Amazon Redshift vs Azure Data Factory comparison

Why PeerSpot?

Amazon Web Services (AWS) and Microsoft are both solutions in the Cloud Data Warehouse category. Amazon Web Services (AWS) is ranked #8 with an average rating of 8.3, while Microsoft is ranked #7 with an average rating of 8.0. Amazon Web Services (AWS) holds a 7.0% mindshare in CDW, compared to Microsoft’s 5.2% mindshare. Additionally, 87% of Amazon Web Services (AWS) users are willing to recommend the solution, compared to 92% of Microsoft users who would recommend it.

Amazon Redshift

Read 73 Amazon Redshift reviews

6,937 Views
4,509 Comparison Views

87% willing to recommend

Azure Data Factory

Read 97 Azure Data Factory reviews

14,793 Views
2,663 Comparison Views

92% willing to recommend

Amazon Redshift

Azure Data Factory

Comparison Buyer's Guide

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Executive SummaryUpdated on Dec 18, 2024

Amazon Redshift and Azure Data Factory are core competitors in the cloud data management space. Amazon Redshift offers robust performance and deep integration within the AWS ecosystem, making it particularly effective for large-scale data storage and processing. Azure Data Factory is well-regarded for its cost-effective pricing model and flexibility, which provides an edge for businesses prioritizing budget management.

Features: Amazon Redshift boasts excellent scalability, allowing for the handling of substantial data volumes seamlessly. Its distributed architecture enables rapid data processing through efficient use of resources. Its integration with AWS services enhances its operational capacity. Azure Data Factory excels in data orchestration, featuring a strong visual interface for easy pipeline creation and over 100 built-in connectors enabling extensive data integration options. Ease of use in crafting ETL solutions is a standout feature.

Room for Improvement: Amazon Redshift's pricing can be a barrier, requiring strategic cost management to optimize its usage benefits. The complexity of tuning performance parameters such as distribution and sort keys might need simplification for better accessibility. Azure Data Factory could further enhance its monitoring capabilities, allowing for more granular insights and troubleshooting. Additionally, improving the documentation on advanced integrations could streamline the implementation process.

Ease of Deployment and Customer Service: Amazon Redshift, being a managed service, offers streamlined deployment and reliable performance, augmented by AWS's comprehensive customer support. Azure Data Factory's integration into the Azure ecosystem ensures smooth deployment with structured support services from Microsoft, aiding in seamless data operations and troubleshooting.

Pricing and ROI: Amazon Redshift's pricing can be relatively high but offers significant ROI for enterprises needing extensive data management capabilities. Effective cost management is necessary to leverage its full potential without incurring unnecessary expenses. Azure Data Factory’s pay-per-use model is designed for resource optimization, offering flexible pricing that aligns well with businesses transitioning to the cloud. This approach helps businesses manage costs effectively while scaling their data operations.

To learn more, read our detailed Amazon Redshift vs. Azure Data Factory Report (Updated: September 2026).

Buyer's Guide

Amazon Redshift vs. Azure Data Factory

September 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

6.0

Some entities quickly achieved cost savings and ROI, while others face challenges with optimization and evaluating benefits.

Sentiment score

5.3

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

We earned back our investment in Amazon Redshift within the first year.

Hemanthreddy Vakiti

Junior Data engineer at a tech vendor with 10,001+ employees

For more quotes and insights, download the Amazon Redshift report

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

Customer Service

Sentiment score

6.8

Amazon Redshift support is efficient yet costly, praised for documentation, but phone contact and complex issue resolution face delays.

Sentiment score

6.2

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

Whenever we need support, if there is an issue accessing stored data due to regional data center problems, the Amazon team is very helpful and provides optimal solutions quickly.

Pavan Kum

Analyst at Cepstrum(EEE Students Society), IIT Guwahati

Documentation that allows anyone with prior knowledge of Redshift or SQL to resolve technical issues.

Hemanthreddy Vakiti

Junior Data engineer at a tech vendor with 10,001+ employees

It's costly when you enable support.

RiteshPurbey

Senior Analyst at ESRI INDIA

For more quotes and insights, download the Amazon Redshift report

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

Scalability Issues

Sentiment score

7.3

Amazon Redshift is highly scalable with flexible cluster adjustments, despite some challenges at larger scales and heavy loads.

Sentiment score

7.3

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

The scalability part needs improvement as the sizing requires trial and error.

PraveenJagadeesan

Data Analytics, Ai & Automation Lead at a venture capital & private equity firm with 10,001+ employees

We have successfully increased our storage space, which was a smooth process without server crashes before or after scaling.

Hemanthreddy Vakiti

Junior Data engineer at a tech vendor with 10,001+ employees

For more quotes and insights, download the Amazon Redshift report

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

Stability Issues

Sentiment score

7.3

Opinions on Amazon Redshift's stability vary, with some praising reliability and others noting issues in large clusters or maintenance.

Sentiment score

7.8

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

Amazon Redshift is a stable product, and I would rate it nine or ten out of ten for stability.

PraveenJagadeesan

Data Analytics, Ai & Automation Lead at a venture capital & private equity firm with 10,001+ employees

For more quotes and insights, download the Amazon Redshift report

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

Room For Improvement

Amazon Redshift users face challenges with performance, integration, cost, and features, preferring improved solutions like Snowflake's offerings.

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

They should bring the entire ETL data management process into Amazon Redshift.

PraveenJagadeesan

Data Analytics, Ai & Automation Lead at a venture capital & private equity firm with 10,001+ employees

Integration with AI could be a good improvement.

Pavan Kum

Analyst at Cepstrum(EEE Students Society), IIT Guwahati

Integration with AI features could elevate its capabilities and popularity.

Hemanthreddy Vakiti

Junior Data engineer at a tech vendor with 10,001+ employees

For more quotes and insights, download the Amazon Redshift report

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

Setup Cost

Amazon Redshift offers mid-to-high pricing, seen as reasonable due to its scalability and potential cost-effectiveness compared to competitors.

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

The cost of technical support is high.

RiteshPurbey

Senior Analyst at ESRI INDIA

It's a pretty good price and reasonable for the product quality.

PraveenJagadeesan

Data Analytics, Ai & Automation Lead at a venture capital & private equity firm with 10,001+ employees

The pricing of Amazon Redshift is expensive.

reviewer1099677

Co-Founder, Director at a tech consulting company with 51-200 employees

For more quotes and insights, download the Amazon Redshift report

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

Valuable Features

Amazon Redshift offers scalability, fast queries, AWS integration, flexibility, security, cost-effectiveness, easy setup, and compatibility for complex data management.

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

Amazon Redshift's performance optimization and scalability are quite helpful, providing functionalities such as scaling up and down.

PraveenJagadeesan

Data Analytics, Ai & Automation Lead at a venture capital & private equity firm with 10,001+ employees

Scalability is also a strong point; I can scale it however I want without any limitations.

reviewer1099677

Co-Founder, Director at a tech consulting company with 51-200 employees

The specific features of Amazon Redshift that are beneficial for handling large data sets include fast retrieval due to cloud services and scalability, which allows us to retrieve data quickly.

Pavan Kum

Analyst at Cepstrum(EEE Students Society), IIT Guwahati

For more quotes and insights, download the Amazon Redshift report

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

Categories and Ranking

Amazon Redshift

Ranking in Cloud Data Warehouse

8th

Average Rating

7.8

Reviews Sentiment

6.9

Number of Reviews

Ranking in other categories

Data Warehouse (6th), Database Management Systems (DBMS) (8th)

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)

Mindshare comparison

As of September 2026, in the Cloud Data Warehouse category, the mindshare of Amazon Redshift is 7.0%, down from 7.4% compared to the previous year. The mindshare of Azure Data Factory is 5.2%, down from 6.8% compared to the previous year. It is calculated based on PeerSpot user engagement data.

Cloud Data Warehouse Mindshare Distribution
Product	Mindshare (%)
Azure Data Factory	5.2%
Amazon Redshift	7.0%
Other	87.8%

Cloud Data Warehouse

Featured Reviews

Hemanthreddy Vakiti

Junior Data engineer at a tech vendor with 10,001+ employees

Optimized restaurant analytics has driven faster insights and streamlined daily reporting

Amazon Redshift offers massive parallel processing capability, allowing it to handle millions of records, along with integration with other AWS features such as S3 and QuickSight. The column-level storage supports high performance and easy data retrieval compared to other tools. The integration with S3 has helped my team immensely since S3 is our starting source, and the direct integration with Amazon Redshift simplifies the transformation and loading process. Columnar storage has benefited our performance significantly, allowing us to extract specific rows from tables with years of data much faster than other tools with row-level storage. Amazon Redshift has positively impacted our organization by significantly improving query performance and speed. Features such as easy integration with S3 allow us to process millions of records efficiently, ultimately saving us nearly one hour per day for our project.

Read full review

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

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Top Industries

By visitors reading reviews

Financial Services Firm

16%

Construction Company

11%

Outsourcing Company

10%

Manufacturing Company

Financial Services Firm

11%

Manufacturing Company

Computer Software Company

Construction Company

Company Size

By reviewers

Large Enterprise

Midsize Enterprise

Small Business

By reviewers
Company Size	Count
Small Business	28
Midsize Enterprise	20
Large Enterprise	29

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

Questions from the Community

How does Amazon Redshift compare with Microsoft Azure Synapse Analytics?

Amazon Redshift is very fast, has a very good response time, and is very user-friendly. The initial setup is very straightforward. This solution can merge and integrate well with many different dat...

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What is your experience regarding pricing and costs for Amazon Redshift?

My experience with pricing and setup cost is satisfactory, as we have been loyal clients of Amazon since the beginning of our organization. However, I am not aware of the exact costs associated wit...

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What needs improvement with Amazon Redshift?

Amazon Redshift could improve by enhancing its UI to be more user-friendly for non-technical users and by offering better cost management, as similar tools tend to be less expensive. Additionally, ...

See all answers

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...

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Comparisons

Snowflake vs Amazon Redshift

Compared 12% of the time

Teradata vs Amazon Redshift

Compared 7% of the time

Microsoft Azure Synapse Analytics vs Amazon Redshift

Compared 6% of the time

Amazon EMR vs Amazon Redshift

Compared 5% of the time

IBM Db2 Warehouse on Cloud vs Amazon Redshift

Compared 5% of the time

More Amazon Redshift Competitors

Snowflake vs Azure Data Factory

Compared 4% of the time

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

More Azure Data Factory Competitors

Product Reports

Buyer's Guide

Amazon Redshift

September 2026

Download Amazon Redshift product report

Buyer's Guide

Azure Data Factory

September 2026

Download Azure Data Factory product report

Overview

Amazon Redshift is a dynamic data warehousing and analytics platform offering scalability and seamless AWS integration for high-performance query processing and diverse data management.

Amazon Redshift provides robust data integration capabilities with AWS services like S3 and QuickSight, enabling efficient data warehousing and analytics. It is known for fast query performance due to its columnar storage and can handle diverse file formats. With a user-friendly SQL interface, Redshift supports data compression and offers a strong cost-performance ratio. Its secure VPC configurations and compatibility with data science tools enhance its functionality, although there is room for improving snapshot restoration, dynamic scaling, and processing large datasets.

What are the key features of Amazon Redshift?

Scalability: Allows growth with business needs, accommodating increasing data volumes.
Massive Parallel Processing: Speeds up query performance through parallel data processing.
Seamless AWS Integration: Connects smoothly with services like S3 and QuickSight for enhanced functionality.
Columnar Storage: Enhances query performance by storing data in columns.
User-friendly SQL Interface: Simplifies data query and manipulation.
Data Compression: Efficiently compresses data to reduce storage costs.

What benefits should users look for in reviews?

Cost-Performance Ratio: Offers competitive pricing with high processing efficiency.
Fast Query Performance: Delivers quick data retrieval and processing speeds.
Security Features: Ensures data security through VPC configurations.
Integration Flexibility: Easily integrates with data science tools and BI platforms.

In industries, Amazon Redshift is essential for managing extensive datasets for business intelligence, operational insights, and reporting. It supports data integration from ERPs and S3, handles SQL queries for comprehensive analysis, and facilitates data storage and transformation. Companies use it for predictive modeling and connect with BI tools like Tableau and Power BI to derive actionable insights.

Amazon Web Services (AWS)

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

Sample Customers

Liberty Mutual Insurance, 4Cite Marketing, BrandVerity, DNA Plc, Sirocco Systems, Gainsight, Blue 449

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

Buyer's Guide

Amazon Redshift vs. Azure Data Factory

September 2026

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