Try our new research platform with insights from 80,000+ expert users

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
6.8
Azure Data Factory offers cost-effective, efficient data consolidation for actionable insights, saving time and resources compared to manual processes.
Sentiment score
5.7
Snowflake Analytics offers varying ROI, with significant time savings and cost reductions depending on use case and implementation.
Our stakeholders and clients have expressed satisfaction with Azure Data Factory's efficiency and cost-effectiveness.
 

Customer Service

Sentiment score
6.4
Azure Data Factory support is generally satisfactory, with responsive assistance, though some users report delays or costly consulting.
Sentiment score
7.2
Snowflake Analytics support is highly rated for responsiveness and professionalism, despite some delays for smaller partners.
The technical support from Microsoft is rated an eight out of ten.
The technical support is responsive and helpful
The technical support for Azure Data Factory is generally acceptable.
The Snowflake Analytics documentation is excellent.
Recently we had a two-day session where the Snowflake Analytics team provided a demo on Cortex AI and its features.
The technical support for Snowflake Analytics is excellent based on what I have heard from others.
 

Scalability Issues

Sentiment score
7.5
Azure Data Factory is highly scalable and flexible but has room for improvement with third-party integrations and large datasets.
Sentiment score
7.8
Snowflake Analytics excels in scalable, cost-effective cloud resources, enabling independent compute and storage scaling to handle large data volumes.
Azure Data Factory is highly scalable.
Storage is unlimited because they use S3 if it is AWS, so storage has no limit.
It supports both horizontal and vertical scaling effectively.
Maintaining security and data governance becomes easier with an entire data lake in place, and the scalability improves performance.
 

Stability Issues

Sentiment score
7.8
Azure Data Factory is stable and reliable, with occasional issues in responsiveness and large dataset handling.
Sentiment score
8.4
Snowflake Analytics is highly rated for reliability, stability, and performance, with rare outages and minimal maintenance issues.
The solution has a high level of stability, roughly a nine out of ten.
Snowflake Analytics has been stable and reliable in my experience.
Snowflake Analytics is stable, scoring around eight point five to nine out of ten.
The Power BI team raised tickets for both Power BI and Snowflake Analytics, and their responses were very good.
 

Room For Improvement

Azure Data Factory needs better integration, scheduling, support, AI features, and user interface improvements for efficient data management.
Snowflake Analytics requires AI integration improvements, better UI, enhanced scalability, and integration with Python, Java, and cloud systems.
Incorporating more dedicated API sources to specific services like HubSpot CRM or Salesforce would be beneficial.
Sometimes, the compute fails to process data if there is a heavy load suddenly, and it doesn't scale up automatically.
There is a problem with the integration with third-party solutions, particularly with SAP.
AIML-based SQL prompt and query generation could be an area for enhancement.
If it offered flexibility similar to Oracle and supported more heterogeneous data sources and database connectivity, it would be even better.
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.
 

Setup Cost

Azure Data Factory offers competitive, flexible pricing based on usage, with costs integrating Azure services and varying significantly.
Enterprise buyers find Snowflake Analytics expensive but flexible, appreciating its data-sharing capabilities and varied pricing options.
The pricing is cost-effective.
It is considered cost-effective.
Snowflake charges per query, which amounts to a very minor cost, such as $0.015 per query.
Snowflake is better and cheaper than Redshift and other cloud warehousing systems.
Snowflake Analytics is quite economical.
 

Valuable Features

Azure Data Factory excels in data integration with user-friendly features, scalability, and over 100 connectors for seamless data movement.
Snowflake Analytics offers efficient, secure, cost-effective data management with advanced features, scalability, and seamless cloud integration.
It connects to different sources out-of-the-box, making integration much easier.
The platform excels in handling major datasets, particularly when working with Power BI for reporting purposes.
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.
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.
Snowflake Analytics supports data security with a single sign-on feature and complies with framework regulations, which is highly beneficial.
It is a data offering where I can see data lineage, data governance, and data security.
 

Categories and Ranking

Azure Data Factory
Ranking in Cloud Data Warehouse
2nd
Average Rating
8.0
Reviews Sentiment
6.9
Number of Reviews
92
Ranking in other categories
Data Integration (1st)
Snowflake Analytics
Ranking in Cloud Data Warehouse
10th
Average Rating
8.4
Reviews Sentiment
7.1
Number of Reviews
42
Ranking in other categories
Web Analytics (2nd)
 

Mindshare comparison

As of November 2025, in the Cloud Data Warehouse category, the mindshare of Azure Data Factory is 6.3%, down from 9.4% compared to the previous year. The mindshare of Snowflake Analytics is 1.2%, up from 0.5% compared to the previous year. It is calculated based on PeerSpot user engagement data.
Cloud Data Warehouse Market Share Distribution
ProductMarket Share (%)
Azure Data Factory6.3%
Snowflake Analytics1.2%
Other92.5%
Cloud Data Warehouse
 

Featured Reviews

KandaswamyMuthukrishnan - PeerSpot reviewer
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
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.
report
Use our free recommendation engine to learn which Cloud Data Warehouse solutions are best for your needs.
872,846 professionals have used our research since 2012.
 

Top Industries

By visitors reading reviews
Financial Services Firm
13%
Computer Software Company
12%
Manufacturing Company
9%
Government
7%
Computer Software Company
17%
Retailer
10%
Financial Services Firm
9%
Insurance Company
6%
 

Company Size

By reviewers
Large Enterprise
Midsize Enterprise
Small Business
By reviewers
Company SizeCount
Small Business31
Midsize Enterprise19
Large Enterprise55
By reviewers
Company SizeCount
Small Business10
Midsize Enterprise12
Large Enterprise21
 

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?
I do not see any areas that could be improved with Snowflake Analytics.
 

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: September 2025.
872,846 professionals have used our research since 2012.