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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
6.1
Azure Data Factory users save time and reduce costs, achieving ROI and enhanced satisfaction with centralized data integration.
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.
Data Engineer at Vthinktechnologies
 

Customer Service

Sentiment score
6.3
Azure Data Factory users praise support and documentation, but note delays and high costs in paid consulting services.
Sentiment score
6.7
StreamSets support is responsive and knowledgeable, offering effective solutions, though response times and technical handling could improve.
They are not slow on responding or very informative.
Sales & Projects Manger at ACS
The technical support is responsive and helpful
Sr. Technical Architect at Hexaware Technologies Limited
The technical support from Microsoft is rated an eight out of ten.
Chief Analytics Officer at Idiro Analytics
IBM technical support sometimes transfers tickets between different teams due to shift changes, which can be frustrating.
Enterprise Solutions Architect at a energy/utilities company with 1,001-5,000 employees
 

Scalability Issues

Sentiment score
7.4
Azure Data Factory is scalable and cloud-native, suitable for medium to large projects, despite some integration limitations.
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.
Chief Analytics Officer at Idiro Analytics
 

Stability Issues

Sentiment score
7.7
Azure Data Factory is reliable, with minor connection issues and improved stability, despite occasional backward compatibility changes.
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.
Chief Analytics Officer at Idiro Analytics
 

Room For Improvement

Azure Data Factory requires better integration, user interface, pricing, real-time processing, connectors, and improved compatibility with Azure services.
StreamSets struggles with integration, real-time processing, clarity in UI, memory issues, security, documentation, and cloud storage performance.
I suggest integrating some AI functionality to analyze data during the transition itself, providing insights such as null records, common records, and duplicates without running a separate pipeline or job.
Director at a computer software company with 1,001-5,000 employees
Sometimes, the compute fails to process data if there is a heavy load suddenly, and it doesn't scale up automatically.
Sr. Technical Architect at Hexaware Technologies Limited
It's very difficult to come up with even a general understanding of what expenses a client can have with this product.
Data Architect/Engineering manager at Intellias
It would be beneficial if StreamSets addressed any potential memory leak issues to prevent unnecessary upgrades.
Enterprise Solutions Architect at a energy/utilities company with 1,001-5,000 employees
 

Setup Cost

Azure Data Factory pricing is complex, varying with data usage and integrations, leading to unpredictable monthly costs.
StreamSets provides flexible pricing models, with varied user satisfaction, favoring larger enterprises over smaller companies due to cost.
The pricing is cost-effective.
Chief Analytics Officer at Idiro Analytics
It is considered cost-effective.
Sr. Technical Architect at Hexaware Technologies Limited
 

Valuable Features

Azure Data Factory excels with scalability, ease of use, robust data transformations, seamless orchestration, and extensive connector support.
StreamSets offers intuitive interface, extensive connectors, and features accessible to non-technical users for seamless data integration and manipulation.
The orchestration features in Azure Data Factory are definitely useful, as it is not only for Azure Data Factory; we can also include DataBricks and other services for integrating the data solution, making it a very beneficial feature.
Director at a computer software company with 1,001-5,000 employees
The platform excels in handling major datasets, particularly when working with Power BI for reporting purposes.
Data Engineer at Vthinktechnologies
It connects to different sources out-of-the-box, making integration much easier.
Sr. Technical Architect at Hexaware Technologies Limited
It allows a hybrid installation approach, rather than being completely cloud-based or on-premises.
Enterprise Solutions Architect at a energy/utilities company with 1,001-5,000 employees
 

Categories and Ranking

Azure Data Factory
Ranking in Data Integration
3rd
Average Rating
8.0
Reviews Sentiment
6.8
Number of Reviews
94
Ranking in other categories
Cloud Data Warehouse (2nd)
StreamSets
Ranking in Data Integration
24th
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 March 2026, in the Data Integration category, the mindshare of Azure Data Factory is 2.8%, down from 9.7% compared to the previous year. The mindshare of StreamSets is 1.2%, down from 1.6% compared to the previous year. It is calculated based on PeerSpot user engagement data.
Data Integration Mindshare Distribution
ProductMindshare (%)
Azure Data Factory2.8%
StreamSets1.2%
Other96.0%
Data Integration
 

Featured Reviews

KandaswamyMuthukrishnan - PeerSpot reviewer
Director at a computer software company with 1,001-5,000 employees
Integrates diverse data sources and streamlines ETL processes effectively
Regarding potential areas of improvement for Azure Data Factory, there is a need for better data transformation, especially since many people are now depending on DataBricks more for connectivity and data integration. Azure Data Factory should consider how to enhance integration or filtering for more transformations, such as integrating with Spark clusters. I am satisfied with Azure Data Factory so far, but I suggest integrating some AI functionality to analyze data during the transition itself, providing insights such as null records, common records, and duplicates without running a separate pipeline or job. The monitoring tools in Azure Data Factory are helpful for optimizing data pipelines; while the current feature is adequate, they can improve by creating a live dashboard to see the online process, including how much percentage has been completed, which will be very helpful for people who are monitoring the pipeline.
SS
Enterprise Solutions Architect at a energy/utilities company with 1,001-5,000 employees
Enables effective batch loading with visual interface and enterprise support
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 infrastructure. I had to switch to a new EC2 box, even though the processor was not fully utilized. It would be beneficial if StreamSets addressed any potential memory leak issues to prevent unnecessary upgrades. Additionally, it would be a great enhancement if StreamSets could produce a lineage graph to visualize how the data has passed through the system.
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Top Industries

By visitors reading reviews
Financial Services Firm
12%
Computer Software Company
11%
Manufacturing Company
9%
Government
6%
Financial Services Firm
9%
Insurance Company
8%
Manufacturing Company
8%
Real Estate/Law Firm
6%
 

Company Size

By reviewers
Large Enterprise
Midsize Enterprise
Small Business
By reviewers
Company SizeCount
Small Business31
Midsize Enterprise20
Large Enterprise57
By reviewers
Company SizeCount
Small Business9
Midsize Enterprise2
Large Enterprise11
 

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: March 2026.
884,797 professionals have used our research since 2012.