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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:
 

ROI

Sentiment score
6.5
Apache Hadoop offers cost-effective storage and processing, with varying returns based on analytics sophistication and workload optimization.
No sentiment score available
 

Customer Service

Sentiment score
6.5
Apache Hadoop's support varies, with high satisfaction from vendor packages, responsive teams, and helpful documentation and community.
Sentiment score
6.7
Oracle Big Data Appliance's customer service is rated 6/10, with many relying on online resources for self-sufficient solutions.
 

Scalability Issues

Sentiment score
7.6
Apache Hadoop offers scalable data management for large-scale deployments, efficiently supports diverse users and adapts across industries.
Sentiment score
7.9
Oracle Big Data Appliance is praised for its scalability, effectively handling growing data volumes, though some suggest further Essbase testing.
 

Stability Issues

Sentiment score
7.4
Apache Hadoop is stable, especially newer versions, with occasional issues in setup, memory, and online data ingestion.
Sentiment score
8.1
Oracle Big Data Appliance is praised for its stability, exhibiting improved performance and reliability after Oracle ACS tuning.
 

Room For Improvement

Apache Hadoop requires enhanced compatibility, improved usability, real-time processing, better security, modern interfaces, and cost-effective solutions to boost adoption.
Oracle Big Data Appliance needs improved data visualization, ease of use, and focus on native AI innovations rather than Cloudera.
 

Setup Cost

Apache Hadoop is cost-effective for large-scale deployments, but smaller enterprises face higher expenses despite potential cloud cost savings.
 

Valuable Features

Apache Hadoop offers cost-efficient, scalable data processing with HDFS, supporting large datasets and seamless integration with tools like Spark.
Oracle Big Data Appliance enhances data processing and security with Spark, supporting Hadoop, and featuring an intuitive drag-and-drop interface.
 

Categories and Ranking

Apache Hadoop
Ranking in Data Warehouse
6th
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 December 2024, in the Data Warehouse category, the mindshare of Apache Hadoop is 5.2%, down from 6.2% compared to the previous year. The mindshare of Oracle Big Data Appliance is 0.9%, down from 1.9% 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.
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Top Industries

By visitors reading reviews
Financial Services Firm
34%
Computer Software Company
10%
University
7%
Energy/Utilities Company
6%
Financial Services Firm
27%
Computer Software Company
11%
University
11%
Government
10%
 

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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Overview

 

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: November 2024.
824,053 professionals have used our research since 2012.