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Azure Data Factory vs Talend Data Fabric comparison

 

Comparison Buyer's Guide

Executive Summary
 

Categories and Ranking

Azure Data Factory
Ranking in Data Integration
1st
Average Rating
8.0
Reviews Sentiment
6.7
Number of Reviews
86
Ranking in other categories
Cloud Data Warehouse (3rd)
Talend Data Fabric
Ranking in Data Integration
28th
Average Rating
8.6
Number of Reviews
5
Ranking in other categories
No ranking in other categories
 

Mindshare comparison

As of November 2024, in the Data Integration category, the mindshare of Azure Data Factory is 11.1%, down from 13.3% compared to the previous year. The mindshare of Talend Data Fabric is 1.5%, up from 1.5% compared to the previous year. It is calculated based on PeerSpot user engagement data.
Data Integration
 

Featured Reviews

Thulani David Mngadi - PeerSpot reviewer
Data flow feature is valuable for data transformation tasks
The workflow automation features in GitLab, particularly its low code/no code approach, are highly beneficial for accelerating development speed. This feature allows for quick creation of pipelines and offers customization options for integration needs, making it versatile for various use cases. GitLab supports a wide range of connectors, catering to a majority of integration needs. Azure Data Factory's virtual enterprise and monitoring capabilities, the visual interface of GitLab makes it user-friendly and easy to teach, facilitating adoption within teams. While the monitoring capabilities are sufficient out of the box, they may not be as comprehensive as dedicated enterprise monitoring tools. GitLab's monitoring features are manageable for production use, with the option to integrate log analytics or create custom dashboards if needed. The data flow feature in Azure Data Factory within GitLab is valuable for data transformation tasks, especially for those who may not have expertise in writing complex code. It simplifies the process of data manipulation and is particularly useful for individuals unfamiliar with Spark coding. While there could be improvements for more flexibility, overall, the data flow feature effectively accomplishes its purpose within GitLab's ecosystem.
KrishnaBaddam - PeerSpot reviewer
Supports API integrations and enables users to handle data management
Informatica is a well-established product known for its stability. Hardware and configuration can affect its performance, and it's not a lightweight tool that will fail quickly. When purchasing Informatica, you have options based on your needs. A simple data ingestion or integration license is relatively affordable, but the full Data Fabric suite is expensive. The Data Fabric suite includes integration, data quality, API management, big data processing, and real-time capabilities. For those who don't need the entire suite, purchasing individual components, such as data integration or data quality, it is a more cost-effective option. These individual licenses are generally less expensive than the complete Data Fabric suite, offering a more flexible and budget-friendly choice than Informatica's flagship.

Quotes from Members

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

Pros

"One advantage of Azure Data Factory is that it's fast, unlike SSIS and other on-premise tools. It's also very convenient because it has multiple connectors. The availability of native connectors allows you to connect to several resources to analyze data streams."
"Data Factory's most valuable feature is Copy Activity."
"The tool's most valuable features are its connectors. It has many out-of-the-box connectors. We use ADF for ETL processes. Our main use case involves integrating data from various databases, processing it, and loading it into the target database. ADF plays a crucial role in orchestrating these ETL workflows."
"The workflow automation features in GitLab, particularly its low code/no code approach, are highly beneficial for accelerating development speed. This feature allows for quick creation of pipelines and offers customization options for integration needs, making it versatile for various use cases. GitLab supports a wide range of connectors, catering to a majority of integration needs. Azure Data Factory's virtual enterprise and monitoring capabilities, the visual interface of GitLab makes it user-friendly and easy to teach, facilitating adoption within teams. While the monitoring capabilities are sufficient out of the box, they may not be as comprehensive as dedicated enterprise monitoring tools. GitLab's monitoring features are manageable for production use, with the option to integrate log analytics or create custom dashboards if needed. The data flow feature in Azure Data Factory within GitLab is valuable for data transformation tasks, especially for those who may not have expertise in writing complex code. It simplifies the process of data manipulation and is particularly useful for individuals unfamiliar with Spark coding. While there could be improvements for more flexibility, overall, the data flow feature effectively accomplishes its purpose within GitLab's ecosystem."
"Data Factory itself is great. It's pretty straightforward. You can easily add sources, join and lookup information, etc. The ease of use is pretty good."
"ADF is another ETL tool similar to Informatica that can transform data or copy it from on-prem to the cloud or vice versa. Once we have the data, we can apply various transformations to it and schedule our pipeline according to our business needs. ADF integrates with Databricks. We can call our Databricks notebooks and schedule them via ADF."
"We have been using drivers to connect to various data sets and consume data."
"Data Factory allows you to pull data from multiple systems, transform it according to your business needs, and load it into a data warehouse or data lake."
"Talend can be used for multi-cloud purposes, allowing users to orchestrate data across various cloud platforms without purchasing AWS Glue, Azure Data Factory, or similar cloud-specific tools."
"We've had no issues with the stability so far."
"The initial setup is very easy."
"The Talend data integration has been one of the most valuable features."
"It is a smart tool for us to design data pipelines. It lets us populate our three data lake instances. We like this solution for its connection capabilities, since it is very important to be able to use many different types of software. We tested a lot of SAP sources successfully, including cloud sources with SAP. It is also very easy to anonymize data with TIBCO, as well as populating HDFS files, packet files, and raw files. It is very easy to do that with Talend Data Fabric."
 

Cons

"Integration of data lineage would be a nice feature in terms of DevOps integration. It would make implementation for a company much easier. I'm not sure if that's already available or not. However, that would be a great feature to add if it isn't already there."
"Currently, our company requires a monitoring tool, and that isn't available in Azure Data Factory."
"The support and the documentation can be improved."
"We require Azure Data Factory to be able to connect to Google Analytics."
"When the record fails, it's tough to identify and log."
"The initial setup is not very straightforward."
"Data Factory's performance during heavy data processing isn't great."
"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."
"We encounter issues getting email notifications. They should provide enough information about the configuration process for email components."
"Deployment can be difficult, but I didn't test the latest version yet. With Talend products, every release brings a lot of new features and functionalities. This is never a small adaptation, because the tool is maturing, but we need to test the latest version and to check its deployment capabilities."
"I would like to see better integration with other tools."
"We are currently using version 7.3.1, but preferred the version before. The problem that we currently have is that Talend are releasing patches for Talend Studio every quarter. Our technical team has to be on top of these patches and constantly ensure everything is updated."
"Talend's architecture is complex to configure, especially due to the various components involved. It requires a more intricate setup."
 

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."
"The solution's pricing is competitive."
"The licensing cost is included in the Synapse."
"The cost is based on the amount of data sets that we are ingesting."
"Pricing appears to be reasonable in my opinion."
"I don't see a cost; it appears to be included in general support."
"The solution's fees are based on a pay-per-minute use plus the amount of data required to process."
"Data Factory is expensive."
"There are no additional licensing fees when you scale"
"There are multiple subscriptions available with Talend, each with its own scope. Subscriptions depend on the number of users you have and how many remote engines you want to install."
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Top Industries

By visitors reading reviews
Financial Services Firm
13%
Computer Software Company
12%
Manufacturing Company
9%
Healthcare Company
7%
Financial Services Firm
21%
Computer Software Company
15%
Educational Organization
7%
Government
7%
 

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...
What needs improvement with Talend Data Fabric?
Talend's architecture is complex to configure, especially due to the various components involved. It requires a more intricate setup. With Talend, multiple servers and components need to be properl...
What is your primary use case for Talend Data Fabric?
Talend Data Fabric is more than just a typical integration tool; it's a comprehensive suite of tools that includes Talend Data Integration. It supports API integrations, transferring data through A...
 

Learn More

 

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
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Find out what your peers are saying about Azure Data Factory vs. Talend Data Fabric and other solutions. Updated: October 2024.
816,406 professionals have used our research since 2012.