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Azure Data Factory vs Snowflake Analytics comparison

 

Comparison Buyer's Guide

Executive SummaryUpdated on Dec 18, 2024

Review summaries and opinions

We asked business professionals to review the solutions they use. Here are some excerpts of what they said:
 

ROI

Sentiment score
5.5
Users praise Azure Data Factory for improved ROI through cost savings, enhanced integration, and increased operational efficiency and satisfaction.
Sentiment score
5.6
Users experience mixed ROI with Snowflake; it often improves operational efficiency, time savings, and cost control.
Our stakeholders and clients have expressed satisfaction with Azure Data Factory's efficiency and cost-effectiveness.
Data Engineer at Vthinktechnologies
Snowflake Analytics has positively impacted our organization by saving about eight to ten hours per week, which we can use for advanced analytics and automation tasks.
Data engineer at a tech vendor with 10,001+ employees
 

Customer Service

Sentiment score
6.3
Azure Data Factory support is mixed; praised for responsiveness and documentation, but some find it slow and inadequate.
Sentiment score
6.9
Snowflake Analytics support is often responsive and competent, but accessibility issues exist for non-major partners, despite strong community resources.
On a scale of one to ten, I would rate the technical support as nine.
Senior Consultant Oracle Technologies at a tech vendor with 10,001+ employees
The technical support from Microsoft is rated an eight out of ten.
Chief Analytics Officer at Idiro Analytics
The technical support is responsive and helpful
Sr. Technical Architect at Hexaware Technologies Limited
The Snowflake Analytics documentation is excellent.
Lead Analytics Consultant at a outsourcing company with 51-200 employees
Recently we had a two-day session where the Snowflake Analytics team provided a demo on Cortex AI and its features.
Associate Principal Engineer at Nagarro
The technical support for Snowflake Analytics is excellent based on what I have heard from others.
Data Governance Architect at Sterlite Technologies Ltd
 

Scalability Issues

Sentiment score
7.4
Azure Data Factory is praised for its scalability and flexibility, despite some integration issues in older tiers.
Sentiment score
7.7
Snowflake Analytics offers exceptional scalability through auto-scaling, cloud integration, and efficient resource management, ideal for handling large data volumes.
Azure Data Factory is highly scalable.
Chief Analytics Officer at Idiro Analytics
I did not experience scalability issues.
Principal Data Engineer at Oracle
Storage is unlimited because they use S3 if it is AWS, so storage has no limit.
Senior Software Architect at USEReady
It supports both horizontal and vertical scaling effectively.
Data Governance Architect at Sterlite Technologies Ltd
Maintaining security and data governance becomes easier with an entire data lake in place, and the scalability improves performance.
Associate Principal Engineer at Nagarro
 

Stability Issues

Sentiment score
7.7
Azure Data Factory is stable and dependable, despite occasional connection issues and challenges with SQL query optimization.
Sentiment score
8.4
Snowflake Analytics is highly stable, supported by major cloud providers, with strong performance and minimal technical issues reported.
The solution has a high level of stability, roughly a nine out of ten.
Chief Analytics Officer at Idiro Analytics
I have been using Azure Data Factory for a very long time, and I did not find too many issues.
Principal Data Engineer at Oracle
Snowflake Analytics has been stable and reliable in my experience.
Associate Principal Engineer at Nagarro
Snowflake Analytics is very stable; I have never experienced any crash downs or server issues.
Data engineer at a tech vendor with 10,001+ employees
Snowflake Analytics is stable, scoring around eight point five to nine out of ten.
Data Governance Architect at Sterlite Technologies Ltd
 

Room For Improvement

Azure Data Factory users experience setup complexity, connectivity issues, and seek improved performance, automation, and integration with other platforms.
Snowflake Analytics struggles with data migration, integration, performance, cost issues, and needs better UI, job scheduling, and AWS support.
The ability to handle the largest volumes of data is another concern; if I have to manage more than one terabyte of data every day, I am not comfortable dealing with Azure Data Factory and had to switch to Oracle Data Integrators (ODI) because it lacks performance features.
Senior Consultant Oracle Technologies at a tech vendor with 10,001+ employees
Incorporating more dedicated API sources to specific services like HubSpot CRM or Salesforce would be beneficial.
Chief Analytics Officer at Idiro Analytics
Sometimes, the compute fails to process data if there is a heavy load suddenly, and it doesn't scale up automatically.
Sr. Technical Architect at Hexaware Technologies Limited
AIML-based SQL prompt and query generation could be an area for enhancement.
Senior Software Architect at USEReady
If it offered flexibility similar to Oracle and supported more heterogeneous data sources and database connectivity, it would be even better.
Data Governance Architect at Sterlite Technologies Ltd
I would prefer Snowflake Analytics to improve their support response times, as sometimes the responses we receive are not very prompt and ticket assignments may not be timely.
Associate Principal Engineer at Nagarro
 

Setup Cost

Azure Data Factory provides cost-effective, usage-based pricing suitable for various budgets, with expenses depending on data volume and services.
Snowflake Analytics uses a pay-as-you-go model, emphasizing strategic design to manage costs, often seen as competitively priced.
The pricing is cost-effective.
Chief Analytics Officer at Idiro Analytics
It is considered cost-effective.
Sr. Technical Architect at Hexaware Technologies Limited
Snowflake charges per query, which amounts to a very minor cost, such as $0.015 per query.
BI Developer at DivVerse LLC
Snowflake is better and cheaper than Redshift and other cloud warehousing systems.
Senior Software Architect at USEReady
Snowflake Analytics is quite economical.
Data Governance Architect at Sterlite Technologies Ltd
 

Valuable Features

Azure Data Factory offers scalable ETL solutions with user-friendly interface, seamless Azure integration, robust orchestration, and effective dataset handling.
Snowflake Analytics provides scalable, secure, and user-friendly analytics with cloud integration, supporting diverse data needs and flexible data sharing.
It connects to different sources out-of-the-box, making integration much easier.
Sr. Technical Architect at Hexaware Technologies Limited
The platform excels in handling major datasets, particularly when working with Power BI for reporting purposes.
Data Engineer at Vthinktechnologies
Regarding the integration feature in Azure Data Factory, the integration part is excellent; we have major source connectors, so we can integrate the data from different data sources and also perform basic transformation while transforming, which is a great feature in Azure Data Factory.
Director at a computer software company with 1,001-5,000 employees
Running a considerable query on Microsoft SQL Server may take up to thirty minutes or an hour, while Snowflake executes the same query in less than three minutes.
BI Developer at DivVerse LLC
Snowflake Analytics supports data security with a single sign-on feature and complies with framework regulations, which is highly beneficial.
Data Governance Architect at Sterlite Technologies Ltd
Previously, we faced issues with slow queries due to traditional systems, but within Snowflake, we can assign separate virtual warehouses for reporting as well as data processing, ensuring that it does not impact tool performance and does not delay reporting to business users.
Data engineer at a tech vendor with 10,001+ employees
 

Categories and Ranking

Azure Data Factory
Ranking in Cloud Data Warehouse
5th
Average Rating
8.0
Reviews Sentiment
6.7
Number of Reviews
96
Ranking in other categories
Data Integration (4th)
Snowflake Analytics
Ranking in Cloud Data Warehouse
12th
Average Rating
8.4
Reviews Sentiment
7.1
Number of Reviews
44
Ranking in other categories
Web Analytics (2nd)
 

Mindshare comparison

As of June 2026, in the Cloud Data Warehouse category, the mindshare of Azure Data Factory is 5.3%, down from 7.6% compared to the previous year. The mindshare of Snowflake Analytics is 3.3%, up from 0.6% compared to the previous year. It is calculated based on PeerSpot user engagement data.
Cloud Data Warehouse Mindshare Distribution
ProductMindshare (%)
Azure Data Factory5.3%
Snowflake Analytics3.3%
Other91.4%
Cloud Data Warehouse
 

Featured Reviews

KandaswamyMuthukrishnan - PeerSpot reviewer
Director at a computer software company with 1,001-5,000 employees
Integrates diverse data sources and streamlines ETL processes effectively
Regarding potential areas of improvement for Azure Data Factory, there is a need for better data transformation, especially since many people are now depending on DataBricks more for connectivity and data integration. Azure Data Factory should consider how to enhance integration or filtering for more transformations, such as integrating with Spark clusters. I am satisfied with Azure Data Factory so far, but I suggest integrating some AI functionality to analyze data during the transition itself, providing insights such as null records, common records, and duplicates without running a separate pipeline or job. The monitoring tools in Azure Data Factory are helpful for optimizing data pipelines; while the current feature is adequate, they can improve by creating a live dashboard to see the online process, including how much percentage has been completed, which will be very helpful for people who are monitoring the pipeline.
Garima Goel - PeerSpot reviewer
Associate Principal Engineer at Nagarro
Have created secure cloud-based data lakes and improved real-time data processing using integrated AI features
There are many capabilities which Snowflake Analytics offers that I find valuable, such as the storage and compute engine that allows working with any cloud system such as AWS or Azure, alongside its efficiencies in storage computation and cost-effectiveness, which saves money compared to on-premise systems. We also have features such as pre-cached results, Time Travel, and fail-safe, which are very useful for restoring data if deleted accidentally, and the streams and data pipes that facilitate real-time ingestion are great features as well. Snowflake Analytics offers multiple new connectors, allowing me to connect it with Kafka, and with Snowpark, I can work with any programming language such as Python, Java, or Scala for data processing and analysis. The data sharing feature offered by Snowflake Analytics is good because it allows sharing specific sets of data to end customers or users from different Snowflake Analytics accounts without exposing the entire dataset for data security reasons. Snowflake Analytics' support for machine learning models and real-time insights has enhanced significantly. Originally, it wasn't strong in AI/ML, but now it has multiple models and forecasting capabilities, providing good competition to tools such as Databricks and Spark. In BI, I have worked majorly with Microsoft Power BI, and the integration with Snowflake Analytics is very easy. The way we integrate Snowflake Analytics with other on-premise systems just requires the warehouse details, username, passwords, and the account name, along with multiple options such as client ID and credentials for logging in and creating a session. The end-to-end encryption provided by Snowflake Analytics is very important because, in my previous firm, working in finance and investment management, data encryption is necessary due to the sensitive nature of customer data and the involvement of people's money. It's crucial to have encryption in transit and at rest, along with data masking features which Snowflake Analytics offers.
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Top Industries

By visitors reading reviews
Financial Services Firm
12%
Computer Software Company
9%
Manufacturing Company
9%
Construction Company
6%
Construction Company
15%
Financial Services Firm
9%
Computer Software Company
8%
Marketing Services Firm
7%
 

Company Size

By reviewers
Large Enterprise
Midsize Enterprise
Small Business
By reviewers
Company SizeCount
Small Business31
Midsize Enterprise21
Large Enterprise63
By reviewers
Company SizeCount
Small Business11
Midsize Enterprise13
Large Enterprise23
 

Questions from the Community

How do you select the right cloud ETL tool?
AWS Glue and Azure Data factory for ELT best performance cloud services.
How does Azure Data Factory compare with Informatica PowerCenter?
Azure Data Factory is flexible, modular, and works well. In terms of cost, it is not too pricey. It offers the stability and reliability I am looking for, good scalability, and is easy to set up an...
How does Azure Data Factory compare with Informatica Cloud Data Integration?
Azure Data Factory is a solid product offering many transformation functions; It has pre-load and post-load transformations, allowing users to apply transformations either in code by using Power Q...
What is your experience regarding pricing and costs for Snowflake Analytics?
Snowflake Analytics is quite economical. It does not appear to incur significant extra expenses beyond the solution's initial cost. However, a complete pricing analysis is still in progress.
What needs improvement with Snowflake Analytics?
In my opinion, Snowflake Analytics can be improved by introducing more features, such as additional integration options. I remember using Snowflake Pro, which allows exporting direct data into the ...
What is your primary use case for Snowflake Analytics?
Snowflake Analytics' data sharing feature has been instrumental for us because we were working with huge data sizes. Our workflow involved dumping data initially into an AWS S3 bucket, then sharing...
 

Overview

 

Sample Customers

1. Adobe 2. BMW 3. Coca-Cola 4. General Electric 5. Johnson & Johnson 6. LinkedIn 7. Mastercard 8. Nestle 9. Pfizer 10. Samsung 11. Siemens 12. Toyota 13. Unilever 14. Verizon 15. Walmart 16. Accenture 17. American Express 18. AT&T 19. Bank of America 20. Cisco 21. Deloitte 22. ExxonMobil 23. Ford 24. General Motors 25. IBM 26. JPMorgan Chase 27. Microsoft (Azure Data Factory is developed by Microsoft) 28. Oracle 29. Procter & Gamble 30. Salesforce 31. Shell 32. Visa
Lionsgate, Adobe, Sony, Capital One, Akamai, Deliveroo, Snagajob, Logitech, University of Notre Dame, Runkeeper
Find out what your peers are saying about Azure Data Factory vs. Snowflake Analytics and other solutions. Updated: June 2026.
900,644 professionals have used our research since 2012.