorough, though a more readable version would be appreciable.
Ved Prakash Yadav - PeerSpot reviewer
Useful for data transformation and helps with column encryption
We use various tools and alerting systems to notify us of pipeline errors or failures. StreamSets supports data governance and compliance by allowing us to encrypt incoming data based on specified rules. We can easily encrypt columns by providing the column name and hash key. If you're considering using StreamSets for the first time, I would advise first understanding why you want to use it and how it will benefit you. If you're dealing with change tracking or handling large amounts of data, it could be cost-effective compared to services like Amazon. It's easy to schedule and manage tasks with the tool, and you can enhance your skills as an ETL developer. You can easily migrate traditional pipelines built on platforms like Informatica or Talend to StreamSets. I rate the overall solution an eight out of ten.
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Use our free recommendation engine to learn which Data Integration solutions are best for your needs.
856,873 professionals have used our research since 2012.
 

Top Industries

By visitors reading reviews
Financial Services Firm
14%
Computer Software Company
12%
Manufacturing Company
9%
Government
6%
Financial Services Firm
13%
Computer Software Company
11%
Manufacturing Company
10%
Insurance Company
9%
 

Company Size

By reviewers
Large Enterprise
Midsize Enterprise
Small Business
 

Questions from the Community

How do you select the right cloud ETL tool?
AWS Glue and Azure Data factory for ELT best performance cloud services.
How does Azure Data Factory compare with Informatica PowerCenter?
Azure Data Factory is flexible, modular, and works well. In terms of cost, it is not too pricey. It offers the stability and reliability I am looking for, good scalability, and is easy to set up an...
How does Azure Data Factory compare with Informatica Cloud Data Integration?
Azure Data Factory is a solid product offering many transformation functions; It has pre-load and post-load transformations, allowing users to apply transformations either in code by using Power Q...
What do you like most about StreamSets?
The best thing about StreamSets is its plugins, which are very useful and work well with almost every data source. It's also easy to use, especially if you're comfortable with SQL. You can customiz...
What needs improvement with StreamSets?
One issue I observed with StreamSets is that the memory runs out quickly when processing large volumes of data. Because of this memory issue, we have to upgrade our EC2 boxes in the Amazon AWS infr...
What is your primary use case for StreamSets?
We are using StreamSets for batch loading.
 

Overview

 

Sample Customers

1. Adobe 2. BMW 3. Coca-Cola 4. General Electric 5. Johnson & Johnson 6. LinkedIn 7. Mastercard 8. Nestle 9. Pfizer 10. Samsung 11. Siemens 12. Toyota 13. Unilever 14. Verizon 15. Walmart 16. Accenture 17. American Express 18. AT&T 19. Bank of America 20. Cisco 21. Deloitte 22. ExxonMobil 23. Ford 24. General Motors 25. IBM 26. JPMorgan Chase 27. Microsoft (Azure Data Factory is developed by Microsoft) 28. Oracle 29. Procter & Gamble 30. Salesforce 31. Shell 32. Visa
Availity, BT Group, Humana, Deluxe, GSK, RingCentral, IBM, Shell, SamTrans, State of Ohio, TalentFulfilled, TechBridge
Find out what your peers are saying about Azure Data Factory vs. StreamSets and other solutions. Updated: June 2025.
856,873 professionals have used our research since 2012.