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Azure Data Factory vs Integrate.io Platform 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

Azure Data Factory
Ranking in Data Integration
5th
Average Rating
8.0
Reviews Sentiment
6.7
Number of Reviews
96
Ranking in other categories
Cloud Data Warehouse (7th)
Integrate.io Platform
Ranking in Data Integration
40th
Average Rating
8.6
Reviews Sentiment
7.1
Number of Reviews
3
Ranking in other categories
Data Observability (6th)
 

Mindshare comparison

As of August 2026, in the Data Integration category, the mindshare of Azure Data Factory is 2.3%, down from 7.2% compared to the previous year. The mindshare of Integrate.io Platform is 0.5%, up from 0.1% compared to the previous year. It is calculated based on PeerSpot user engagement data.
Data Integration Mindshare Distribution
ProductMindshare (%)
Azure Data Factory2.3%
Integrate.io Platform0.5%
Other97.2%
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.
RP
Founder at Rembrand Pardo Consulting
Streamlines daily data workflows and has improved reliability for complex business integrations
One area where Integrate.io Platform could improve is around visibility and debugging. While the logging is helpful, it can sometimes take time to trace issues across multiple steps in a pipeline, especially when flows become complex. A more streamlined way to track data through each stage or clearer error messaging would make troubleshooting faster and more intuitive. Another improvement would be flexibility in handling edge cases. For standard transformations, it works well, but when business logic gets more complex, it can feel a bit limited without introducing workarounds. Having more advanced customization options without sacrificing the ease of use would be a big plus, in my opinion. Documentation clarity around existing pipelines was also something I felt could be better supported. Since integrations tend to evolve over time, having strong built-in documentation features or easier ways to understand dependencies between jobs would have helped, especially when onboarding someone new. I only stayed with this client for six months, so we needed to bring or train their team members to do this. Revisiting flows after a while would have been nice. The last thing would be performance transparency could be improved. Jobs generally run reliably, but having clearer insights into performance, such as bottlenecks, processing time per step, or optimizing suggestions would make it easier to fine-tune workflows as data volume grows. Part of my job, and what the client in this case wanted, was to scale in the future without having to change to another tool, so that would help a lot. I would say the platform is solid, but these kinds of improvements that I mentioned would make it even more efficient to manage at scale and over time.

Quotes from Members

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

Pros

"Azure Data Factory is a very easy to use ETL tool for loading and transforming data from one location to another."
"The user interface is very good. It makes me feel very comfortable when I am using the tool."
"The most important feature is that it can help you do the multi-threading concepts."
"I like the basic features like the data-based pipelines."
"It's cloud-based, allowing multiple users to easily access the solution from the office or remote locations. I like that we can set up the security protocols for IP addresses, like allow lists. It's a pretty user-friendly product as well. The interface and build environment where you create pipelines are easy to use. It's straightforward to manage the digital transformation pipelines we build."
"It has big potential, especially as a PaaS offering."
"The features that I've found most valuable, in order: That it is a complete ETL Solution, the second one is interface, the third one workflow, and the fourth one ease of use."
"The most valuable features of the solution are its ease of use and the readily available adapters for connecting with various sources."
"Integrate.io Platform has positively impacted my organization by reducing a lot of our workloads because we can make this replication faster and connect it with other connectors, and it also gives us this GPU that allows us to work faster."
"Integrate.io Platform has helped simplify my data pipelines, as it is really good with Salesforce sync."
"I think the platform helped them move forward towards a more streamlined, reliable, and scalable way of handling their data operations."
 

Cons

"Azure Data Factory uses many resources and has issues with parallel workflows."
"Sometimes, the compute fails to process data if there is a heavy load suddenly, and it doesn't scale up automatically."
"Technical support isn't the best, as it's a bit delayed at times. Whenever we need some urgent support, wherein we have to restart or something has stuck, it takes a bit of time."
"It would be helpful if they could adjust the data capture feature so that when there are source-side changes ADF could automatically figure it out."
"On the UI side, they could make it a little more intuitive in terms of how to add the radius components. Somebody who has been working with tools like Informatica or DataStage gets very used to how the UI looks and feels."
"The product integration with advanced coding options could cater to users needing more customization."
"In the next release, it's important that some sort of scheduler for running tasks is added."
"The stability of Azure as a PaaS could be improved."
"Customer support could be better. We often get replies that are delayed, and sometimes there is a lot of back and forth."
"Another improvement would be flexibility in handling edge cases. For standard transformations, it works well, but when business logic gets more complex, it can feel a bit limited without introducing workarounds."
 

Pricing and Cost Advice

"In terms of licensing costs, we pay somewhere around S14,000 USD per month. There are some additional costs. For example, we would have to subscribe to some additional computing and for elasticity, but they are minimal."
"I am aware of the pricing of Azure Data Factory, but I prefer not to disclose specific details."
"Data Factory is affordable."
"The licensing is a pay-as-you-go model, where you pay for what you consume."
"The licensing model for Azure Data Factory is good because you won't have to overpay. Pricing-wise, the solution is a five out of ten. It was not expensive, and it was not cheap."
"There's no licensing for Azure Data Factory, they have a consumption payment model. How often you are running the service and how long that service takes to run. The price can be approximately $500 to $1,000 per month but depends on the scaling."
"I rate the product price as six on a scale of one to ten, where one is low price and ten is high price."
"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."
Information not available
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Top Industries

By visitors reading reviews
Financial Services Firm
12%
Manufacturing Company
9%
Computer Software Company
9%
Construction Company
7%
Construction Company
14%
Financial Services Firm
10%
Outsourcing Company
10%
Comms Service Provider
8%
 

Company Size

By reviewers
Large Enterprise
Midsize Enterprise
Small Business
By reviewers
Company SizeCount
Small Business31
Midsize Enterprise21
Large Enterprise63
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...
What needs improvement with Integrate.io Platform?
I think Integrate.io Platform can be improved if there is a connector with all the cloud providers, mostly AWS or maybe GCP, to allow us to have this replication duplicated in our AWS infrastructur...
What is your primary use case for Integrate.io Platform?
My main use case for Integrate.io Platform is for database replications because it has a latency around 60 seconds. I use Integrate.io Platform mainly to integrate machine learning initiatives that...
What advice do you have for others considering Integrate.io Platform?
I would rate Integrate.io Platform a 10 out of 10. I chose this rating because I appreciate the latency and the fast replication that we have; our clients here want all the things fast, and they do...
 

Also Known As

No data available
DRIVEN APM, Xplenty
 

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
GAP, Samsung, REA Group, TellApart, Pintrest, Expedia, CapitalOne, Oportun, Hotels.com, HomeAway, CommonwealthBank, D&B, DeerWalk
Find out what your peers are saying about Azure Data Factory vs. Integrate.io Platform and other solutions. Updated: August 2026.
908,800 professionals have used our research since 2012.