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Apache Hadoop vs Oracle Big Data Appliance comparison

 

Comparison Buyer's Guide

Executive SummaryUpdated on Dec 18, 2024

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
8th
Average Rating
7.8
Reviews Sentiment
6.8
Number of Reviews
39
Ranking in other categories
No ranking in other categories
Oracle Big Data Appliance
Ranking in Data Warehouse
19th
Average Rating
8.0
Reviews Sentiment
7.5
Number of Reviews
5
Ranking in other categories
No ranking in other categories
 

Mindshare comparison

As of March 2025, in the Data Warehouse category, the mindshare of Apache Hadoop is 5.1%, down from 5.8% compared to the previous year. The mindshare of Oracle Big Data Appliance is 1.0%, down from 1.5% compared to the previous year. It is calculated based on PeerSpot user engagement data.
Data Warehouse
 

Featured Reviews

Sushil Arya - PeerSpot reviewer
Provides ease of integration with the IT workflow of a business
When working with Kafka, I saw that the data came in an incremental order. The incremental data processing part is still not very effective in Apache Hadoop. If the data is already there, it can be processed very effectively, especially if the data is coming in every second. If you want to know the location of some data every second, then such data is not processed effectively in Apache Hadoop. I can say that one of the features where improvements are required revolves around the licensing cost of the tool. If the tool can build some licensing structures in a pay-per-use manner, organizations can get the look and feel of Apache Hadoop. Apache Hadoop can offer a licensing structure of the product that can be seen as similar to how AWS operates. Apache Hadoop can look into the capability of processing incremental data. The tool's setup process can be a scope of improvement. Also, it is not very simple because while doing the setup, we need to do all the server settings, including port listing and firewall configurations. If we look at other products on the market, then they can be made simpler. There are certain shortcomings when it comes to the product's technical support part, making it an area where improvements are required. The time frame for the resolution is an area that needs to be improved. The overall communication part of the technical support team also needs improvement.
Mohammed Hamad - PeerSpot reviewer
Provides clean, centralized data
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. Oracle could also improve Big Data Appliance by having one technology on their stack and working on it instead of continually changing the name or technologies or features. In addition, they could have a program to enable their partners to use this technology because right now, I have to have an expert to use the AI elements.

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 are powerful tools for ingestion, as data is in multiple systems."
"The platform's quick data processing capabilities have been instrumental in supporting our AI-driven projects."
"Hadoop is extensible — it's elastic."
"What I like about Apache Hadoop is that it's for big data, in particular big data analysis, and it's the easier solution. I like the data processing feature for AI/ML use cases the most because some solutions allow me to collect data from relational databases, while Hadoop provides me with more options for newer technologies."
"The performance is pretty good."
"Its integration is Hadoop's best feature because that allows us to support different tools in a big data platform."
"Since both Apache Hadoop and Amazon EC2 are elastic in nature, we can scale and expand on demand for a specific PoC, and scale down when it's done."
"Apache Hadoop is crucial in projects that save and retrieve data daily. Its valuable features are scalability and stability. It is easy to integrate with the existing infrastructure."
"The best thing about the product is that the end-user can build the reports by themselves without really knowing anything about databases."
"This is a comprehensive solution that is easy to deploy."
"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."
 

Cons

"It would be helpful to have more information on how to best apply this solution to smaller organizations, with less data, and grow the data lake."
"The load optimization capabilities of the product are an area of concern where improvements are required."
"The solution could use a better user interface. It needs a more effective GUI in order to create a better user environment."
"In the next release, I would like to see Hive more responsive for smaller queries and to reduce the latency."
"Improvements in security measures would be beneficial, given the large volumes of data handled."
"The solution needs a better tutorial. There are only documents available currently. There's a lot of YouTube videos available. However, in terms of learning, we didn't have great success trying to learn that way. There needs to be better self-paced learning."
"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."
"There is a lack of virtualization and presentation layers, so you can't take it and implement it like a radio solution."
"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."
"It seems like the deployment of repositories has become more difficult in later versions of the product rather than easier."
 

Pricing and Cost Advice

"The product is open-source, but some associated licensing fees depend on the subscription level."
"This is a low cost and powerful solution."
"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."
"If my company can use the cloud version of Apache Hadoop, particularly the cloud storage feature, it would be easier and would cost less because an on-premises deployment has a higher cost during storage, for example, though I don't know exactly how much Apache Hadoop costs."
"It's reasonable, but there's room for improvement in cost-effectiveness."
"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."
"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
34%
Computer Software Company
11%
University
7%
Energy/Utilities Company
6%
Financial Services Firm
30%
Computer Software Company
15%
Government
10%
University
9%
 

Company Size

By reviewers
Large Enterprise
Midsize Enterprise
Small Business
 

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.
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...
What needs improvement with Apache Hadoop?
Hadoop lacks OLAP capabilities. I recommend adding a Delta Lake feature to make the data compatible with ACID properties. Also, video and audio streaming import issues could be improved to ensure p...
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Sample Customers

Amazon, Adobe, eBay, Facebook, Google, Hulu, IBM, LinkedIn, Microsoft, Spotify, AOL, Twitter, University of Maryland, Yahoo!, Cornell University Web Lab
Caixa Bank
Find out what your peers are saying about Apache Hadoop vs. Oracle Big Data Appliance and other solutions. Updated: February 2025.
842,466 professionals have used our research since 2012.