Azure Data Factory vs Oracle Big Data Appliance comparison

Why PeerSpot?

Microsoft and Oracle are both solutions in the Cloud Data Warehouse category. Additionally, 92% of Microsoft users are willing to recommend the solution, compared to 75% of Oracle users who would recommend it.

Azure Data Factory

Read 97 Azure Data Factory reviews

15,321 Views
2,758 Comparison Views

92% willing to recommend

Oracle Big Data Appliance

Read 6 Oracle Big Data Appliance reviews

1,847 Views
1,459 Comparison Views

75% willing to recommend

Azure Data Factory

Oracle Big Data Appliance

Comparison Buyer's Guide

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Executive Summary

We performed a comparison between Azure Data Factory and Oracle Big Data Appliance based on real PeerSpot user reviews.

Find out what your peers are saying about Snowflake Computing, Google, Databricks and others in Cloud Data Warehouse.

To learn more, read our detailed Cloud Data Warehouse Report (Updated: September 2026).

Buyer's Guide

Cloud Data Warehouse

September 2026

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Helped 915,341 peers since 2012

Review summaries and opinions

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

Categories and Ranking

Azure Data Factory

Average Rating

8.0

Reviews Sentiment

6.7

Number of Reviews

Ranking in other categories

Data Integration (6th), Cloud Data Warehouse (6th)

Oracle Big Data Appliance

Average Rating

8.0

Reviews Sentiment

6.8

Number of Reviews

Ranking in other categories

Data Warehouse (13th)

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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reviewer1031826

Analytics Lead at a tech vendor with 10,001+ employees

Platinum partnership leverages advanced storage and fosters seamless data integration

Areas of Oracle Big Data Appliance that can be improved include the pricing perspective because nowadays they have competition. We have so many technologies that have come to the market for less than even one-fourth or one-fifth of the Oracle price. For my side, the last time I worked with Oracle was in '21, '22. The price is a challenge that they have to look after. From the storage and data management perspective, I cannot recall anything that they have to improve, but they have to improve the visualization part significantly because they offer Oracle BI, which is an extremely not-matured application.

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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 think it makes it very easy to understand what data flow is and so on. You can leverage the user interface to do the different data flows, and it's great. I like it a lot."

"Data Factory's best feature is the ease of setting up pipelines for data and cloud integrations."

"This solution has provided us with an easier, and more efficient way to carry out data migration tasks."

"Azure Data Factory is great because it's a cloud service; you do not have to take care of the installation and configuration yourself."

"The solution has a good interface and the integration with GitHub is very useful."

"The solution includes a feature that increases the number of processors used which makes it very powerful and adds to the scalability."

"The overall performance is quite good."

"The data copy template is a valuable feature."

More Azure Data Factory pros

"Because Big Data Appliance allows me to have a single source of truth, it means I have clean data that can be monetized and leveraged to gain more insights with real-time reports from the dashboard."

"This is a comprehensive solution that is easy to deploy."

"Big Data responds to my needs."

"The best feature of Oracle Big Data Appliance, from a price perspective for the storage, is because they have technology called the ZFS technology; it offers huge storage with a decent price."

"The best thing about the product is that the end-user can build the reports by themselves without really knowing anything about databases."

"The most valuable feature is that it can be used in conjunction with Spark memory processing, and our processing time has gone to 20 minutes from what used to be two or three hours on the mainframe."

"We could work on large unstructured datasets from different parts of the world on Facebook and Twitter to get better insights."

Cons

"There should be a way that it can do switches, so if at any point in time I want to do some hybrid mode of making any data collections or ingestions, I can just click on a button."

"Some known bugs and issues with Azure Data Factory could be rectified."

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

"The solution should offer better integration with Azure machine learning. We should be able to embed the cognitive services from Microsoft, for example as a web API. It should allow us to embed Azure machine learning in a more user-friendly way."

"Azure Data Factory can improve the transformation features. You have to do a lot of transformation activities. This is something that is just not fully covered. Additionally, the integration could improve for other tools, such as Azure Data Catalog."

"Data Factory's cost is too high."

"Some of the optimization techniques are not scalable."

"To my mind, the solution needs to be more connectable to its own services."

More Azure Data Factory cons

"Areas of Oracle Big Data Appliance that can be improved include the pricing perspective because nowadays they have competition; we have so many technologies that have come to the market for less than even one-fourth or one-fifth of the Oracle price."

"It seems like the deployment of repositories has become more difficult in later versions of the product rather than easier."

"We need to display the results on our website. I think there is another product that joins with it to give you the possibility."

"From a technical perspective, Big Data Appliance could be improved with more innovation in the AI and machine-learning parts instead of relying on Cloudera."

"The product should be simplified for the average user."

"We had to pursue several performance tuning measures to bring up the system to scale."

Pricing and Cost Advice

"Pricing appears to be reasonable in my opinion."

"Data Factory is expensive."

"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."

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

"The licensing cost is included in the Synapse."

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

"The solution's pricing is competitive."

More Azure Data Factory pricing and cost advice

"Oracle's prices are too high compared to others in the market."

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Top Industries

By visitors reading reviews

Financial Services Firm

11%

Manufacturing Company

Computer Software Company

Construction Company

Financial Services Firm

20%

Manufacturing Company

13%

Comms Service Provider

Outsourcing 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	1
Midsize Enterprise	1
Large Enterprise	7

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 needs improvement with Oracle Big Data Appliance?

See all answers

What is your primary use case for Oracle Big Data Appliance?

The typical use case for Oracle Big Data Appliance, which my clients use, is usually that the customer who has an Oracle application uses it because they can leverage the storage part. I don't need...

See all answers

Comparisons

Snowflake vs Azure Data Factory

Compared 4% of the time

Databricks vs Azure Data Factory

Compared 4% of the time

Palantir Foundry vs Azure Data Factory

Compared 3% of the time

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

Compared 3% of the time

SnapLogic vs Azure Data Factory

Compared 3% of the time

More Azure Data Factory Competitors

SAP BW4HANA vs Oracle Big Data Appliance

Compared 13% of the time

Apache Hadoop vs Oracle Big Data Appliance

Compared 9% of the time

Oracle Exadata vs Oracle Big Data Appliance

Compared 8% of the time

IBM Integrated Analytics System vs Oracle Big Data Appliance

Compared 7% of the time

Snowflake vs Oracle Big Data Appliance

Compared 4% of the time

More Oracle Big Data Appliance Competitors

Product Reports

Buyer's Guide

Azure Data Factory

October 2026

Download Azure Data Factory product report

Buyer's Guide

Data Warehouse

September 2026

Download Oracle Big Data Appliance product report

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

Oracle Big Data Appliance offers a comprehensive platform integrating ZFS technology and supporting Spark, designed to boost performance with Hadoop distributions, ensuring data security and accessibility across multiple languages.

Oracle Big Data Appliance presents an adaptable solution facilitating data consolidation with robust storage technology, crucial for central data repositories. Its Spark in-memory processing significantly reduces time through seamless integration with Hadoop distributions like Hortonworks and Cloudera. Role-based security enhances organizational data access, while multi-language support meets diverse processing requirements. Although challenges exist in AI capabilities and visualization tool efficiency, the platform remains valuable for entity-wide deployment.

What key features does Oracle Big Data Appliance offer?

Drag-and-Drop Interface: Enables non-technical users to build reports effortlessly.
ZFS Technology: Provides cost-effective storage solutions.
Spark on YARN Support: Enhances Hadoop performance with faster processing.
Security Roles: Ensures data access alignment with user privileges.
Multi-Language Support: Assists in handling diverse language processing needs.

What benefits should users look for when evaluating Oracle Big Data Appliance?

Centralized Data Management: Avoids the need for additional data warehouses.
Regulatory Reporting Facilitation: Eases compliance processes in sectors like Medicare.
Role-Based Reporting: Empowers end-users to create reports based on specific needs.
Consultation Integrations: Supports seamless data management when coupled with external services.

Oracle Big Data Appliance is predominantly used in healthcare and financial services, where data consolidation and regulatory compliance are crucial. Entities leverage Oracle's storage capabilities to maintain centralized repositories, expediting regulatory reporting and claim management processes, particularly benefiting sectors like Medicare. Consulting services frequently integrate Oracle platforms to enhance data management efficiency, especially for organizations utilizing Oracle applications.

Oracle

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

Caixa Bank

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