Apache Hadoop vs Oracle Big Data Appliance comparison

Apache and Oracle are both solutions in the Data Warehouse category. Apache is ranked #7 with an average rating of 8.2, while Oracle is ranked #14 with an average rating of 8.0. Apache holds a 3.7% mindshare in Data Warehouse, compared to Oracle’s 2.5% mindshare. Additionally, 89% of Apache users are willing to recommend the solution, compared to 75% of Oracle users who would recommend it.

Apache Hadoop

Read 41 Apache Hadoop reviews

2,310 Views
1,409 Comparison Views

89% willing to recommend

Oracle Big Data Appliance

Read 6 Oracle Big Data Appliance reviews

793 Views
587 Comparison Views

75% willing to recommend

Apache Hadoop

Oracle Big Data Appliance

Comparison Buyer's Guide

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Executive SummaryUpdated on Dec 18, 2024

Apache Hadoop and Oracle Big Data Appliance are products competing in the big data processing category. While Oracle Big Data Appliance is perceived as superior due to its comprehensive features and Oracle integration, Hadoop is notable for its cost-effectiveness.

Features: Apache Hadoop offers scalability, wide community support, and extensive customization possibilities through its open-source framework. Oracle Big Data Appliance provides a tightly integrated solution with advanced security, high performance, and seamless Oracle ecosystem compatibility.

Room for Improvement: Apache Hadoop could improve in simplifying deployment, enhancing user-friendly interfaces, and providing more robust enterprise-level support. Oracle Big Data Appliance may benefit from reducing costs, offering flexible integration with non-Oracle products, and expanding support outside the Oracle ecosystem.

Ease of Deployment and Customer Service: Apache Hadoop deployment generally requires significant technical expertise and relies on community support. In contrast, Oracle Big Data Appliance offers a turnkey solution with simplified deployment and robust vendor-provided customer service.

Pricing and ROI: Apache Hadoop is open-source, often leading to lower setup costs and potentially higher ROI if companies invest in technical expertise. Oracle Big Data Appliance, with higher initial investment, provides value through comprehensive support and integration, offering ROI for organizations utilizing Oracle's suite.

To learn more, read our detailed Apache Hadoop vs. Oracle Big Data Appliance Report (Updated: March 2026).

Buyer's Guide

Apache Hadoop vs. Oracle Big Data Appliance

March 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:

Categories and Ranking

Apache Hadoop

Ranking in Data Warehouse

7th

Average Rating

8.0

Reviews Sentiment

6.6

Number of Reviews

Ranking in other categories

No ranking in other categories

Oracle Big Data Appliance

Ranking in Data Warehouse

14th

Average Rating

8.0

Reviews Sentiment

6.8

Number of Reviews

Ranking in other categories

No ranking in other categories

Mindshare comparison

As of March 2026, in the Data Warehouse category, the mindshare of Apache Hadoop is 3.7%, down from 4.3% compared to the previous year. The mindshare of Oracle Big Data Appliance is 2.5%, up from 0.9% compared to the previous year. It is calculated based on PeerSpot user engagement data.

Data Warehouse Mindshare Distribution
Product	Mindshare (%)
Apache Hadoop	3.7%
Oracle Big Data Appliance	2.5%
Other	93.8%

Data Warehouse

Featured Reviews

Nick Rapoport

Financial Advisor at a financial services firm with 10,001+ employees

Reliable performance maintained but requires ongoing management and support

Hadoop was used for years, but there were problems since the people who originally set it up left the firm. The group that owned it later didn't have the technical resources to properly maintain it. Although there was nothing wrong with Hadoop itself, issues arose without proper management and upgrades.

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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

"The performance is pretty good."

"The most important feature is its ability to handle large volumes. Some of our customers have really large volumes, and it is capable of handling their data in terms of the core volume and daily incremental volume. So, its processing power and speed are most valuable."

"The most valuable features are powerful tools for ingestion, as data is in multiple systems."

"The ability to add multiple nodes without any restriction is the solution's most valuable aspect."

"Most valuable features are HDFS and Kafka: Ingestion of huge volumes and variety of unstructured/semi-structured data is feasible, and it helps us to quickly onboard a new Big Data analytics prospect."

"As compared to Hive on MapReduce, Impala on MPP returns results of SQL queries in a fairly short amount of time, and is relatively fast when reading data into other platforms like R."

"The solution is easy to expand. We haven't seen any issues with it in that sense. We've added 10 servers, and we've added two nodes. We've been expanding since we started using it since we started out so small. Companies that need to scale shouldn't have a problem doing so."

"Apache Hadoop can manage large amounts and volumes of data with relative ease, which is a feature that is beneficial."

More Apache Hadoop pros

"Big Data responds to my needs."

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

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

"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."

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

"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."

Cons

"We would like to have more dynamics in merging this machine data with other internal data to make more meaning out of it."

"The solution is very expensive."

"The solution is not easy to use. The solution should be easy to use and suitable for almost any case connected with the use of big data or working with large amounts of data."

"In certain cases, the configurations for dealing with data skewness do not make any sense."

"Based on our needs, we would like to see a tool for data visualization and enhanced Ambari for management, plus a pre-built IoT hub/model. These would reduce our efforts and the time needed to prove to a customer that this will help them."

"The main thing is the lack of community support. If you want to implement a new API or create a new file system, you won't find easy support."

"The load optimization capabilities of the product are an area of concern where improvements are required."

"The integration with Apache Hadoop with lots of different techniques within your business can be a challenge."

More Apache Hadoop cons

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

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

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

"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."

Pricing and Cost Advice

"For any big enterprise the costs can be handled, and it is suitable for big enterprises because the scale of data is large. For medium and small enterprises, the tool is on the high-price side."

"Do take into consider that data storage and compute capacity scale differently and hence purchasing a "boxed" / 'all-in-one" solution (software and hardware) might not be the best idea."

"It's reasonable, but there's room for improvement in cost-effectiveness."

"The price could be better. Hortonworks no longer exists, and Cloudera killed the free version of Hadoop."

"We don't directly pay for it. Our clients pay for it, and they usually don't complain about the price. So, it is probably acceptable."

"We just use the free version."

"The price of Apache Hadoop could be less expensive."

"The product is open-source, but some associated licensing fees depend on the subscription level."

More Apache Hadoop 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

31%

Computer Software Company

Government

University

No data available

Company Size

By reviewers

Large Enterprise

Midsize Enterprise

Small Business

By reviewers
Company Size	Count
Small Business	14
Midsize Enterprise	8
Large Enterprise	21

By reviewers
Company Size	Count
Small Business	1
Midsize Enterprise	1
Large Enterprise	6

Questions from the Community

What do you like most about Apache Hadoop?

It's primarily open source. You can handle huge data volumes and create your own views, workflows, and tables. I can also use it for real-time data streaming.

See all answers

What is your experience regarding pricing and costs for Apache Hadoop?

The product is open-source, but some associated licensing fees depend on the subscription level. While it might be free for students, organizations typically need to pay for their subscriptions. Th...

See all answers

What needs improvement with Apache Hadoop?

The problem with Apache Hadoop arose when the guys that originally set it up left the firm, and the group that later owned it didn't have enough technical resources to properly maintain it. This wa...

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

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Compared 11% of the time

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Compared 10% of the time

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Compared 6% of the time

Teradata vs Oracle Big Data Appliance

Compared 6% of the time

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Compared 5% of the time

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Product Reports

Buyer's Guide

Apache Hadoop

March 2026

Download Apache Hadoop product report

Buyer's Guide

Data Warehouse

February 2026

Download Oracle Big Data Appliance product report

Overview

The Apache Hadoop project develops open-source software for reliable, scalable, distributed computing. The Apache Hadoop software library is a framework that allows for the distributed processing of large data sets across clusters of computers using simple programming models. It is designed to scale up from single servers to thousands of machines, each offering local computation and storage. Rather than rely on hardware to deliver high-availability, the library itself is designed to detect and handle failures at the application layer, so delivering a highly-available service on top of a cluster of computers, each of which may be prone to failures.

Apache

Oracle Big Data Appliance is a flexible, high-performance, secure platform for running diverse workloads on Hadoop and NoSQL systems. With Oracle Big Data SQL, Oracle Big Data Appliance extends Oracle’s industry-leading implementation of SQL to Hadoop and NoSQL systems. By combining the newest technologies from the Hadoop ecosystem and powerful Oracle SQL capabilities together on a single pre-configured platform, Oracle Big Data Appliance is uniquely able to support rapid development of new Big Data applications and tight integration with existing relational data.

For more information on Oracle Big Data Appliance, visit Oracle.com

Oracle

Sample Customers

Amazon, Adobe, eBay, Facebook, Google, Hulu, IBM, LinkedIn, Microsoft, Spotify, AOL, Twitter, University of Maryland, Yahoo!, Cornell University Web Lab

Caixa Bank

Buyer's Guide

Apache Hadoop vs. Oracle Big Data Appliance

March 2026

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