Azure Data Factory vs Fivetran comparison

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Azure Data Factory

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Executive SummaryUpdated on Dec 19, 2024

Azure Data Factory and Fivetran are both leading ETL tools in the data integration category. Azure Data Factory has an advantage due to its comprehensive feature set suitable for complex data scenarios while Fivetran stands out for its simplicity and efficiency in data replication.

Features: Azure Data Factory provides comprehensive ETL support with enhanced scalability and a large selection of connectors. Its robust data transformation capabilities via a visual interface and seamless integration with other Azure services allow for a streamlined process. It is particularly beneficial for complex data scenarios. Fivetran offers simplicity and minimizes manual intervention in data replication. Its managed pipelines and integration with DBT provide advantages, though it lags in advanced transformation capabilities compared to Azure Data Factory.

Room for Improvement: Azure Data Factory users report challenges with debugging tools, user interface intuitiveness, and integration with data providers. Enhancements in data capture features and support for machine learning models are desired, along with simplification of its pricing model. Fivetran could improve logging detail and data pipeline observability for better monitoring. Its high cost for large data sources and limited customization options are also noted, with a need for more connectors and transparent pricing.

Ease of Deployment and Customer Service: Azure Data Factory is well-suited for Microsoft Azure's public cloud, offering deployment flexibility and integration with Azure services, though its support has been criticized for response time and costs. Fivetran's customer service is considered adequate but faces issues with problem resolution speed. While both products allow public cloud deployments, Fivetran is favored for quick and easy data replication setups.

Pricing and ROI: Azure Data Factory employs a pay-as-you-go pricing model, aligning costs with usage but potentially leading to unpredictability. It is generally cost-competitive, with economic value increased when part of the Azure ecosystem. Some users express concerns about costs due to usage spikes. Fivetran is noted for higher costs, especially for large data volumes. Its usage-based pricing model is perceived as expensive by some users, but its rapid deployment and data management benefits can justify the expense.

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

Azure Data Factory vs. Fivetran

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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

6.6

Fivetran offers significant time and cost-saving benefits, simplifying data integration and maintenance while reducing reliance on data engineers.

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

Fivetran provides time savings, cost reductions, and improvements in data quality.

Team Lead Data Engineer at Data Pilot

It saves us the effort of having one to two data engineers managing the tasks that Fivetran handles.

For more quotes and insights, download the Fivetran report

Lead Data Engineer at Sensilab

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

6.0

Fivetran customer support is efficient yet sometimes slow, rated 7-9, with calls for improved critical issue communication.

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.

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

Chief Analytics Officer at Idiro Analytics

The technical support is responsive and helpful

Joy Maitra

Sr. Technical Architect at Hexaware Technologies Limited

If they could provide support more quickly, that would be great.

Vigneswar Jeyaraj

Manager at InfoCepts

The technical support provided by Fivetran has generally been good, with a response time and competence that I would rate as good.

Lead Data Engineer at Sensilab

Customer support from Fivetran is quite good; it's really nice and responsive.

For more quotes and insights, download the Fivetran report

Team Lead Data Engineer at Data Pilot

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

7.1

Fivetran scales well for various businesses, accommodating data needs but can be costly and complex for smaller enterprises.

Azure Data Factory is highly scalable.

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

Chief Analytics Officer at Idiro Analytics

I did not experience scalability issues.

SubrataDey

Principal Data Engineer at Oracle

Fivetran's scalability has been tested effectively, and it has been working well for our organization's growing data needs.

For more quotes and insights, download the Fivetran report

Team Lead Data Engineer at Data Pilot

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

8.0

Users generally express high satisfaction with Fivetran's stable reliability, despite occasional issues with API connections and custom setups.

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

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

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

They have 99.9% accuracy on the data load and they maintain transparency.

Vigneswar Jeyaraj

Manager at InfoCepts

In my experience, Fivetran is stable with very few instances of downtime or reliability issues.

For more quotes and insights, download the Fivetran report

Team Lead Data Engineer at Data Pilot

During the duration of the time that we used Fivetran, it was highly stable.

reviewer2396643

Founder at a marketing services firm with 1-10 employees

Room For Improvement

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

Fivetran needs improvements in connectors, real-time processing, user interface, pricing, support, documentation, and integration capabilities.

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.

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

Chief Analytics Officer at Idiro Analytics

From a cost perspective, if the number of connectors is lesser, then Fivetran is not the most cost-efficient option.

reviewer2396643

Founder at a marketing services firm with 1-10 employees

I want more flexibility during ingestion, specifically for transformations needed beforehand.

Team Lead Data Engineer at Data Pilot

Fivetran could improve by adapting more for technical users and by providing more options for such users.

For more quotes and insights, download the Fivetran report

Lead Data Engineer at Sensilab

Setup Cost

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

Fivetran's pricing is high, favoring larger enterprises with discounts available; smaller companies may find it prohibitive.

The pricing is cost-effective.

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

Chief Analytics Officer at Idiro Analytics

It is considered cost-effective.

Joy Maitra

Sr. Technical Architect at Hexaware Technologies Limited

Our current yearly contract for Fivetran is approximately $70,000.

For more quotes and insights, download the Fivetran report

Lead Data Engineer at Sensilab

Valuable Features

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

Fivetran is valued for seamless data replication, user-friendly interface, scalability, and minimal coding, enabling efficient data handling.

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

The most valuable feature of Fivetran is its built-in connectors for a wide range of data sources.

For more quotes and insights, download the Fivetran report

Lead Data Engineer at Sensilab

The real-time data replication is what I see best in the market where it reduces the overhead of customers needing to maintain the pipeline.

Vigneswar Jeyaraj

Manager at InfoCepts

The ability to seamlessly integrate with a large variety of data sources is valuable.

reviewer2396643

Founder at a marketing services firm with 1-10 employees

Categories and Ranking

Azure Data Factory

Ranking in Data Integration

5th

Average Rating

8.0

Reviews Sentiment

6.7

Number of Reviews

Ranking in other categories

Cloud Data Warehouse (7th)

Fivetran

Ranking in Data Integration

13th

Average Rating

8.2

Reviews Sentiment

6.8

Number of Reviews

Ranking in other categories

Data Replication (3rd), Cloud Data Integration (9th)

Mindshare comparison

As of September 2026, in the Data Integration category, the mindshare of Azure Data Factory is 2.2%, down from 5.5% compared to the previous year. The mindshare of Fivetran is 1.8%, down from 2.1% compared to the previous year. It is calculated based on PeerSpot user engagement data.

Data Integration Mindshare Distribution
Product	Mindshare (%)
Azure Data Factory	2.2%
Fivetran	1.8%
Other	96.0%

Data Integration

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.

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Has accelerated data integration workflows and supports seamless development of custom connectors

Team Lead Data Engineer at Data Pilot

I've worked extensively with Fivetran, mainly used for extraction purposes, and I've worked with the transformation element in it as well. Fivetran not only has built-in connectors but also provides SDK connectors, allowing us to develop our own connectors in an easy manner. I don't have to write raw Python scripts or dumping scripts; it offers straightforward examples and guidelines, making it much simpler to develop custom connectors inside Fivetran. We've been able to develop many custom connectors as well, which is unique and beneficial for having everything centralized instead of having those connectors located elsewhere. One of the best features by Fivetran is its clean, simple, and intuitive UI. It includes a transformation section where I can deploy my DBT queries and scripts. It also supplies good tracking capabilities for billing estimates and user permissions, allowing for customization to the desired level. The number of connectors it has remains a standout feature, and within connectors, the options available are very helpful. Although it sometimes appears static due to its built-in nature, it offers good flexibility for data transformation and caching, which I appreciate because it saves us extensive script-writing time.

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Top Industries

By visitors reading reviews

Financial Services Firm

11%

Manufacturing Company

Computer Software Company

Construction Company

Financial Services Firm

12%

Manufacturing Company

10%

Computer Software Company

Comms Service Provider

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	10
Midsize Enterprise	7
Large Enterprise	16

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's the deal with the HVR software acquisition?

As a user of HVR Software I followed this deal closely. Fivetran is apparently trying to establish more in its sector and by buying an already established data replication software, they become som...

Does HVR Software provide reliable insights?

I honestly can't think of another data replication software that can give you better statistics and insight than HVR Software. There's the feature for topology and statistics and both of them can ...

How much traffic can HVR Software handle?

As someone who works at a company where a high volume of information is replicated and has tried several data replication softwares, I can tell you that you're looking at the right one. HVR Softwar...

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Product Reports

Azure Data Factory

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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

Fivetran offers a seamless, scalable data integration platform with strong connectors and real-time synchronization. Tailored for managing ETL workflows and integrating with DBT, it appeals to organizations seeking efficient data management.

Fivetran distinguishes itself through its intuitive interface and extensive scalability, allowing businesses to manage entire ETL workflows seamlessly. Its robust connectors ensure smooth integration with multiple data sources, while transparent logging and minimal coding requirements enhance accessibility. With real-time data synchronization, organizations benefit from up-to-date insights for analytics and engineering purposes. While some users point out areas for improvement like better documentation and expanded integration options, Fivetran remains a cherished tool for centralizing data in data warehouses such as supporting change data capture, migrations, and synchronizations from systems like Salesforce, NetSuite, and Google Analytics. Operating within an ELT framework, it empowers businesses to streamline data processes without complex extraction logic.

What are the key features of Fivetran?

Ease of Use: Intuitive platform minimizing setup complexity
Scalability: Adapt to growing data needs efficiently
Powerful Connectors: Seamless integration with diverse data sources
Real-Time Synchronization: Instant data updates supporting timely insights
DBT Integration: Simplifies transformations within ETL workflows
Transparent Logging: Provides clear visibility into operations

Which benefits can users expect in reviews?

Cost-Effective Scalability: Manage increased data without significant financial impact
Minimal Coding: Reduces technical barriers enhancing accessibility
Comprehensive Data Management: Centralizes diverse data streams effectively
Timely Analytics: Real-time updates foster actionable insights
Streamlined Workflow Management: Efficiently handles complex ETL processes

In industry-specific implementation, Fivetran is integral for businesses requiring robust data integration to power analytics. Retailers utilize it to consolidate e-commerce data for sales insights, while finance firms rely on its capabilities to merge financial data for reporting. In the tech sector, it supports engineering teams by providing a reliable data pipeline that fuels app development and performance monitoring.

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

Autodesk, Condé Nast, JetBlue, Morgan Stanley, OpenAI, LVMH, Pfizer, Verizon, SpotifyNational Australia Bank, Saks, Cemex, Okta, Dropbox, Pitney Bowes, World Fuel Services,Lufthansa, AutoZone, ASICS, ASOS, Coupa, Databricks, Hermes, New Relic, Intercom,Canva, Honeywell, Square, DocuSign, Nandos, Oldcastle Infrastructure

Azure Data Factory vs. Fivetran