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.
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Microsoft SQL Server
Score 8.7 out of 10
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Microsoft SQL Server is a relational database.
$1,418
Per License
Pricing
Azure Data Factory
Microsoft SQL Server
Editions & Modules
No answers on this topic
Subscription
$1,418.00
Per License
Enterprise
$13,748.00
Per License
Offerings
Pricing Offerings
Azure Data Factory
Microsoft SQL Server
Free Trial
No
No
Free/Freemium Version
No
No
Premium Consulting/Integration Services
No
No
Entry-level Setup Fee
No setup fee
No setup fee
Additional Details
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More Pricing Information
Community Pulse
Azure Data Factory
Microsoft SQL Server
Features
Azure Data Factory
Microsoft SQL Server
Data Source Connection
Comparison of Data Source Connection features of Product A and Product B
Azure Data Factory
8.5
10 Ratings
3% above category average
Microsoft SQL Server
-
Ratings
Connect to traditional data sources
9.010 Ratings
00 Ratings
Connecto to Big Data and NoSQL
8.010 Ratings
00 Ratings
Data Transformations
Comparison of Data Transformations features of Product A and Product B
Azure Data Factory
7.8
10 Ratings
3% below category average
Microsoft SQL Server
-
Ratings
Simple transformations
8.710 Ratings
00 Ratings
Complex transformations
7.010 Ratings
00 Ratings
Data Modeling
Comparison of Data Modeling features of Product A and Product B
Azure Data Factory
6.3
10 Ratings
21% below category average
Microsoft SQL Server
-
Ratings
Data model creation
4.57 Ratings
00 Ratings
Metadata management
5.58 Ratings
00 Ratings
Business rules and workflow
6.010 Ratings
00 Ratings
Collaboration
7.09 Ratings
00 Ratings
Testing and debugging
6.310 Ratings
00 Ratings
Data Governance
Comparison of Data Governance features of Product A and Product B
Best scenario is for ETL process. The flexibility and connectivity is outstanding. For our environment, SAP data connectivity with Azure Data Factory offers very limited features compared to SAP Data Sphere. Due to the limited modelling capacity of the tool, we use Databricks for data modelling and cleaning. Usage of multiple tools could have been avoided if adf has modelling capabilities.
Microsoft SQL is ubiquitous, while MySQL runs under the hood all over the place. Microsoft SQL is the platform taught in colleges and certification courses and is the one most likely to be used by businesses because it is backed by Microsoft. Its interface is friendly (well, as pleasant as SQL can be) and has been used by so many for so long that resources are freely available if you encounter any issues.
Granularity of Errors: Sometimes, Azure Data Factory provides error messages that are too generic or vague for us, making it challenging to pinpoint the exact cause of a pipeline failure. Enhanced error messages with more actionable details would greatly assist us as users in debugging their pipelines.
Pipeline Design UI: In my experience, the visual interface for designing pipelines, especially when dealing with complex workflows or numerous activities, can become cluttered. I think a more intuitive and scalable design interface would improve usability. In my opinion, features like zoom, better alignment tools, or grouping capabilities could make managing intricate designs more manageable.
Native Support: While Azure Data Factory does support incremental data loads, in my experience, the setup can be somewhat manual and complex. I think native and more straightforward support for Change Data Capture, especially from popular databases, would simplify the process of capturing and processing only the changed data, making regular data updates more efficient
Microsoft SQL Server Enterprise edition has a high cost but is the only edition which supports SQL Always On Availability Groups. It would be nice to include this feature in the Standard version.
Licensing of Microsoft SQL Server is a quite complex matter, it would be good to simplify licensing in the future. For example, per core vs per user CAL licensing, as well as complex licensing scenarios in the Cloud and on Edge locations.
It would be good to include native tools for converting Oracle, DB2, Postgresql and MySQL/MariaDB databases (schema and data) for import into Microsoft SQL Server.
We understand that the Microsoft SQL Server will continue to advance, offering the same robust and reliable platform while adding new features that enable us, as a software center, to create a superior product. That provides excellent performance while reducing the hardware requirements and the total cost of ownership of our solution.
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.
SQL Server mostly 'just works' or generates error messages to help you sort out the trouble. You can usually count on the product to get the job done and keep an eye on your potential mistakes. Interaction with other Microsoft products makes operating as a Windows user pretty straight forward. Digging through the multitude of dialogs and wizards can be a pain, but the answer is usually there somewhere.
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
We managed to handle most of our problems by looking into Microsoft's official documentation that has everything explained and almost every function has an example that illustrates in detail how a particular functionality works. Just like PowerShell has the ability to show you an example of how some cmdlet works, that is the case also here, and in my opinion, it is a very good practice and I like it.
Other than SQL taking quite a bit of time to actually install there are no problems with installation. Even on hardware that has good performance SQL can still take close to an hour to install a typical server with management and reporting services.
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 programming languages like Python or automation tools like ansible. Numerous options for connectivity be it a database or storage account helps us move data transfer to the cloud or on-premise systems.
[Microsoft] SQL Server has a much better community and professional support and is overall just a more reliable system with Microsoft behind it. I've used MySQL in the past and SQL Server has just become more comfortable for me and is my go to RDBMS.
Increased accuracy - We went from multiple users having different versions of an Excel spreadsheet to a single source of truth for our reporting.
Increased Efficiency - We can now generate reports at any time from a single source rather than multiple users spending their time collating data and generating reports.
Improved Security - Enterprise level security on a dedicated server rather than financial files on multiple laptop hard drives.