Azure Data Factory vs Snowflake Analytics comparison

Microsoft and Snowflake Computing are both solutions in the Cloud Data Warehouse category. Microsoft is ranked #3 with an average rating of 8.0, while Snowflake Computing is ranked #8 with an average rating of 8.3. Microsoft holds a 12.9% mindshare in CDW, compared to Snowflake Computing’s 0.7% mindshare. Additionally, 92% of Microsoft users are willing to recommend the solution, compared to 100% of Snowflake Computing users who would recommend it.

Azure Data Factory

Read 86 Azure Data Factory reviews

5,937 Views
4,775 Comparison Views

92% willing to recommend

Snowflake Analytics

Read 35 Snowflake Analytics reviews

410 Views
277 Comparison Views

100% willing to recommend

Azure Data Factory

Snowflake Analytics

Comparison Buyer's Guide

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Executive Summary

We performed a comparison between Azure Data Factory and Snowflake Analytics based on real PeerSpot user reviews.

Find out in this report how the two Cloud Data Warehouse solutions compare in terms of features, pricing, service and support, easy of deployment, and ROI.

To learn more, read our detailed Azure Data Factory vs. Snowflake Analytics Report (Updated: October 2024).

Buyer's Guide

Azure Data Factory vs. Snowflake Analytics

October 2024

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Helped 816,406 peers since 2012

Categories and Ranking

Azure Data Factory

Ranking in Cloud Data Warehouse

3rd

Average Rating

8.0

Reviews Sentiment

6.7

Number of Reviews

Ranking in other categories

Data Integration (1st)

Snowflake Analytics

Ranking in Cloud Data Warehouse

8th

Average Rating

8.4

Number of Reviews

Ranking in other categories

Web Analytics (1st)

Mindshare comparison

As of November 2024, in the Cloud Data Warehouse category, the mindshare of Azure Data Factory is 12.9%, down from 13.4% compared to the previous year. The mindshare of Snowflake Analytics is 0.7%, down from 0.8% compared to the previous year. It is calculated based on PeerSpot user engagement data.

Cloud Data Warehouse

Featured Reviews

Thulani David Mngadi

Data architect at Old Mutual

Data flow feature is valuable for data transformation tasks

The workflow automation features in GitLab, particularly its low code/no code approach, are highly beneficial for accelerating development speed. This feature allows for quick creation of pipelines and offers customization options for integration needs, making it versatile for various use cases. GitLab supports a wide range of connectors, catering to a majority of integration needs. Azure Data Factory's virtual enterprise and monitoring capabilities, the visual interface of GitLab makes it user-friendly and easy to teach, facilitating adoption within teams. While the monitoring capabilities are sufficient out of the box, they may not be as comprehensive as dedicated enterprise monitoring tools. GitLab's monitoring features are manageable for production use, with the option to integrate log analytics or create custom dashboards if needed. The data flow feature in Azure Data Factory within GitLab is valuable for data transformation tasks, especially for those who may not have expertise in writing complex code. It simplifies the process of data manipulation and is particularly useful for individuals unfamiliar with Spark coding. While there could be improvements for more flexibility, overall, the data flow feature effectively accomplishes its purpose within GitLab's ecosystem.

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Manoj Kambli

Director at Hexaware Technologies Limited

For processing data, it can be easily optimized and supports structured and unstructured data

In terms of cost. Many customers face issues with the expenses on Snowflake. The pricing visibility is complex. If you understand pricing, you can estimate costs, but if not, it can be challenging. They need to provide better cost visibility upfront. For example, credits are not always utilized properly, which isn't easy for new users. A more user-friendly cost calculator would help, as the current one requires expertise to use effectively. These things are not easy for someone who is new to Snowflake, unlike Azure's calculators, which give good visibility into the cost. It does have a calculator, but you need to be skilled in using it. Otherwise, it's hard to estimate the total cost for future loads. For additional features, there could be its own AI model like Google has Gemini. Snowflake can come up with those kinds of features for Analytics. If you can just type in your prompt and get answers, especially for Analytics people on the client side, they will love that. Like, in Google's Gemini, you type the prompt and get the answers based on the data available. If they come up with that kind of AI and UI, it will be easier for clients to analyze their data. They can just type a query like, "What is my highest selling product?" They don't have to write a complex query.

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Quotes from Members

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

Pros

"I can do everything I want with SSIS and Azure Data Factory."

"Data Factory's most valuable feature is Copy Activity."

"One of the most valuable features of Azure Data Factory is the drag-and-drop interface. This helps with workflow management because we can just drag any tables or data sources we need. Because of how easy it is to drag and drop, we can deliver things very quickly. It's more customizable through visual effect."

"It is beneficial that the solution is written with Spark as the back end."

"The function of the solution is great."

"The most valuable features of Azure Data Factory are the flexibility, ability to move data at scale, and the integrations with different Azure components."

"An excellent tool for pipeline orchestration."

"The most valuable feature of Azure Data Factory is the core features that help you through the whole Azure pipeline or value chain."

More Azure Data Factory pros

"Features like the fact that the solution is very fast and available on the cloud are some of the valuable attributes of the solution."

"Its performance speed is very good."

"It's a scalable solution because you can analyze a huge amount of data in the solution."

"It is quite a convenient tool."

"One of the valuable features is the solution’s time travel capability. The solution is highly stable. The solution is highly scalable. The initial setup is straightforward, and the deployment process is quick and efficient. I recommend the solution. Overall, I rate it a perfect ten."

"The most valuable feature of Snowflake Analytics is the ability to control and manage the cost."

"Time Travel and Snowpipe are good features."

"It can run complex workloads with varied compute."

More Snowflake Analytics pros

Cons

"Lacks a decent UI that would give us a view of the kinds of requests that come in."

"I rate Azure Data Factory six out of 10 for stability. ADF is stable now, but we had problems recently with indexing on an SQL database. It's slow when dealing with a huge volume of data. It depends on whether the database is configured as general purpose or hyperscale."

"There are limitations when processing more than one GD file."

"Azure Data Factory's pricing in terms of utilization could be improved."

"My only problem is the seamless connectivity with various other databases, for example, SAP."

"The pricing model should be more transparent and available online."

"Data Factory would be improved if it were a little more configuration-oriented and not so code-oriented and if it had more automated features."

"Sometimes I need to do some coding, and I'd like to avoid that. I'd like no-code integrations."

More Azure Data Factory cons

"The technical support is not very good."

"The solution needs to consider including some updates in the future."

"I cannot comment on the product's stability because we are still struggling with its performance."

"One notable absence in Snowflake's offerings is an on-premises solution."

"Moving data from legacy systems to Snowflake is not that easy. There are some cases where processors are not actually compatible with Snowflake."

"I don't see many drawbacks with Snowflake Analytics, but it's not as mature as other tools. It is evolving and needs to integrate various features, like data loading and analytics, better. These components are not fully connected, so the tool should become a more integrated application."

"We haven't seen any areas that are lacking."

"The pricing visibility is complex. If you understand pricing, you can estimate costs, but if not, it can be challenging."

More Snowflake Analytics cons

Pricing and Cost Advice

"The licensing cost is included in the Synapse."

"The solution's fees are based on a pay-per-minute use plus the amount of data required to process."

"Understanding the pricing model for Data Factory is quite complex."

"The cost is based on the amount of data sets that we are ingesting."

"I am aware of the pricing of Azure Data Factory, but I prefer not to disclose specific details."

"Our licensing fees are approximately 15,000 ($150 USD) per month."

"Azure products generally offer competitive pricing, suitable for diverse budget considerations."

"The licensing model for Azure Data Factory is good because you won't have to overpay. Pricing-wise, the solution is a five out of ten. It was not expensive, and it was not cheap."

More Azure Data Factory pricing and cost advice

"It is not overly expensive. I would rate the pricing a six out of ten, with ten being expensive."

"Snowflake Analytics is not an expensive solution, and its pricing is average."

"Snowflake Analytics is a little more costly than Azure."

"It is an expensive solution, but the kind of usability and flexibility it proactively provides for the organizations justify the price."

"The tool is quite expensive."

"The pricing is on the higher side."

"I rate the product price a seven on a scale of one to ten, where one is low price, and ten is high price."

"The solution's price is high and I would rate it an eight out of ten."

More Snowflake Analytics pricing and cost advice

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Top Industries

By visitors reading reviews

Financial Services Firm

13%

Computer Software Company

12%

Manufacturing Company

Healthcare Company

Computer Software Company

14%

Retailer

10%

Financial Services Firm

Manufacturing Company

Company Size

By reviewers

Large Enterprise

Midsize Enterprise

Small Business

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...

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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...

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What do you like most about Snowflake Analytics?

Its performance speed is very good.

See all answers

What is your experience regarding pricing and costs for Snowflake Analytics?

I would rate the pricing of Snowflake Analytics a two out of ten, where one is cheap, and ten is expensive. Especially when compared to competitors and what they offer, the pricing is good. Users p...

See all answers

What needs improvement with Snowflake Analytics?

Snowflake Analytics should probably have more built-in tools for master data management, data purification, and enhancement. Instead of using third-party tools, it would probably be good if it coul...

See all answers

Comparisons

Informatica PowerCenter vs Azure Data Factory

Compared 14% of the time

Snowflake vs Azure Data Factory

Compared 11% of the time

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

Compared 8% of the time

Alteryx Designer vs Azure Data Factory

Compared 7% of the time

IBM InfoSphere DataStage vs Azure Data Factory

Compared 4% of the time

More Azure Data Factory Competitors

Adobe Analytics vs Snowflake Analytics

Compared 24% of the time

Mixpanel vs Snowflake Analytics

Compared 17% of the time

Amplitude vs Snowflake Analytics

Compared 13% of the time

Glassbox vs Snowflake Analytics

Compared 11% of the time

SAP IQ vs Snowflake Analytics

Compared 9% of the time

More Snowflake Analytics Competitors

Product Reports

Buyer's Guide

Azure Data Factory

November 2024

Download Azure Data Factory product report

Buyer's Guide

Snowflake Analytics

October 2024

Download Snowflake Analytics product report

Learn More

Microsoft

Snowflake Computing

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.

Conventional data platforms and big data solutions struggle to deliver on their fundamental purpose: to enable any user to work with any data, without limits on scale, performance or flexibility. Whether you’re a data analyst, data scientist, data engineer, or any other business or technology professional, you’ll get more from your data with Snowflake.

To achieve this, we built a new data platform from the ground up for the cloud. It’s designed with a patented new architecture to be the centerpiece for data pipelines, data warehousing, data lakes, data application development, and for building data exchanges to easily and securely share governed data. The result, A platform delivered as a service that’s powerful but simple to use.

Snowflake’s cloud data platform supports a multi-cloud strategy, including a cross-cloud approach to mix and match clouds as you see fit. Snowflake delivers advantages such as global data replication, which means you can move your data to any cloud in any region, without having to re-code your applications or learn new skills.

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

Buyer's Guide

Azure Data Factory vs. Snowflake Analytics

October 2024

Free Report: Azure Data Factory vs. Snowflake Analytics

Find out what your peers are saying about Azure Data Factory vs. Snowflake Analytics and other solutions. Updated: October 2024.

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