Azure Data Factory vs. SAS Data Management

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
SAS Data Management
Score 8.0 out of 10
N/A
A suite of solutions for data connectivity, enhanced transformations and robust governance. Solutions provide a unified view of data with access to data across databases, data warehouses and data lakes. Connects with cloud platforms, on-premises systems and multicloud data sources.N/A
Pricing
Azure Data FactorySAS Data Management
Editions & Modules
No answers on this topic
No answers on this topic
Offerings
Pricing Offerings
Azure Data FactorySAS Data Management
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 FactorySAS Data Management
Top Pros
Top Cons
Features
Azure Data FactorySAS Data Management
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
SAS Data Management
8.3
10 Ratings
0% below category average
Connect to traditional data sources9.17 Ratings8.610 Ratings
Connecto to Big Data and NoSQL9.07 Ratings8.19 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
SAS Data Management
6.7
8 Ratings
20% below category average
Simple transformations9.17 Ratings6.18 Ratings
Complex transformations7.97 Ratings7.48 Ratings
Data Modeling
Comparison of Data Modeling features of Product A and Product B
Azure Data Factory
7.5
7 Ratings
7% below category average
SAS Data Management
6.7
8 Ratings
18% below category average
Data model creation8.25 Ratings5.56 Ratings
Metadata management7.26 Ratings7.47 Ratings
Business rules and workflow7.27 Ratings6.67 Ratings
Collaboration6.56 Ratings7.07 Ratings
Testing and debugging7.27 Ratings6.17 Ratings
Data Governance
Comparison of Data Governance features of Product A and Product B
Azure Data Factory
7.6
7 Ratings
9% below category average
SAS Data Management
7.9
9 Ratings
5% below category average
Integration with data quality tools7.27 Ratings7.69 Ratings
Integration with MDM tools8.07 Ratings8.27 Ratings
Best Alternatives
Azure Data FactorySAS Data Management
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 FactorySAS Data Management
Likelihood to Recommend
9.2
(7 ratings)
7.6
(11 ratings)
Likelihood to Renew
-
(0 ratings)
9.0
(2 ratings)
Usability
-
(0 ratings)
6.0
(2 ratings)
Performance
-
(0 ratings)
9.0
(1 ratings)
Support Rating
7.0
(1 ratings)
7.7
(6 ratings)
User Testimonials
Azure Data FactorySAS Data Management
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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SAS
When data is in a system that needs a complex transformation to be usable for an average user. Such tasks as data residing in systems that have very different connection speeds. It can be integrated and used together after passing through the SAS Data Integration Studio removing timing issues from the users' worries. A part that is perhaps less appropriate is getting users who are not familiar with the source data to set up the load processes.
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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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SAS
  • SAS/Access is great for manipulating large and complex databases.
  • SAS/Access makes it easy to format reports and graphics from your data.
  • Data Management and data storage using the Hadoop environment in SAS/Access allows for rapid analysis and simple programming language for all your data needs.
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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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SAS
  • Requires third-party drivers to connect to common data sources like SFDC, MS SQL, Postgres.
  • Debugging errors from the logs is a complicated process.
  • E-mail alert system is very primitive and needs customization to make it more modern,
  • Cannot send SMS alerts for jobs.
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Likelihood to Renew
Microsoft
No answers on this topic
SAS
We are happy with the software and its functionality. As a SAS-shop, DataFlux is a logical choice for complex data integration.
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Usability
Microsoft
No answers on this topic
SAS
The main negative point is the use of a non-standard language for customizations, as well as the poor integration with non-SAS systems. However, there is no doubt that it is a high-performance and powerful product capable of responding optimally to certain requirements.
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Performance
Microsoft
No answers on this topic
SAS
It worked as expected.
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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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SAS
With SAS, you pay a license fee annually to use this product. Support is incredible. You get what you pay for, whether it's SAS forums on the SAS support site, technical support tickets via email or phone calls, or example documentation. It's not open source. It's documented thoroughly, and it works.
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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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SAS
Because of ease of using SAS DI and data processing speed. There were lots of issues with AWS Redshift on cloud environment in terms of making connections with the data sources and while fetching the data we need to write complex queries.
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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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SAS
  • We have more users who can connect to the many different data sources.
  • Our users do have existing SAS programming knowledge and that can carry over.
  • Business functions are starting to rely on SAS Data Integration Studio work product shortly after introduction.
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