Azure Data Factory vs. Snowflake

Overview
ProductRatingMost Used ByProduct SummaryStarting Price
Azure Data Factory
Score 8.1 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
Snowflake
Score 8.7 out of 10
N/A
The Snowflake Cloud Data Platform is the eponymous data warehouse with, from the company in San Mateo, a cloud and SQL based DW that aims to allow users to unify, integrate, analyze, and share previously siloed data in secure, governed, and compliant ways. With it, users can securely access the Data Cloud to share live data with customers and business partners, and connect with other organizations doing business as data consumers, data providers, and data service providers.N/A
Pricing
Azure Data FactorySnowflake
Editions & Modules
No answers on this topic
No answers on this topic
Offerings
Pricing Offerings
Azure Data FactorySnowflake
Free Trial
NoYes
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 FactorySnowflake
Features
Azure Data FactorySnowflake
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
Snowflake
-
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
Snowflake
-
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
21% below category average
Snowflake
-
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
Snowflake
-
Ratings
Integration with data quality tools4.310 Ratings00 Ratings
Integration with MDM tools7.09 Ratings00 Ratings
Best Alternatives
Azure Data FactorySnowflake
Small Businesses
Skyvia
Skyvia
Score 10.0 out of 10
Google BigQuery
Google BigQuery
Score 8.8 out of 10
Medium-sized Companies
IBM InfoSphere Information Server
IBM InfoSphere Information Server
Score 8.0 out of 10
Google BigQuery
Google BigQuery
Score 8.8 out of 10
Enterprises
IBM InfoSphere Information Server
IBM InfoSphere Information Server
Score 8.0 out of 10
Google BigQuery
Google BigQuery
Score 8.8 out of 10
All AlternativesView all alternativesView all alternatives
User Ratings
Azure Data FactorySnowflake
Likelihood to Recommend
9.0
(7 ratings)
9.0
(43 ratings)
Likelihood to Renew
-
(0 ratings)
10.0
(2 ratings)
Usability
8.0
(1 ratings)
9.3
(19 ratings)
Support Rating
7.0
(1 ratings)
9.9
(8 ratings)
Contract Terms and Pricing Model
-
(0 ratings)
8.0
(1 ratings)
User Testimonials
Azure Data FactorySnowflake
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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Snowflake Computing
Snowflake is well suited when you have to store your data and you want easy scalability and increase or decrease the storage per your requirement. You can also control the computing cost, and if your computing cost is less than or equal to 10% of your storage cost, then you don't have to pay for computing, which makes it cost-effective as well.
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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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Snowflake Computing
  • Snowflake scales appropriately allowing you to manage expense for peak and off peak times for pulling and data retrieval and data centric processing jobs
  • Snowflake offers a marketplace solution that allows you to sell and subscribe to different data sources
  • Snowflake manages concurrency better in our trials than other premium competitors
  • Snowflake has little to no setup and ramp up time
  • Snowflake offers online training for various employee types
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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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Snowflake Computing
  • Add constraints for views and not just for tables
  • Do not force customers to renew for same or higher amount to avoid loosing unused credits. Already paid credits should not expire (at least within a reasonable time frame), independent of renewal deal size.
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Likelihood to Renew
Microsoft
No answers on this topic
Snowflake Computing
SnowFlake is very cost effective and we also like the fact we can stop, start and spin up additional processing engines as we need to. We also like the fact that it's easy to connect our SQL IDEs to Snowflake and write our queries in the environment that we are used to
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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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Snowflake Computing
Because the fact that you can query tons of data in a few seconds is incredible, it also gives you a lot of functions to format and transform data right in your query, which is ideal when building data models in BI tools like Power BI, it is available as a connector in the most used BI tools worldwide.
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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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Snowflake Computing
We have had terrific experiences with Snowflake support. They have drilled into queries and given us tremendous detail and helpful answers. In one case they even figured out how a particular product was interacting with Snowflake, via its queries, and gave us detail to go back to that product's vendor because the Snowflake support team identified a fault in its operation. We got it solved without lots of back-and-forth or finger-pointing because the Snowflake team gave such detailed information.
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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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Snowflake Computing
I have had the experience of using one more database management system at my previous workplace. What Snowflake provides is better user-friendly consoles, suggestions while writing a query, ease of access to connect to various BI platforms to analyze, [and a] more robust system to store a large amount of data. All these functionalities give the better edge to Snowflake.
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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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Snowflake Computing
  • With separate compute and storage feature, the queries get executed quickly and it improves our overall productivity.
  • Earlier we were using a different product for analytical purposes, but with Snowflake's in-built analytical feature we are now able to save money.
  • Snowflake is cost efficient, features like auto suspend for compute resources helped to control the costs.
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ScreenShots

Snowflake Screenshots

Screenshot of Snowflake Installation