Azure Data Factory vs. Azure Virtual Machines

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
Azure Virtual Machines
Score 7.9 out of 10
N/A
Virtual Machines (VMs) are available on Microsoft Azure, providing what is built as a low-cost, per-second compute service, available via Windows or Linux.
$0
Per Hour
Pricing
Azure Data FactoryAzure Virtual Machines
Editions & Modules
No answers on this topic
3 Year Reserved - Burstable VMs - B1S
$0.0038
Per Hour
Spot - General Purpose - Av2
$0.005
Per Hour
1 Year Reserved - Burstable VMs - B1S
$0.0059
Per Hour
Pay as You Go - Burstable VMs - B1S
$0.0075
Per Hour
Spot - Compute Optimized - Fsv2
$0.0104
Per Hour
Spot - General Purpose - Dv3
$0.0125
Per Hour
Spot - Memory Optimized - Ev3
$0.016
Per Hour
3 Year Reserved - Compute Optimized - Fsv2
$0.0307
Per Hour
3 Year Reserved - General Purpose - Dv3
$0.0369
Per Hour
3 Year Reserved - Memory Optimized - Ev3
$0.0481
Per Hour
1 Year Reserved - Compute Optimized - Fsv2
$0.05
Per Hour
1 Year Reserved - General Purpose - Dv3
$0.0548
Per Hour
1 Year Reserved - Memory Optimized - Ev3
$0.0753
Per Hour
Pay as You Go - Compute Optimized - Fsv2
$0.0846
Per Hour
Pay as You Go - General Purpose - Dv3
$0.096
Per Hour
Pay as You Go - Memory Optimized - Ev3
$0.126
Per Hour
Offerings
Pricing Offerings
Azure Data FactoryAzure Virtual Machines
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 FactoryAzure Virtual Machines
Considered Both Products
Azure Data Factory

No answer on this topic

Azure Virtual Machines
Chose Azure Virtual Machines
In comparison with AWS EC2, it is easier to deploy using the GUI, when it comes to using CLI is pretty much the same.
Features
Azure Data FactoryAzure Virtual Machines
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
Azure Virtual Machines
-
Ratings
Connect to traditional data sources9.010 Ratings00 Ratings
Connecto to Big Data and NoSQL8.010 Ratings00 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
Azure Virtual Machines
-
Ratings
Simple transformations8.710 Ratings00 Ratings
Complex transformations7.010 Ratings00 Ratings
Data Modeling
Comparison of Data Modeling features of Product A and Product B
Azure Data Factory
6.3
10 Ratings
22% below category average
Azure Virtual Machines
-
Ratings
Data model creation4.57 Ratings00 Ratings
Metadata management5.58 Ratings00 Ratings
Business rules and workflow6.010 Ratings00 Ratings
Collaboration7.09 Ratings00 Ratings
Testing and debugging6.310 Ratings00 Ratings
Data Governance
Comparison of Data Governance features of Product A and Product B
Azure Data Factory
5.7
10 Ratings
33% below category average
Azure Virtual Machines
-
Ratings
Integration with data quality tools4.310 Ratings00 Ratings
Integration with MDM tools7.09 Ratings00 Ratings
Server Virtualization
Comparison of Server Virtualization features of Product A and Product B
Azure Data Factory
-
Ratings
Azure Virtual Machines
7.2
24 Ratings
11% below category average
Virtual machine automated provisioning00 Ratings8.024 Ratings
Management console00 Ratings4.122 Ratings
Live virtual machine backup00 Ratings6.120 Ratings
Live virtual machine migration00 Ratings8.716 Ratings
Hypervisor-level security00 Ratings9.017 Ratings
Best Alternatives
Azure Data FactoryAzure Virtual Machines
Small Businesses
Skyvia
Skyvia
Score 10.0 out of 10
DigitalOcean Droplets
DigitalOcean Droplets
Score 9.5 out of 10
Medium-sized Companies
IBM InfoSphere Information Server
IBM InfoSphere Information Server
Score 8.0 out of 10
VMware vSOM (discontinued)
VMware vSOM (discontinued)
Score 10.0 out of 10
Enterprises
IBM InfoSphere Information Server
IBM InfoSphere Information Server
Score 8.0 out of 10
VMware vSOM (discontinued)
VMware vSOM (discontinued)
Score 10.0 out of 10
All AlternativesView all alternativesView all alternatives
User Ratings
Azure Data FactoryAzure Virtual Machines
Likelihood to Recommend
9.0
(7 ratings)
9.6
(24 ratings)
Usability
8.0
(1 ratings)
9.0
(1 ratings)
Support Rating
7.0
(1 ratings)
7.0
(1 ratings)
User Testimonials
Azure Data FactoryAzure Virtual Machines
Likelihood to Recommend
Microsoft
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.
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Microsoft
If you want to host a dedicated Windows server on the cloud, and especially if you want to integrate it with your on premises Active Directory, Azure Virtual Machines should be your first choice. Obviously running Linux on Azure works very well too, but given Azure's pricing is not the cheapest, there are other providers out there that have a better cost-benefit ratio for Linux. That said, hosting Windows on Azure can be affordable (especially when compared to other providers) if you plan your licensing, topology, and application architecture correctly.
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Pros
Microsoft
  • Data Ingestion - it works very well with numerous data sources.
  • Data pipeline orchestration: It is a generic, popular tool for orchestrating data pipelines.
  • Works well in Azure ecosystem, Azure services and data platforms like Databricks.
  • It is a serverless and scalable solution for cloud data integration.
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Microsoft
  • When demand is high, we scale the service out, eg During a Football Match.
  • When a football match is over and the throughput of data from OPTA drops we save by the service scaling back in.
  • Our App Service Plans along with the Clean C# code are lightening fast giving a good customer experience.
  • When producing the TV Guide information and a program overruns its scheduled time, a client can instantly be updated to the new programming schedule as our change is instant and its in the right place for all the clients to download and adjust their television guides appropriately to send out to the public giving a 24x7 uptime service that is precise and accurate and resilient to outages due to failover zones around the world.
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Cons
Microsoft
  • 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
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Microsoft
  • Pricing can be a concern if you are truly agnostic to which cloud you are building your particular solution in.
  • The UI, as is the case with any cloud provider, is crowded.
  • As with any cloud provider, it can be difficult to tune in exactly the right amount of servers for your needs...you might find yourself under/overprovisioning.
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Usability
Microsoft
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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Microsoft
No VM console, weak management interface, changing CPU/memory is not straightforward. On the positive side, basic RDP functionality is good to have. As long as things are working, the ability to host Windows VMs is appreciated.
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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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Microsoft
I give the overall support for Azure Virtual Machines a 7 because I think while the overall support do a great job there are still areas that it could improve on such as efficiency and speed. So while I only give it a 7 and it has some issues it is still better than the overall support at Amazon EC2 Auto Scaling.
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Alternatives Considered
Microsoft
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.
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Microsoft
Azure Virtual Machines offer unparalleled flexibility in provisioning, managing and upgrading the VM instances, both manually and programmatically. AVM offer very granular billing options and enables high costs optimisations (while still being costly). The other competitors I mentioned are very good at offering dead-cheap VMs. But if you need anything beyond that, especially for big computing, you need Azure Virtual Machines.
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Return on Investment
Microsoft
  • Facilitate better decision-making and improve business processes.
  • Optimize business process outcomes by increasing internal efficiency and operational effectiveness.
  • Boosts revenue growth while improving business process agility.
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Microsoft
  • It's so easy to spin up new instances, that it becomes also to easy to have to many of them to manage. Many teams end up with a couple of hundreds of VMs after a short while, making the whole thing very hard to maneuver
  • Azure VMs are the next step for us to rely on Onprem servers, and leaving the management of the infrastructure to the professionals
  • The ease of use, is also important when our main focus is to deliver new applications and integrations fast, and not having to worry about infrastructure. We sell bottles, not CPUs
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ScreenShots