Azure Data Factory vs StreamSets comparison

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Azure Data Factory

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Executive Summary

We performed a comparison between Azure Data Factory and StreamSets based on real PeerSpot user reviews.

Find out in this report how the two Data Integration solutions compare in terms of features, pricing, service and support, easy of deployment, and ROI.

To learn more, read our detailed Azure Data Factory vs. StreamSets Report (Updated: May 2024).

Azure Data Factory vs. StreamSets

May 2024

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Helped 787,061 peers since 2012

Categories and Ranking

Azure Data Factory

Ranking in Data Integration

1st

Average Rating

8.0

Number of Reviews

Ranking in other categories

Cloud Data Warehouse (3rd)

StreamSets

Ranking in Data Integration

8th

Average Rating

8.4

Number of Reviews

Ranking in other categories

No ranking in other categories

Market share comparison

As of June 2024, in the Data Integration category, the market share of Azure Data Factory is 9.6% and it decreased by 29.4% compared to the previous year. The market share of StreamSets is 1.6% and it increased by 29.9% compared to the previous year. It is calculated based on PeerSpot user engagement data.

Data Integration

Unique Categories:

Cloud Data Warehouse

13.6%

No other categories found

Featured Reviews

Zubair_Ahmed

Senior Consultant at Veraqor

Nov 30, 2023

Seamless cloud-based data integration providing a versatile platform with scalable data processing, diverse data connectors, and comprehensive monitoring and management capabilities

My task involves extracting data from a source, performing necessary transformations, and subsequently loading the data into a target destination, which happens to be Azure SQL Database The company is experiencing significant benefits as one of our customers is successfully implementing the…

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Namanya Brian

CEO-founder at Tubayo

Apr 14, 2023

Data streams and pipelines help our team identify areas for improvement in our solution

One of the things I like is the data pipelines. They have a very good design. Implementing pipelines is very straightforward. It doesn't require any technical skill. We have also integrated it with Kafka messaging and it is not complex to do. It is really so easy to connect or integrate with data interfaces. And moving data into analytics platforms using StreamSets is easy. It doesn't require any coding, meaning your can transfer or move data into data payloads without coding skills. It's a good move, for someone in the beginning, who doesn't have any knowledge because it's quite easy.

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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

"Data Factory's best features are connectivity with different tools and focusing data ingestion using pipeline copy data."

"The most valuable features are data transformations."

"Feature-wise, one of the most valuable ones is the data flows introduced recently in the solution."

"On the tool itself, we've never experienced any bugs or glitches. There haven't been crashes. Stability has been good."

"It's extremely consistent."

"It is easy to deploy workflows and schedule jobs."

"The best part of this product is the extraction, transformation, and load."

"Data Factory's most valuable feature is Copy Activity."

More Azure Data Factory pros

"Also, the intuitive canvas for designing all the streams in the pipeline, along with the simplicity of the entire product are very big pluses for me. The software is very simple and straightforward. That is something that is needed right now."

"In StreamSets, everything is in one place."

"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 customize it to do what you need. Many other tools have started to use features similar to those introduced by StreamSets, like automated workflows that are easy to set up."

"It is a very powerful, modern data analytics solution, in which you can integrate a large volume of data from different sources. It integrates all of the data and you can design, create, and monitor pipelines according to your requirements. It is an all-in-one day data ops solution."

"The scheduling within the data engineering pipeline is very much appreciated, and it has a wide range of connectors for connecting to any data sources like SQL Server, AWS, Azure, etc. We have used it with Kafka, Hadoop, and Azure Data Factory Datasets. Connecting to these systems with StreamSets is very easy."

"StreamSets Transformer is a good feature because it helps you when you are developing applications and when you don't want to write a lot of code. That is the best feature overall."

"Important features include that it comprises lots of functionality to connect data from various sources through connector availability, scheduling pipelines at any time, and integration with third-party and security solutions for encryption."

"One of the things I like is the data pipelines. They have a very good design. Implementing pipelines is very straightforward. It doesn't require any technical skill."

More StreamSets pros

Cons

"You cannot use a custom data delimiter, which means that you have problems receiving data in certain formats."

"Azure Data Factory can improve by having support in the drivers for change data capture."

"Azure Data Factory can improve the transformation features. You have to do a lot of transformation activities. This is something that is just not fully covered. Additionally, the integration could improve for other tools, such as Azure Data Catalog."

"The number of standard adaptors could be extended further."

"The product's technical support has certain shortcomings, making it an area where improvements are required."

"The support and the documentation can be improved."

"One area for improvement is documentation. At present, there isn't enough documentation on how to use Azure Data Factory in certain conditions. It would be good to have documentation on the various use cases."

"Real-time replication is required, and this is not a simple task."

More Azure Data Factory cons

"The software is very good overall. Areas for improvement are the error logging and the version history. I would like to see better, more detailed error logging information."

"One thing that I would like to add is the ability to manually enter data. The way the solution currently works is we don't have the option to manually change the data at any point in time. Being able to do that will allow us to do everything that we want to do with our data. Sometimes, we need to manually manipulate the data to make it more accurate in case our prior bifurcation filters are not good. If we have the option to manually enter the data or make the exact iterations on the data set, that would be a good thing."

"The monitoring visualization is not that user-friendly. It should include other features to visualize things, like how many records were streamed from a source to a destination on a particular date."

"The design experience is the bane of our existence because their documentation is not the best. Even when they update their software, they don't publish the best information on how to update and change your pipeline configuration to make it conform to current best practices. We don't pay for the added support. We use the "freeware version." The user community, as well as the documentation they provide for the standard user, are difficult, at best."

"We often faced problems, especially with SAP ERP. We struggled because many columns weren't integers or primary keys, which StreamSets couldn't handle. We had to restructure our data tables, which was painful. Also, pipeline failures were common, and data drifting wasn't addressed, which made things worse. Licensing was another issue we encountered."

"I would like to see further improvement in the UI. In addition, upgrades are not automatic and they should be automated. Currently, we have to manually upgrade versions."

"I would like to see it integrate with other kinds of platforms, other than Java. We're going to have a lot of applications using .NET and other languages or frameworks. StreamSets is very helpful for the old Java platform but it's hard to integrate with the other platforms and frameworks."

"We create pipelines or jobs in StreamSets Control Hub. It is a great feature, but if there is a way to have a folder structure or organize the pipelines and jobs in Control Hub, it would be great. I submitted a ticket for this some time back."

More StreamSets cons

Pricing and Cost Advice

"I would not say that this product is overly expensive."

"Pricing is comparable, it's somewhere in the middle."

"Our licensing fees are approximately 15,000 ($150 USD) per month."

"I am aware of the pricing of Azure Data Factory, but I prefer not to disclose specific details."

"Data Factory is affordable."

"The pricing model is based on usage and is not cheap."

"I rate the product price as six on a scale of one to ten, where one is low price and ten is high price."

"The licensing is a pay-as-you-go model, where you pay for what you consume."

More Azure Data Factory pricing and cost advice

"It's not expensive because you pay per month, and the tasks you can perform with it are huge. It's reliable and cost-effective."

"There are different versions of the product. One is the corporate license version, and the other one is the open-source or free version. I have been using the corporate license version, but they have recently launched a new open-source version so that anybody can create an account and use it. The licensing cost varies from customer to customer. I don't have a lot of input on that. It is taken care of by PMO, and they seem fine with its pricing model. It is being used enterprise-wide. They seem to have got a good deal for StreamSets."

"The pricing is too fixed. It should be based on how much data you need to process. Some businesses are not so big that they process a lot of data."

"StreamSets is an expensive solution."

"We use the free version. It's great for a public, free release. Our stance is that the paid support model is too expensive to get into. They should honestly reevaluate that."

"It's not so favorable for small companies."

"StreamSets is expensive, especially for small businesses."

"I believe the pricing is not equitable."

More StreamSets pricing and cost advice

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Top Industries

By visitors reading reviews

Computer Software Company

13%

Financial Services Firm

13%

Manufacturing Company

Healthcare Company

Financial Services Firm

17%

Computer Software Company

13%

Manufacturing Company

Government

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?

We often faced problems, especially with SAP ERP. We struggled because many columns weren't integers or primary keys, which StreamSets couldn't handle. We had to restructure our data tables, which ...

What is your primary use case for StreamSets?

StreamSets is used for data transformation rather than ETL processes. It focuses on transforming data directly from sources without handling the extraction part of the process. The transformed data...

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Product Reports

Download Azure Data Factory product report

Azure Data Factory

June 2024

Download StreamSets product report

May 2024

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Overview

Azure Data Factory efficiently manages and integrates data from various sources, enabling seamless movement and transformation across platforms. Its valuable features include seamless integration with Azure services, handling large data volumes, flexible transformation, user-friendly interface, extensive connectors, and scalability. Users have experienced improved team performance, workflow simplification, enhanced collaboration, streamlined processes, and boosted productivity.

StreamSets is a data integration platform that enables organizations to efficiently move and process data across various systems. It offers a user-friendly interface for designing, deploying, and managing data pipelines, allowing users to easily connect to various data sources and destinations. StreamSets also provides real-time monitoring and alerting capabilities, ensuring that data is flowing smoothly and any issues are quickly addressed.

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