Azure Data Factory vs. Azure Stream Analytics

Overview
ProductRatingMost Used ByProduct SummaryStarting Price
Azure Data Factory
Score 9.0 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
Azure Stream Analytics
Score 8.0 out of 10
N/A
Microsoft offers Azure Stream Analytics for IoT and connected devices, supporting real-time analytics and reporting.
$0.11
per hour with a 1 SU minimum
Pricing
Azure Data FactoryAzure Stream Analytics
Editions & Modules
No answers on this topic
Standard
$0.11
per hour with a 1 SU minimum
Dedicated
$0.11
per hour with a 36 SU minimum
Offerings
Pricing Offerings
Azure Data FactoryAzure Stream Analytics
Free Trial
NoNo
Free/Freemium Version
NoNo
Premium Consulting/Integration Services
NoNo
Entry-level Setup FeeNo setup feeNo setup fee
Additional DetailsAzure Stream Analytics is priced by the number of Streaming Units provisioned. A Streaming Unit represents the amount of memory and compute allocated to your resources.
More Pricing Information
Community Pulse
Azure Data FactoryAzure Stream Analytics
Considered Both Products
Azure Data Factory
Chose Azure Data Factory
Azure Data Factory fits well into our overall systems architecture where we already utilize largely Azure services and also Microsoft based products in the on-premises environment. I think cost structure is also very competitive with Azure Data Factory. Most services provide a …
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 …
Chose Azure Data Factory
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.
Chose Azure Data Factory
I'd chose data factory because its very easy to use, its UI is beautiful, it's library for .net is very useful and it lives within the microsoft ecosystem.
Chose Azure Data Factory
Azure Data Factory is a relatively new player in the space, and its feature set marks it as such. It does not have the full features of a more mature product set such as any of the above. However, it does allow for the creation of ETL/ELT flows/pipelines with minimal initial …
Azure Stream Analytics
Chose Azure Stream Analytics
Azure Stream Analytics is easy to implement and also to integrate compare to other services like iot analytics
Features
Azure Data FactoryAzure Stream Analytics
Data Source Connection
Comparison of Data Source Connection features of Product A and Product B
Azure Data Factory
9.0
Ratings
7% above category average
Azure Stream Analytics
-
Ratings
Connect to traditional data sources9.00 Ratings00 Ratings
Connecto to Big Data and NoSQL9.00 Ratings00 Ratings
Data Transformations
Comparison of Data Transformations features of Product A and Product B
Azure Data Factory
8.5
Ratings
4% above category average
Azure Stream Analytics
-
Ratings
Simple transformations9.00 Ratings00 Ratings
Complex transformations8.00 Ratings00 Ratings
Data Modeling
Comparison of Data Modeling features of Product A and Product B
Azure Data Factory
7.2
Ratings
10% below category average
Azure Stream Analytics
-
Ratings
Data model creation8.00 Ratings00 Ratings
Metadata management7.00 Ratings00 Ratings
Business rules and workflow7.00 Ratings00 Ratings
Collaboration6.00 Ratings00 Ratings
Testing and debugging7.00 Ratings00 Ratings
Data Governance
Comparison of Data Governance features of Product A and Product B
Azure Data Factory
7.5
Ratings
8% below category average
Azure Stream Analytics
-
Ratings
Integration with data quality tools7.00 Ratings00 Ratings
Integration with MDM tools8.00 Ratings00 Ratings
Streaming Analytics
Comparison of Streaming Analytics features of Product A and Product B
Azure Data Factory
-
Ratings
Azure Stream Analytics
6.1
Ratings
27% below category average
Real-Time Data Analysis00 Ratings7.00 Ratings
Data Ingestion from Multiple Data Sources00 Ratings7.00 Ratings
Low Latency00 Ratings8.00 Ratings
Integrated Development Tools00 Ratings2.00 Ratings
Data wrangling and preparation00 Ratings7.00 Ratings
Linear Scale-Out00 Ratings5.00 Ratings
Data Enrichment00 Ratings7.00 Ratings
Best Alternatives
Azure Data FactoryAzure Stream Analytics
Small Businesses
Skyvia
Skyvia
Score 9.9 out of 10
IBM Streams (discontinued)
IBM Streams (discontinued)
Score 9.0 out of 10
Medium-sized Companies
IBM InfoSphere Information Server
IBM InfoSphere Information Server
Score 8.0 out of 10
Confluent
Confluent
Score 9.9 out of 10
Enterprises
IBM InfoSphere Information Server
IBM InfoSphere Information Server
Score 8.0 out of 10
Spotfire Streaming
Spotfire Streaming
Score 6.6 out of 10
All AlternativesView all alternativesView all alternatives
User Ratings
Azure Data FactoryAzure Stream Analytics
Likelihood to Recommend
9.0
(0 ratings)
7.0
(0 ratings)
Support Rating
7.0
(0 ratings)
-
(0 ratings)
User Testimonials
Azure Data FactoryAzure Stream Analytics
Likelihood to Recommend
In a data pipeline, you will be able to add different kinds of activities for example connect from your on-premise SFTP and move CSV files to storage accounts. As well data factory has its own data flow if you are an ETL developer who experimented with maybe you have worked with SSIS, thus, you will start quickly with this new feature of the data factory.
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Data enrichment is effectively done in stream analytics also checking the values with different functionality like windowing and group by clause is effectively working.
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Pros
  • Creating ETL and ELT workflows as well as orchestrating and monitoring pipelines without writing any code.
  • Hybrid data integration is easily and agilely possible through this software.
  • It has lot of various useful components
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  • Routing of data from multiple inputs to multiple output
  • You create your own user define function.
  • Intermediate query is working very effectively.
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Cons
  • Learning curve for pipeline creation interface.
  • Alerting isn't necessarily built in. Had to work around this to meet team needs.
  • With GIT enabled, some features can only be done via git, while some need to be done via the portal.
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  • Code competency is not that much effective
  • Ml models can't be integrated with stream analytics
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Usability
So far product has performed as expected. We were noticing some performance issues, but they were largely Synapse related. This has led to a shift from Synapse to Databricks. Overall this has delayed our analytic platform. Once databricks becomes fully operational, Azure Data Factory will be critical to our environment and future success.
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No answers on this topic
Support Rating
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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No answers on this topic
Alternatives Considered
Azure Data Factory fits well into our overall systems architecture where we already utilize largely Azure services and also Microsoft based products in the on-premises environment. I think cost structure is also very competitive with Azure Data Factory. Most services provide a visual interface for designing ETL workflows, but our team found Azure Data Factory's interface more intuitive.
Read full review
Azure Stream Analytics is easy to implement and also to integrate compare to other services like iot analytics
Read full review
Return on Investment
  • Limiting the amount of data moving up and down from the cloud for cloud-native applications.
  • Overall simple to use interface which is actually easier for a first time ETL developer than SSIS.
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  • Very nice roi while using it.
  • Multiple integration is the best functionality
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ScreenShots