Azure Data Factory vs Snowflake comparison

Why PeerSpot?

Microsoft and Snowflake Computing are both solutions in the Cloud Data Warehouse category. Microsoft is ranked #7 with an average rating of 8.0, while Snowflake Computing is ranked #1 with an average rating of 8.3. Microsoft holds a 5.2% mindshare in CDW, compared to Snowflake Computing’s 15.4% mindshare. Additionally, 92% of Microsoft users are willing to recommend the solution, compared to 97% of Snowflake Computing users who would recommend it.

Azure Data Factory

Read 97 Azure Data Factory reviews

14,793 Views
2,663 Comparison Views

92% willing to recommend

Snowflake

Read 106 Snowflake reviews

17,461 Views
8,207 Comparison Views

97% willing to recommend

Azure Data Factory

Snowflake

Comparison Buyer's Guide

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Executive SummaryUpdated on Feb 1, 2026

Snowflake and Azure Data Factory are competitors in cloud data management and integration solutions. While Snowflake is favored for its data management and warehouse capabilities, Azure Data Factory leads with its integration features.

Features: Snowflake excels in path applications, time travel retrieval, and scalability. It offers ease of management and zero-copy cloning, which streamlines data operations. Azure Data Factory stands out with its intuitive data flow operations, effective orchestration, and ability to support various data sources, particularly in hybrid scenarios. Its integration with other Azure services enhances its versatility.

Room for Improvement: Snowflake users suggest improvements in AI tool integration, better handling of unstructured data, and reduced costs. Enhanced external tool integration and user experience with pipelines are also needed. Azure Data Factory could improve performance during heavy loads, provide better monitoring capabilities, and enhance integration with SAP and other third-party solutions. Easier use and clearer pricing are also desired.

Ease of Deployment and Customer Service: Snowflake is predominantly cloud-based with responsive customer support, but lacks some service-level agreements. Azure Data Factory offers hybrid cloud deployments, and while it generally provides helpful customer service, its technical support documentation and real-time assistance could be improved.

Pricing and ROI: Snowflake uses a credit-based pricing model which can be cost-effective, but unpredictable. It delivers strong ROI. Azure Data Factory has a pay-as-you-go model seen as cost-effective, though the usage-based pricing sometimes makes cost prediction challenging. Both solutions are seen as solid investments, with Azure Data Factory being particularly effective in cutting down on data integration expenses.

To learn more, read our detailed Azure Data Factory vs. Snowflake Report (Updated: August 2026).

Buyer's Guide

Azure Data Factory vs. Snowflake

August 2026

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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

5.3

Azure Data Factory centralizes data, cuts costs, boosts efficiency, enhances client satisfaction, and delivers a 20-30% return.

Sentiment score

5.7

Companies appreciate Snowflake's scalability and security, reporting cost reduction and productivity gains, despite challenges in isolating ROI impact.

Our stakeholders and clients have expressed satisfaction with Azure Data Factory's efficiency and cost-effectiveness.

Deena Thayalan

Data Engineer at Vthinktechnologies

For more quotes and insights, download the Azure Data Factory report

No quotes available

For more quotes and insights, download the Snowflake report

Customer Service

Sentiment score

6.2

Azure Data Factory support is generally proficient and accessible, though response times and costs can vary for dedicated support.

Sentiment score

5.5

Snowflake's responsive, knowledgeable support and resources are valued, though time differences and complex queries can cause delays.

On a scale of one to ten, I would rate the technical support as nine.

Hafiz Abdul Mannan

Senior Consultant Oracle Technologies at a tech vendor with 10,001+ employees

The technical support from Microsoft is rated an eight out of ten.

Brian Sullivan

Chief Analytics Officer at Idiro Analytics

The technical support is responsive and helpful

Joy Maitra

Sr. Technical Architect at Hexaware Technologies Limited

For more quotes and insights, download the Azure Data Factory report

We sought this documentation multiple times but faced difficulty in obtaining it.

AmolDhormare

Data Integration Developer at a tech services company with 1,001-5,000 employees

I received great support in migrating data to Snowflake, with quick responses and innovative solutions.

Snehasish Das

Technology Leader at eTCaaS

I am satisfied with the work of technical support from Snowflake; they are responsive and helpful.

SunilPatil1

Asset Builder at Genpact - Headstrong

For more quotes and insights, download the Snowflake report

Scalability Issues

Sentiment score

7.3

Azure Data Factory is scalable and flexible but sometimes requires support for quotas and improvements for broader scalability.

Sentiment score

7.7

Snowflake offers seamless scalability and flexibility in managing large datasets efficiently, with some noting potential cost implications.

Azure Data Factory is highly scalable.

Brian Sullivan

Chief Analytics Officer at Idiro Analytics

I did not experience scalability issues.

SubrataDey

Principal Data Engineer at Oracle

For more quotes and insights, download the Azure Data Factory report

Snowflake is very scalable and has a dedicated team constantly improving the product.

Snehasish Das

Technology Leader at eTCaaS

The billing doubles with size increase, but processing does not necessarily speed up accordingly.

reviewer1438647

Data Architect at a tech services company with 10,001+ employees

Recently, Snowflake has introduced streaming capabilities, real-time and dynamic tables, along with various connectors.

reviewer2403603

Senior Data Engineer at a tech services company with 11-50 employees

For more quotes and insights, download the Snowflake report

Stability Issues

Sentiment score

7.8

Azure Data Factory is highly rated for stability, though performance varies with setup, data volume, and resource allocation.

Sentiment score

8.3

Snowflake is praised for its high stability and performance, handling large datasets seamlessly across various cloud providers.

The solution has a high level of stability, roughly a nine out of ten.

Brian Sullivan

Chief Analytics Officer at Idiro Analytics

It gives me the accurate result.

Kunal Das

Test Engineer at Happiest Minds Technologies

I have been using Azure Data Factory for a very long time, and I did not find too many issues.

SubrataDey

Principal Data Engineer at Oracle

For more quotes and insights, download the Azure Data Factory report

Snowflake is highly stable and performs well even with large data sets exceeding terabytes, maintaining stability throughout.

AmolDhormare

Data Integration Developer at a tech services company with 1,001-5,000 employees

Snowflake is very stable, especially when used with AWS.

Snehasish Das

Technology Leader at eTCaaS

Snowflake as a SaaS offering means that maintenance isn't an issue for me.

reviewer1438647

Data Architect at a tech services company with 10,001+ employees

For more quotes and insights, download the Snowflake report

Room For Improvement

Azure Data Factory needs better setup, connectivity, documentation, support, performance, and UI for enhanced functionality and user experience.

Users recommend UI and pricing transparency improvements, enhanced analytics, data tools, support, and unstructured data integration in Snowflake.

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.

Hafiz Abdul Mannan

Senior Consultant Oracle Technologies at a tech vendor with 10,001+ employees

If I am making a pipeline, it should give me suggestions, such as which activity should be used, so that I don't have to remember each activity.

Kunal Das

Test Engineer at Happiest Minds Technologies

Incorporating more dedicated API sources to specific services like HubSpot CRM or Salesforce would be beneficial.

Brian Sullivan

Chief Analytics Officer at Idiro Analytics

For more quotes and insights, download the Azure Data Factory report

Enhancements in user experience for data observability and quality checks would be beneficial, as these tasks currently require SQL coding, which might be challenging for some users.

reviewer1438647

Data Architect at a tech services company with 10,001+ employees

What things you are going with to ask the support and how we manage the relationship matters a lot.

SunilPatil1

Asset Builder at Genpact - Headstrong

If more connectors were brought in and more visibility features were added, particularly around cost tracking in the FinOps area, it would be beneficial.

reviewer2403603

Senior Data Engineer at a tech services company with 11-50 employees

For more quotes and insights, download the Snowflake report

Setup Cost

Azure Data Factory's pricing is competitive but complex, requiring careful monitoring to manage costs for high data usage.

Snowflake's pricing is flexible and competitive but estimating costs can be challenging due to its credit-based model.

The pricing is cost-effective.

Brian Sullivan

Chief Analytics Officer at Idiro Analytics

It is considered cost-effective.

Joy Maitra

Sr. Technical Architect at Hexaware Technologies Limited

For more quotes and insights, download the Azure Data Factory report

When it comes to cloud support, the setup cost is very cheap compared to other platforms, such as Oracle or PostgreSQL, which typically require higher costs.

AmolDhormare

Data Integration Developer at a tech services company with 1,001-5,000 employees

Snowflake's pricing is on the higher side.

Snehasish Das

Technology Leader at eTCaaS

Snowflake lacks transparency in estimating resource usage.

reviewer1438647

Data Architect at a tech services company with 10,001+ employees

For more quotes and insights, download the Snowflake report

Valuable Features

Azure Data Factory excels in performance, ease of use, scalability, and integration, making it highly valued for ETL processes.

Snowflake provides scalable, efficient data management with SQL access, multi-cloud support, cost-effective plans, and strong integration capabilities.

It connects to different sources out-of-the-box, making integration much easier.

Joy Maitra

Sr. Technical Architect at Hexaware Technologies Limited

The platform excels in handling major datasets, particularly when working with Power BI for reporting purposes.

Deena Thayalan

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.

KandaswamyMuthukrishnan

Director at a computer software company with 1,001-5,000 employees

For more quotes and insights, download the Azure Data Factory report

We had a comparison with Databricks and Snowflake a few months back, and this auto-scaling takes an edge within Snowflake; that's what our observation reflects.

SunilPatil1

Asset Builder at Genpact - Headstrong

I have used the Snowflake Zero-Copy Cloning feature in the past while prototyping data in lower environments. This feature is helpful as it saves a lot of time during the data replication process.

reviewer2403603

Senior Data Engineer at a tech services company with 11-50 employees

Snowflake has contributed to significant cost savings.

AmolDhormare

Data Integration Developer at a tech services company with 1,001-5,000 employees

For more quotes and insights, download the Snowflake report

Categories and Ranking

Azure Data Factory

Ranking in Cloud Data Warehouse

7th

Average Rating

8.0

Reviews Sentiment

6.7

Number of Reviews

Ranking in other categories

Data Integration (5th)

Snowflake

Ranking in Cloud Data Warehouse

1st

Average Rating

8.4

Reviews Sentiment

6.9

Number of Reviews

106

Ranking in other categories

Data Warehouse (1st), AI Synthetic Data (1st), Database Management Systems (DBMS) (3rd), AI Software Development (6th)

Mindshare comparison

As of September 2026, in the Cloud Data Warehouse category, the mindshare of Azure Data Factory is 5.2%, down from 6.8% compared to the previous year. The mindshare of Snowflake is 15.4%, down from 17.4% compared to the previous year. It is calculated based on PeerSpot user engagement data.

Cloud Data Warehouse Mindshare Distribution
Product	Mindshare (%)
Snowflake	15.4%
Azure Data Factory	5.2%
Other	79.4%

Cloud Data Warehouse

Featured Reviews

Kunal Das

Test Engineer at Happiest Minds Technologies

Drag-and-drop pipelines have saved days of work and now automate data movement and backfilling

If the AI features were more improved so that I don't have to provide each and every detail, Azure Data Factory could be improved in a much better way by improving the AI features. For example, if I want to fetch any data from a raw source, I need to provide each and every detail. But if I am just uploading my raw data and if AI will sync with that data, it can analyze that data and give me proper suggestions on how that should be done in a proper way. Automatic suggestions could improve in a much better way. As I have mentioned, the AI features as well as more drag-and-drop activities could be improved. If I am making a pipeline, it should give me suggestions, such as which activity should be used, so that I don't have to remember each activity. If I have used one activity, I shouldn't have to remember what activity should I use next. It should give auto-suggestions. That is why I have given a nine out of 10. Currently, I don't know about its governance and security, but in view of its improvement, I think Azure Data Factory should improve in these areas. As I already mentioned, the AI features should be improved. Also, the auto-suggestion features should also improve.

Read full review

SunilPatil1

Asset Builder at Genpact - Headstrong

Have prioritized security while managing multi-agent data migration and cloud adoption

We utilize Time Travel with Snowflake because this is a very useful feature. Everyone finds it crucial because in conventional data platforms, it's very difficult to handle these kinds of things. This feature is essential, though I don't have the use cases currently; it is just there for implementation. Regarding Snowflake's automated scaling and suspension features, this auto-scaling is very significant. We had a comparison with Databricks and Snowflake a few months back, and this auto-scaling takes an edge within Snowflake; that's what our observation reflects.

Read full review

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Top Industries

By visitors reading reviews

Financial Services Firm

11%

Manufacturing Company

Computer Software Company

Construction Company

Financial Services Firm

18%

Manufacturing Company

11%

Outsourcing Company

Construction Company

Company Size

By reviewers

Large Enterprise

Midsize Enterprise

Small Business

By reviewers
Company Size	Count
Small Business	31
Midsize Enterprise	21
Large Enterprise	64

By reviewers
Company Size	Count
Small Business	30
Midsize Enterprise	20
Large Enterprise	61

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.

See all answers

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...

See all answers

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...

See all answers

What is your experience regarding pricing and costs for Snowflake?

I am not the person who manages pricing, setup cost, and licensing. Our team is not limited in pricing. The only experience we have had in terms of running and reprocessing a large number of histor...

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What needs improvement with Snowflake?

One main area for improvement in Snowflake is cost visibility and optimization; while it's flexible and scalable, costs can increase quickly if warehouses are left running unnecessarily or workload...

See all answers

What is your primary use case for Snowflake?

As a Data Engineer, I primarily use Snowflake for data warehousing tasks as well as ETL processing, and sometimes I also use it for data sharing. I personally find Snowflake better than other tools...

See all answers

Comparisons

Databricks vs Azure Data Factory

Compared 4% of the time

Informatica Intelligent Data Management Cloud (IDMC) vs Azure Data Factory

Compared 3% of the time

Palantir Foundry vs Azure Data Factory

Compared 3% of the time

SnapLogic vs Azure Data Factory

Compared 3% of the time

Oracle Data Integrator (ODI) vs Azure Data Factory

Compared 3% of the time

More Azure Data Factory Competitors

Teradata vs Snowflake

Compared 6% of the time

Microsoft Azure Synapse Analytics vs Snowflake

Compared 6% of the time

Databricks vs Snowflake

Compared 5% of the time

Amazon Redshift vs Snowflake

Compared 5% of the time

Oracle Exadata vs Snowflake

Compared 3% of the time

More Snowflake Competitors

Product Reports

Buyer's Guide

Azure Data Factory

August 2026

Download Azure Data Factory product report

Buyer's Guide

Snowflake

August 2026

Download Snowflake product report

Also Known As

No data available

Snowflake Computing, Snowflake Data Cloud

Overview

Azure Data Factory efficiently manages and integrates data from various sources, enabling seamless movement and transformation across platforms. Its valuable features include seamless integration with Azure services, handling large data volumes, flexible transformation, user-friendly interface, extensive connectors, and scalability. Users have experienced improved team performance, workflow simplification, enhanced collaboration, streamlined processes, and boosted productivity.

Microsoft

Snowflake provides a modern data warehousing solution with features designed for seamless integration, scalability, and consumption-based pricing. It handles large datasets efficiently, making it a market leader for businesses migrating to the cloud.

Snowflake offers a flexible architecture that separates storage and compute resources, supporting efficient ETL jobs. Known for scalability and ease of use, it features built-in time zone conversion and robust data sharing capabilities. Its enhanced security, performance, and ability to handle semi-structured data are notable. Users suggest improvements in UI, pricing, on-premises integration, and data science functions, while calling for better transaction performance and machine learning capabilities. Users benefit from effective SQL querying, real-time analytics, and sharing options, supporting comprehensive data analysis with tools like Tableau and Power BI.

What are Snowflake's Key Features?

Scalability: Easily adjusts to handle growing data volumes.
Seamless Integration: Works with a wide range of platforms.
Consumption-Based Costs: Pay only for what you use.
Time Travel: Access historical data effortlessly.
Data Sharing: Secure and efficient sharing of datasets.
Time Zone Conversion: Built-in feature for global operations.
Security: Robust measures to protect sensitive information.
Compute and Storage Separation: Independent scaling for optimal performance.

What Benefits Should You Look for?

Cost Efficiency: Optimized pricing models for minimal waste.
Enhanced Performance: Fast queries and processing times.
Flexibility: Handles both structured and semi-structured data.
Analytics Capabilities: Supports advanced data analysis and reporting.

In industries like finance, healthcare, and retail, Snowflake's flexible data warehousing and analytics capabilities facilitate cloud migration, streamline data storage, and allow organizations to consolidate data from multiple sources for advanced insights and AI-driven strategies. Its integration with analytics tools supports comprehensive data analysis and reporting tasks.

Snowflake Computing

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

Accordant Media, Adobe, Kixeye Inc., Revana, SOASTA, White Ops

Buyer's Guide

Azure Data Factory vs. Snowflake

August 2026

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