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: December 2024).

Azure Data Factory vs. Fivetran

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Categories and Ranking

Azure Data Factory

Ranking in Data Integration

1st

Average Rating

8.0

Reviews Sentiment

6.9

Number of Reviews

Ranking in other categories

Cloud Data Warehouse (3rd)

Fivetran

Ranking in Data Integration

13th

Average Rating

8.0

Reviews Sentiment

6.9

Number of Reviews

Ranking in other categories

Data Replication (3rd), Cloud Data Integration (6th)

Mindshare comparison

As of December 2024, in the Data Integration category, the mindshare of Azure Data Factory is 11.0%, down from 13.3% compared to the previous year. The mindshare of Fivetran is 2.2%, up from 1.9% compared to the previous year. It is calculated based on PeerSpot user engagement data.

Data Integration

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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Erik Jones

Head of BI and Analytics at HyperScience

Solution reduces time-to-value; high ROI

Fivetran has room for improvement in data pipeline observability. The Fivetran logs are fairly basic, compared to, for example, the insight Fivetran gives into helping users understanding the performance of data pipelines. So I think their observability into the pipeline itself could be improved. In addition, Fivetran is in the very early stages of allowing other companies to access its metadata API, but that's something that could use improvement, and I know that they're working on right now. We use a separate tool for "reverse ETL", which is the opposite of what Fivetran does; it pushes data from your data warehouse back out to business applications. If Fivetran pulls data from those same applications, they should also enable users to push it back. I would love to do both ETL and reverse ETL in the same tool. It would be nice if Fivetran offered both their regular offering plus the reverse ETL option as well.

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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

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

"The data mapping and the ability to systematically derive data are nice features. It worked really well for the solution we had. It is visual, and it did the transformation as we wanted."

"When it comes to our business requirements, this solution has worked well for us. However, we have not stretched it to the limit."

"Data Flow and Databricks are going to be extremely valuable services, allowing data solutions to scale as the business grows and new data sources are added."

"The feature I found most helpful in Azure Data Factory is the pipeline feature, including being able to connect to different sources. Azure Data Factory also has built-in security, which is another valuable feature."

"Allows more data between on-premises and cloud solutions"

"The most valuable features of the solution are its ease of use and the readily available adapters for connecting with various sources."

"The scalability of the product is impressive."

More Azure Data Factory pros

"Fivetran can perform data migration incredibly fast, depending on the source and target."

"The solution is stable. We've never faced any stability issues."

"The most valuable feature of Fivetran is that it only synchronizes what needs to be synchronized."

"The product is very easy to use and very easy to configure."

"The product has some seamless connectors, which are readily available."

"For us, Fivetran has been able to scale both in terms of the data we bring into our warehouse and the amount of data that we use as well."

"Fivetran's most valuable feature is replication."

"You can manage all of your connectors individually, which gives you a very good ability to trace which one of your ETL processes is running and when."

More Fivetran pros

Cons

"They require more detailed error reporting, data normalization tools, easier connectivity to other services, more data services, and greater compatibility with other commonly used schemas."

"Data Factory could be improved in terms of data transformations by adding more metadata extractions."

"Snowflake connectivity was recently added and if the vendor provided some videos on how to create data then that would be helpful."

"Customer service is not satisfactory. Third-party personnel handle support and rely on a knowledge repository."

"The initial setup is not very straightforward."

"The speed and performance need to be improved."

"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."

"We have experienced some issues with the integration. This is an area that needs improvement."

More Azure Data Factory cons

"Fivetran could improve in the area of customization, especially in how they socialize their tools."

"Fivetran would be improved by adding the ability to integrate the data from third-party APIs."

"The environment must be more development-friendly."

"More connectors are needed for exotic, popular, and rising star portals."

"It should have a few more monitoring functionalities."

"The documentation is decent, but it's hard to find information online about Fivetran. For example, if you try to search for an error code, you won't find much information about it in forums."

"Fivetran is very expensive for data sources with a lot of rows, such as email data. I would like to see cheaper pricing for data sources like that."

"Fivetran should add more connectors because its competitors, like Airbyte, have more connectors."

More Fivetran cons

Pricing and Cost Advice

"The price is fair."

"The licensing cost is included in the Synapse."

"There's no licensing for Azure Data Factory, they have a consumption payment model. How often you are running the service and how long that service takes to run. The price can be approximately $500 to $1,000 per month but depends on the scaling."

"Pricing appears to be reasonable in my opinion."

"I don't see a cost; it appears to be included in general support."

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

"I would not say that this product is overly expensive."

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

More Azure Data Factory pricing and cost advice

"The solution is affordable."

"I've heard that the license for HVR is a bit costly compared to its competitors, but since it's reliable and efficient, I think the customer shouldn't be bothered about the cost."

"In the first year, we were given a very good discount. It was approximately 20,000 Euros per year. In the third year, we purchased credit for two years and the price was 33,000 Euros per year."

"Fivetran is very expensive, and its database-driven pricing model is outdated."

"I would say they're a little bit on the expensive side, and their contract process is not particularly good, but there is a lot of potential flexibility."

"I rate the pricing a six out of ten."

"I can't give exact amounts because that's based on usage, but it's more expensive than some of its competitors."

"The pricing model is okay and mid to large companies will not have an issue with it."

More Fivetran 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

Educational Organization

29%

Computer Software Company

12%

Financial Services Firm

10%

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.

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...

Informatica PowerCenter vs Azure Data Factory

Comparisons

Compared 13% of the time

Snowflake vs Azure Data Factory

Compared 10% 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

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AWS Database Migration Service vs Fivetran

Compared 15% of the time

Oracle GoldenGate vs Fivetran

Compared 11% of the time

Qlik Replicate vs Fivetran

Compared 10% of the time

StreamSets vs Fivetran

Compared 6% of the time

Confluent vs Fivetran

Compared 6% of the time

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Product Reports

Azure Data Factory

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Microsoft

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.

Fivetran is a data integration and migration solution that centralizes data from various sources into a data warehouse (such as Snowflake or BigQuery) for analytics. Its most valuable features include replication and managed pipelines, integration with DBT for data transformation, and many source connections.

Fivetran is easy to use, with fast data migration and an intuitive portal for easy setup and troubleshooting. It has helped organizations integrate and manage data, saving time and resources.

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

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Azure Data Factory vs. Fivetran