Try our new research platform with insights from 80,000+ expert users

Azure Data Factory vs Quest SharePlex 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:
 

Categories and Ranking

Azure Data Factory
Ranking in Data Integration
1st
Average Rating
8.0
Reviews Sentiment
6.9
Number of Reviews
90
Ranking in other categories
Cloud Data Warehouse (3rd)
Quest SharePlex
Ranking in Data Integration
49th
Average Rating
9.0
Reviews Sentiment
7.3
Number of Reviews
5
Ranking in other categories
No ranking in other categories
 

Mindshare comparison

As of April 2025, in the Data Integration category, the mindshare of Azure Data Factory is 9.5%, down from 12.7% compared to the previous year. The mindshare of Quest SharePlex is 0.7%, down from 0.7% 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.
MJ
Excellent replication with good stability and very helpful support
I don't know how easy it would be to change the architecture in an already implemented replication. For example, if we have a certain way of architecting for a particular database migration and want to change that during a period of time, is that an easy or difficult change? There was a need for us to change the architecture in-between the migration, but we didn't do it. We thought, "This is possibly complicated. Let's not change it in the middle because we were approaching our cutover date." That was one thing that we should have checked with support about for training. Also, maybe if we could have a seperate section of showing out-of-sync tables in Foglight, instead of looking into the "warning" messages.

Quotes from Members

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

Pros

"Allows more data between on-premises and cloud solutions"
"I enjoy the ease of use for the backend JSON generator, the deployment solution, and the template management."
"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."
"In terms of my personal experience, it works fine."
"Data Factory's best feature is the ease of setting up pipelines for data and cloud integrations."
"I find that the solution integrates well with cloud technologies, which we are using for different clouds like Snowflake and AWS"
"Data Factory's best features are simplicity and flexibility."
"I find the most valuable feature in Azure Data Factory to be its ability to handle large datasets."
"The core replication and its performance. Performance is crucial, and SharePlex is by far the fastest. The way it handles replication to multiple targets along with basic filtering, as well as from multiple sources to a single target, is very efficient."
"There are some capabilities within SharePlex where you can see how the data is migrating and if it still maintains good data integrity. For example, if there are some tables that get out of sync, there are ways to find them and fix the problem on the spot. Since these are very common issues, we can easily fix these types of problems using utilities, like compare and repair. So, if you find something is out of sync, then you can just repair that table. It basically syncs that table from source to target to see if there are any differences. It will then replicate those differences to the target."
"I like SharePlex's Compare and Repair tool."
"Because of the volume of the transactions, we heavily use a feature that allows SharePlex to replicate thousands of transactions. It's called PEP, Post Enhancement Performance, and that has helped us scale tremendously."
"The core features of the solution we like are the reliability of the data transfer and the accuracy of data read and write. The stability of the solution is also excellent."
 

Cons

"DataStage is easier to learn than Data Factory because it's more visual. Data Factory has some drag-and-drop options, but it's not as intuitive as DataStage. It would be better if they added more drag-and-drop features. You can start using DataStage without knowing the code. You don't need to learn how the code works before using the solution."
"There aren't many third-party extensions or plugins available in the solution."
"The one element of the solution that we have used and could be improved is the user interface."
"Snowflake connectivity was recently added and if the vendor provided some videos on how to create data then that would be helpful."
"The need to work more on developing out-of-the-box connectors for other products like Oracle, AWS, and others."
"Azure Data Factory should be cheaper to move data to a data center abroad for calamities in case of disasters."
"I do not have any notes for improvement."
"If the user interface was more user friendly and there was better error feedback, it would be helpful."
"I don't know how easy it would be to change the architecture in an already implemented replication. For example, if we have a certain way of architecting for a particular database migration and want to change that during a period of time, is that an easy or difficult change? There was a need for us to change the architecture in-between the migration, but we didn't do it. We thought, "This is possibly complicated. Let's not change it in the middle because we were approaching our cutover date." That was one thing that we should have checked with support about for training."
"The reporting features need improvement. It would be very good for users to have a clear understanding of the status of replication."
"For its function in relation to replication (i.e. filtering), I'd give it a six or seven out of 10. GoldenGate has much more functionality by comparison."
"I would like the solution to have some kind of machine learning and AI capabilities. Often, if we want to improve the performance of posting, we have to bump up a parameter. That means we need to stop the process, come up with a figure that we want to bump the parameter up to, and then start SharePlex. Machine learning and AI capabilities for these kinds of improvement would tremendously help boost productivity for us."
"I would like more ability to automate installation and configuration in line with some of the DevOps processes that are more mature in the market. That would be a considerable improvement."
 

Pricing and Cost Advice

"The price you pay is determined by how much you use it."
"It seems very low initially, but as the data grows, the solution’s bills grow exponentially."
"It's not particularly expensive."
"The licensing cost is included in the Synapse."
"The pricing model is based on usage and is not cheap."
"Data Factory is expensive."
"My company is on a monthly subscription for Azure Data Factory, but it's more of a pay-as-you-go model where your monthly invoice depends on how many resources you use. On a scale of one to five, pricing for Azure Data Factory is a four. It's just the usage fees my company pays monthly."
"I rate the product price as six on a scale of one to ten, where one is low price and ten is high price."
"It is not as expensive as Oracle GoldenGate and has worked really well within our budgets."
"It's really good value for the money. There are some things they could improve on, but in terms of the pricing, features, and support, as a holistic package, we are not thinking of anything else at this point in time."
report
Use our free recommendation engine to learn which Data Integration solutions are best for your needs.
847,862 professionals have used our research since 2012.
 

Top Industries

By visitors reading reviews
Financial Services Firm
14%
Computer Software Company
12%
Manufacturing Company
9%
Healthcare Company
7%
Financial Services Firm
19%
Computer Software Company
11%
Real Estate/Law Firm
7%
Manufacturing Company
6%
 

Company Size

By reviewers
Large Enterprise
Midsize Enterprise
Small Business
No data available
 

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...
Ask a question
Earn 20 points
 

Also Known As

No data available
Dell SharePlex, SharePlex
 

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
Bodybuilding.com, Priceline.com, Ameco Beijing, Viasat, SK Broadband
Find out what your peers are saying about Azure Data Factory vs. Quest SharePlex and other solutions. Updated: April 2025.
847,862 professionals have used our research since 2012.