AWS Data Pipeline vs. Azure Data Factory

Overview
ProductRatingMost Used ByProduct SummaryStarting Price
AWS Data Pipeline
Score 9.5 out of 10
N/A
AWS Data Pipeline is a web service used to process and move data between different AWS compute and storage services, as well as on-premises data sources, at specified intervals. With AWS Data Pipeline, users can regularly access data where it’s stored, transform and process it at scale, and transfer the results to AWS services such as Amazon S3, Amazon RDS, Amazon DynamoDB, and Amazon EMR. AWS Data Pipeline is designed to help create complex data processing workloads that are fault tolerant,…N/A
Azure Data Factory
Score 8.3 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
Pricing
AWS Data PipelineAzure Data Factory
Editions & Modules
No answers on this topic
No answers on this topic
Offerings
Pricing Offerings
AWS Data PipelineAzure Data Factory
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
AWS Data PipelineAzure Data Factory
Considered Both Products
AWS Data Pipeline
Azure Data Factory

No answer on this topic

Top Pros
Top Cons
Features
AWS Data PipelineAzure Data Factory
Data Source Connection
Comparison of Data Source Connection features of Product A and Product B
AWS Data Pipeline
-
Ratings
Azure Data Factory
9.1
7 Ratings
10% above category average
Connect to traditional data sources00 Ratings9.27 Ratings
Connecto to Big Data and NoSQL00 Ratings9.07 Ratings
Data Transformations
Comparison of Data Transformations features of Product A and Product B
AWS Data Pipeline
-
Ratings
Azure Data Factory
8.5
7 Ratings
2% above category average
Simple transformations00 Ratings9.27 Ratings
Complex transformations00 Ratings7.77 Ratings
Data Modeling
Comparison of Data Modeling features of Product A and Product B
AWS Data Pipeline
-
Ratings
Azure Data Factory
7.7
7 Ratings
6% below category average
Data model creation00 Ratings8.45 Ratings
Metadata management00 Ratings7.56 Ratings
Business rules and workflow00 Ratings7.57 Ratings
Collaboration00 Ratings7.16 Ratings
Testing and debugging00 Ratings7.57 Ratings
Data Governance
Comparison of Data Governance features of Product A and Product B
AWS Data Pipeline
-
Ratings
Azure Data Factory
7.7
7 Ratings
6% below category average
Integration with data quality tools00 Ratings7.47 Ratings
Integration with MDM tools00 Ratings8.07 Ratings
Best Alternatives
AWS Data PipelineAzure Data Factory
Small Businesses
Skyvia
Skyvia
Score 9.6 out of 10
Skyvia
Skyvia
Score 9.6 out of 10
Medium-sized Companies
Astera Centerprise
Astera Centerprise
Score 8.8 out of 10
IBM InfoSphere Information Server
IBM InfoSphere Information Server
Score 8.2 out of 10
Enterprises
Astera Centerprise
Astera Centerprise
Score 8.8 out of 10
IBM InfoSphere Information Server
IBM InfoSphere Information Server
Score 8.2 out of 10
All AlternativesView all alternativesView all alternatives
User Ratings
AWS Data PipelineAzure Data Factory
Likelihood to Recommend
10.0
(1 ratings)
9.3
(7 ratings)
Support Rating
-
(0 ratings)
7.0
(1 ratings)
User Testimonials
AWS Data PipelineAzure Data Factory
Likelihood to Recommend
Amazon AWS
AWS Data Pipeline is a web service that helps you reliably process and move data between different AWS compute and storage services, as well as on-premises data sources, at specified intervals. With AWS Data Pipeline, you can regularly access your data where it’s stored, transform and process it at scale, and efficiently transfer the results to AWS services such as Amazon S3, Amazon RDS, Amazon DynamoDB, and Amazon EMR.
Read full review
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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Pros
Amazon AWS
  • Helps you easily create complex data processing workloads
  • Fault tolerant
  • Highly available
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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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Cons
Amazon AWS
  • Pipeline Stuck in Pending Status
  • Pipeline Component Stuck in Waiting for Runner Status
  • EMR Cluster Fails With Error
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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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Support Rating
Amazon AWS
No answers on this topic
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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Alternatives Considered
Amazon AWS
AWS data pipelines are easy to use over data factory for data engineers
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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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Return on Investment
Amazon AWS
  • Easy to use
  • Data engineers are able to create the data pipelines quickly and effectively
  • Scalable and Fault tolerant
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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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ScreenShots