Azure Data Factory vs. Talend Data Integration

Overview
ProductRatingMost Used ByProduct SummaryStarting Price
Azure Data Factory
Score 8.2 out of 10
N/A
Microsoft's Azure Data Factory is a service built for all data integration needs and skill levels. It is designed to allow the user to easily construct ETL and ELT processes code-free within the intuitive visual environment, or write one's own code. Visually integrate data sources using more than 80 natively built and maintenance-free connectors at no added cost. Focus on data—the serverless integration service does the rest.N/A
Talend Data Integration
Score 7.7 out of 10
N/A
The Talend Integration Suite, from Talend, is a set of tools for data integration.N/A
Pricing
Azure Data FactoryTalend Data Integration
Editions & Modules
No answers on this topic
No answers on this topic
Offerings
Pricing Offerings
Azure Data FactoryTalend Data Integration
Free Trial
NoNo
Free/Freemium Version
NoNo
Premium Consulting/Integration Services
NoNo
Entry-level Setup FeeNo setup feeNo setup fee
Additional Details
More Pricing Information
Community Pulse
Azure Data FactoryTalend Data Integration
Considered Both Products
Azure Data Factory
Chose Azure Data Factory
Azure Data Factory helps us automate to schedule jobs as per customer demands to make ETL triggers when the need arises. Anyone can define the workflow with the Azure Data Factory UI designer tool and easily test the systems. It helped us automate the same workflow with …
Talend Data Integration

No answer on this topic

Top Pros
Top Cons
Features
Azure Data FactoryTalend Data Integration
Data Source Connection
Comparison of Data Source Connection features of Product A and Product B
Azure Data Factory
9.1
7 Ratings
9% above category average
Talend Data Integration
8.2
9 Ratings
1% below category average
Connect to traditional data sources9.27 Ratings8.89 Ratings
Connecto to Big Data and NoSQL9.07 Ratings7.68 Ratings
Data Transformations
Comparison of Data Transformations features of Product A and Product B
Azure Data Factory
8.5
7 Ratings
3% above category average
Talend Data Integration
8.8
9 Ratings
7% above category average
Simple transformations9.27 Ratings8.89 Ratings
Complex transformations7.87 Ratings8.89 Ratings
Data Modeling
Comparison of Data Modeling features of Product A and Product B
Azure Data Factory
7.6
7 Ratings
6% below category average
Talend Data Integration
7.9
9 Ratings
2% below category average
Data model creation8.35 Ratings7.28 Ratings
Metadata management7.46 Ratings8.08 Ratings
Business rules and workflow7.47 Ratings8.87 Ratings
Collaboration6.86 Ratings5.58 Ratings
Testing and debugging7.47 Ratings8.89 Ratings
Data Governance
Comparison of Data Governance features of Product A and Product B
Azure Data Factory
7.7
7 Ratings
8% below category average
Talend Data Integration
7.8
8 Ratings
6% below category average
Integration with data quality tools7.37 Ratings7.68 Ratings
Integration with MDM tools8.07 Ratings8.08 Ratings
Best Alternatives
Azure Data FactoryTalend Data Integration
Small Businesses
Skyvia
Skyvia
Score 9.7 out of 10
Skyvia
Skyvia
Score 9.7 out of 10
Medium-sized Companies
IBM InfoSphere Information Server
IBM InfoSphere Information Server
Score 8.1 out of 10
IBM InfoSphere Information Server
IBM InfoSphere Information Server
Score 8.1 out of 10
Enterprises
IBM InfoSphere Information Server
IBM InfoSphere Information Server
Score 8.1 out of 10
IBM InfoSphere Information Server
IBM InfoSphere Information Server
Score 8.1 out of 10
All AlternativesView all alternativesView all alternatives
User Ratings
Azure Data FactoryTalend Data Integration
Likelihood to Recommend
9.3
(7 ratings)
8.3
(18 ratings)
Usability
-
(0 ratings)
9.0
(1 ratings)
Support Rating
7.0
(1 ratings)
6.6
(4 ratings)
User Testimonials
Azure Data FactoryTalend Data Integration
Likelihood to Recommend
Microsoft
Well-suited Scenarios for Azure Data Factory (ADF): When an organization has data sources spread across on-premises databases and cloud storage solutions, I think Azure Data Factory is excellent for integrating these sources. Azure Data Factory's integration with Azure Databricks allows it to handle large-scale data transformations effectively, leveraging the power of distributed processing. For regular ETL or ELT processes that need to run at specific intervals (daily, weekly, etc.), I think Azure Data Factory's scheduling capabilities are very handy. Less Appropriate Scenarios for Azure Data Factory: Real-time Data Streaming - Azure Data Factory is primarily batch-oriented. Simple Data Copy Tasks - For straightforward data copy tasks without the need for transformation or complex workflows, in my opinion, using Azure Data Factory might be overkill; simpler tools or scripts could suffice. Advanced Data Science Workflows: While Azure Data Factory can handle data prep and transformation, in my experience, it's not designed for in-depth data science tasks. I think for advanced analytics, machine learning, or statistical modeling, integration with specialized tools would be necessary.
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Qlik
The same way you design data integration job can be used to design services. It is easy to enhance by custom components and can adapt to all requirements. Talend Data Integration connects to [a] multitude of data sources and streaming service. Very easy interface to design complex applications without spending much time on coding. Easy to learn and master. Talend constantly strives to better itself by adding more features and functionalities.
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Pros
Microsoft
  • It allows copying data from various types of data sources like on-premise files, Azure Database, Excel, JSON, Azure Synapse, API, etc. to the desired destination.
  • We can use linked service in multiple pipeline/data load.
  • It also allows the running of SSIS & SSMS packages which makes it an easy-to-use ETL & ELT tool.
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Qlik
  • We used Talend to ETLing the data from myriad sources such Oracle Database, Clarify, Salesforce, Sugar CRM, SQL DB, MQ, Stibo Step, FTP, Netezza, and Files.
  • We leverage Talend transformation capabilities for stitching the data , unions and join
  • We successfully created the final unified set that can be used by business
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Cons
Microsoft
  • Limited source/sink (target) connectors depending on which area of Azure Data Factory you are using.
  • Does not yet have parity with SSIS as far as the transforms available.
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Qlik
  • Pricing for sure can be the area for improvement.
  • Real time processing is slow as compared to other tools like Abinitio.
  • While developing batches, it crashes a lot. It may be the issue with me, but I wanted to highlight it.
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Usability
Microsoft
No answers on this topic
Qlik
We use Talend Data Integration day in and day out. It is the best and easiest tool to jump on to and use. We can build a basic integration super-fast. We could build basic integrations as fast as within the hour. It is also easy to build transformations and use Java to perform some operations.
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Support Rating
Microsoft
We have not had need to engage with Microsoft much on Azure Data Factory, but they have been responsive and helpful when needed. This being said, we have not had a major emergency or outage requiring their intervention. The score of seven is a representation that they have done well for now, but have not proved out their support for a significant issue
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Qlik
Good support, specially when it relates to PROD environment. The support team has access to the product development team. Things are internally escalated to development team if there is a bug encountered. This helps the customer to get quick fix or patch designed for problem exceptions. I have also seen support showing their willingness to help develop custom connector for a newly available cloud based big data solution
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Alternatives Considered
Microsoft
The easy integration with other Microsoft software as well as high processing speed, very flexible cost, and high level of security of Microsoft Azure products and services stack up against other similar products.
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Qlik
In comparison with the other ETLs I used, Talend is more flexible than Data Services (where you cannot create complex commands). It is similar to Datastage speaking about commands and interfaces. It is more user-friendly than ODI, which has a metadata point of view on its own, while Talend is more classic. It has both on-prem and cloud approaches, while Matillion is only cloud-based.
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Return on Investment
Microsoft
  • It is very useful and make things easier
  • Debugging can improve
  • Its better suited than other products with the same objective
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Qlik
  • It’s only been a positive RoI with Talend given we’ve interfaced large datasets between critical on-Prem and cloud-native apps to efficiently run our business operations.
  • 40K+ plots data, covering 1K+ crop varieties.
  • 3K+ Customer & their credit data, 3K+ product inventory & pricing.
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