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Azure Data Factory vs IBM App Connect 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:
 

ROI

Sentiment score
6.4
Azure Data Factory offers significant ROI, efficiency, and cost savings, with users highlighting benefits in data integration and migration.
Sentiment score
7.3
IBM App Connect enhances ROI by reducing resource needs and managing complex operations, requiring skilled practitioners for optimal results.
Our stakeholders and clients have expressed satisfaction with Azure Data Factory's efficiency and cost-effectiveness.
Data Engineer at Vthinktechnologies
IBM App Connect definitely saves significant time, approximately 50 to 60%.
Software Engineer at a tech vendor with 1,001-5,000 employees
 

Customer Service

Sentiment score
6.3
Azure Data Factory support is generally satisfactory, with responsive assistance and strong community resources enhancing user satisfaction.
Sentiment score
6.7
IBM App Connect's 24/7 support offers timely help, though complex issues need escalation and response times could improve.
The technical support from Microsoft is rated an eight out of ten.
Chief Analytics Officer at Idiro Analytics
The technical support is responsive and helpful
Sr. Technical Architect at Hexaware Technologies Limited
The technical support for Azure Data Factory is generally acceptable.
Solution Architect at Mercedes-Benz AG
When opening a ticket with the global team, problems are resolved promptly and effectively.
Team Leader, Software Development at a manufacturing company with 11-50 employees
The customer support is available 24/7.
Software Engineer at a tech vendor with 1,001-5,000 employees
The technical support from IBM is good.
Developer at a tech vendor with 10,001+ employees
 

Scalability Issues

Sentiment score
7.4
Azure Data Factory offers scalable cloud-based solutions for diverse operations, despite some third-party integration limitations and use case challenges.
Sentiment score
7.5
IBM App Connect excels in cloud scalability, notably in Kubernetes, though costs and larger payloads can challenge Hypervisor Edition.
Azure Data Factory is highly scalable.
Chief Analytics Officer at Idiro Analytics
IBM App Connect demonstrates good scalability.
Team Leader, Software Development at a manufacturing company with 11-50 employees
I would rate the scalability of IBM App Connect as nine out of ten.
Developer at a tech vendor with 10,001+ employees
IBM App Connect is very scalable and a flexible tool.
Software Engineer at a tech vendor with 1,001-5,000 employees
 

Stability Issues

Sentiment score
7.8
Azure Data Factory is considered highly stable and reliable, though minor issues can occur, mostly in development environments.
Sentiment score
7.6
IBM App Connect is praised for stability, with issues mostly in complex cases and quick responses to reported problems.
The solution has a high level of stability, roughly a nine out of ten.
Chief Analytics Officer at Idiro Analytics
Some companies require multiple configurations, including ODBC connections, JDBC connections, different BI databases, main databases, and replication servers.
Team Leader, Software Development at a manufacturing company with 11-50 employees
 

Room For Improvement

Azure Data Factory needs better integration, UI, documentation, data handling, pricing transparency, real-time processing, connectivity, and scheduling.
IBM App Connect needs improvements in logging, interface, integrations, setup, cost, security, debugging, observability, and reliability.
Incorporating more dedicated API sources to specific services like HubSpot CRM or Salesforce would be beneficial.
Chief Analytics Officer at Idiro Analytics
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
There is a problem with the integration with third-party solutions, particularly with SAP.
Solution Architect at Mercedes-Benz AG
Version 13 includes around 200 features with cloud platform compatibility.
Team Leader, Software Development at a manufacturing company with 11-50 employees
I find it particularly good for on-premises and now cloud use.
Developer at a tech vendor with 10,001+ employees
Better debugging and observability would help us track any single transaction end-to-end across steps and connectors.
Software Engineer at a tech vendor with 1,001-5,000 employees
 

Setup Cost

Azure Data Factory's pricing is pay-as-you-go, with costs based on usage, offering competitive and cost-effective solutions.
IBM App Connect is costly but valued by enterprises for quality; licensing complexities require expertise and allow for discounts.
The pricing is cost-effective.
Chief Analytics Officer at Idiro Analytics
It is considered cost-effective.
Sr. Technical Architect at Hexaware Technologies Limited
For insurance companies with simple JDBC connections, the process is straightforward.
Team Leader, Software Development at a manufacturing company with 11-50 employees
 

Valuable Features

Azure Data Factory offers scalable ETL processes with easy integration, user-friendly interface, and strong orchestration, security, and automation features.
IBM App Connect offers easy integration with minimal coding, pre-built adapters, security, scalability, rapid deployment, and flexible integration.
It connects to different sources out-of-the-box, making integration much easier.
Sr. Technical Architect at Hexaware Technologies Limited
The platform excels in handling major datasets, particularly when working with Power BI for reporting purposes.
Data Engineer at Vthinktechnologies
Regarding the integration feature in Azure Data Factory, the integration part is excellent; we have major source connectors, so we can integrate the data from different data sources and also perform basic transformation while transforming, which is a great feature in Azure Data Factory.
Director at a computer software company with 1,001-5,000 employees
Overall, 50 to 60% of the time is saved when using IBM App Connect.
Software Engineer at a tech vendor with 1,001-5,000 employees
The transformation capabilities in IBM App Connect are particularly beneficial.
Team Leader, Software Development at a manufacturing company with 11-50 employees
The features I find most valuable are message routing, message transformation, and protocol translation.
Developer at a tech vendor with 10,001+ employees
 

Categories and Ranking

Azure Data Factory
Average Rating
8.0
Reviews Sentiment
6.8
Number of Reviews
93
Ranking in other categories
Data Integration (3rd), Cloud Data Warehouse (2nd)
IBM App Connect
Average Rating
8.2
Reviews Sentiment
6.8
Number of Reviews
26
Ranking in other categories
Cloud Data Integration (12th)
 

Mindshare comparison

While both are Data Integration and Access solutions, they serve different purposes. Azure Data Factory is designed for Data Integration and holds a mindshare of 3.0%, down 9.8% compared to last year.
IBM App Connect, on the other hand, focuses on Cloud Data Integration, holds 3.0% mindshare, down 3.8% since last year.
Data Integration Market Share Distribution
ProductMarket Share (%)
Azure Data Factory3.0%
SSIS3.7%
Informatica Intelligent Data Management Cloud (IDMC)3.5%
Other89.8%
Data Integration
Cloud Data Integration Market Share Distribution
ProductMarket Share (%)
IBM App Connect3.0%
AWS Glue9.2%
AWS Database Migration Service7.4%
Other80.4%
Cloud 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.
Emirhan Guven - PeerSpot reviewer
Team Leader, Software Development at a manufacturing company with 11-50 employees
Transforms data efficiently and navigates licensing challenges with ease
The transition between version 12 and version 13 presents some challenges. While version 12 had approximately 10 features, version 13 includes around 200 features with cloud platform compatibility. The learning curve for developers moving from version 12 to 13 could be smoother. When using new components, better context explanations would be beneficial. In version 13, accessing new features requires connecting through a web browser, which can be challenging to understand. The explanation of new features could be more user-friendly.
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881,733 professionals have used our research since 2012.
 

Top Industries

By visitors reading reviews
Financial Services Firm
13%
Computer Software Company
11%
Manufacturing Company
9%
Government
6%
Manufacturing Company
15%
Financial Services Firm
15%
Computer Software Company
11%
Retailer
7%
 

Company Size

By reviewers
Large Enterprise
Midsize Enterprise
Small Business
By reviewers
Company SizeCount
Small Business31
Midsize Enterprise19
Large Enterprise57
By reviewers
Company SizeCount
Small Business4
Midsize Enterprise4
Large Enterprise21
 

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 IBM App Connect?
I like the adapters. The adapters help us achieve scalability. If you want to connect to SAP, there's an adapter. Salesforce? There's an adapter. You want to connect to another system? There's like...
What is your experience regarding pricing and costs for IBM App Connect?
Configuration time varies by implementation. For insurance companies with simple JDBC connections, the process is straightforward. However, companies requiring multiple configurations for ODBC, JDB...
What is your primary use case for IBM App Connect?
I am a developer specializing in IBM App Connect. We have a customer interested in comparing ESB tools, such as webMethods, which was previously owned by Software AG company before IBM acquired the...
 

Also Known As

No data available
IBM Cast Iron
 

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
United Way of Allegheny County, Saint-Gobain CPS, Ricoh, SunTrust Banks Inc.
Find out what your peers are saying about Azure Data Factory vs. IBM App Connect and other solutions. Updated: May 2023.
881,733 professionals have used our research since 2012.