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Apache Hadoop vs Infobright DB 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
7th
Average Rating
7.8
Reviews Sentiment
6.7
Number of Reviews
40
Ranking in other categories
No ranking in other categories
Infobright DB
Ranking in Data Warehouse
27th
Average Rating
7.6
Reviews Sentiment
6.3
Number of Reviews
10
Ranking in other categories
Relational Databases Tools (37th)
 

Mindshare comparison

As of May 2025, in the Data Warehouse category, the mindshare of Apache Hadoop is 5.1%, down from 5.6% compared to the previous year. The mindshare of Infobright DB is 0.5%, up from 0.1% 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.
SD
If you need a real big data solution, look for a distributed solution that actually has a proven track record.
This version of Infobright has zero support for distributed scalability. The internal smart grid employed for each table has a major flaw in that the data size cannot be expunged until 2GB of data is reached at the column-level. This is a major flaw, making usage in a big-data scenario impossible. This means that you can delete as many records from a database table as you want. However, unless the 2GB aggregate size threshold was reached for some of the columns in the table, no reduction in disk space usage will occur. Only the data from the columns that reached 2GB will actually decrease. Other columns below 2GB in size do not leave the disk. I spent countless hours trying to find some workaround for this. I have nightmares of my e-mail inbox full of unsolvable questions about data size reduction from our field engineers.

Quotes from Members

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

Pros

"It's open-source, so it's very cost-effective."
"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."
"The platform's quick data processing capabilities have been instrumental in supporting our AI-driven projects."
"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."
"I liked that Apache Hadoop was powerful, had a lot of tools, and the fact that it was free and community-developed."
"One valuable feature is that we can download data."
"The most valuable feature is the database."
"It is a reliable product."
"It has very amazing smart grid query feature for very fast aggregate queries across millions of rows"
 

Cons

"Hadoop's security could be better."
"There is a lack of virtualization and presentation layers, so you can't take it and implement it like a radio solution."
"The stability of the solution needs improvement."
"Real-time data processing is weak. This solution is very difficult to run and implement."
"The integration with Apache Hadoop with lots of different techniques within your business can be a challenge."
"What could be improved in Apache Hadoop is its user-friendliness. It's not that user-friendly, but maybe it's because I'm new to it. Sometimes it feels so tough to use, but it could be because of two aspects: one is my incompetency, for example, I don't know about all the features of Apache Hadoop, or maybe it's because of the limitations of the platform. For example, my team is maintaining the business glossary in Apache Atlas, but if you want to change any settings at the GUI level, an advanced level of coding or programming needs to be done in the back end, so it's not user-friendly."
"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."
"Only the data from the columns that reached 2GB will actually decrease. Other columns below 2GB in size do not leave the disk."
 

Pricing and Cost Advice

"It's reasonable, but there's room for improvement in cost-effectiveness."
"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."
"​There are no licensing costs involved, hence money is saved on the software infrastructure​."
"The product is open-source, but some associated licensing fees depend on the subscription level."
"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."
"The price of Apache Hadoop could be less expensive."
"The price could be better. Hortonworks no longer exists, and Cloudera killed the free version of Hadoop."
"We just use the free version."
"Our pricing was based on server instances and it was actually very cheap compared to Oracle. I guess you get what you pay for."
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Top Industries

By visitors reading reviews
Financial Services Firm
33%
Computer Software Company
11%
University
7%
Energy/Utilities Company
6%
No data available
 

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?
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...
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Comparisons

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Also Known As

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Infobright
 

Overview

 

Sample Customers

Amazon, Adobe, eBay, Facebook, Google, Hulu, IBM, LinkedIn, Microsoft, Spotify, AOL, Twitter, University of Maryland, Yahoo!, Cornell University Web Lab
REZ-1, SonicWALL, IntegriChain, Fuseforward International Inc., Polystar, Live Rail, Mavenir Systems, JDSU Partners, Bango
Find out what your peers are saying about Apache Hadoop vs. Infobright DB and other solutions. Updated: April 2025.
850,028 professionals have used our research since 2012.