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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 April 2025, in the Data Warehouse category, the mindshare of Apache Hadoop is 5.0%, down from 5.7% 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

"I liked that Apache Hadoop was powerful, had a lot of tools, and the fact that it was free and community-developed."
"The most valuable feature is the database."
"I recommend it for the telecom sector. I know it well, and it's a good fit."
"High throughput and low latency. We start with data mashing on Hive and finally use this for KPI visualization."
"The best thing about this solution is that it is very powerful and very cheap."
"Hadoop is designed to be scalable, so I don't think that it has limitations in regards to scalability."
"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."
"Hadoop can store any kind of data—structured, unstructured, and semi-structured—and presents it using the relational model through Hive."
"It has very amazing smart grid query feature for very fast aggregate queries across millions of rows"
 

Cons

"There is a lack of virtualization and presentation layers, so you can't take it and implement it like a radio solution."
"The integration with Apache Hadoop with lots of different techniques within your business can be a challenge."
"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 solution could use a better user interface. It needs a more effective GUI in order to create a better user environment."
"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."
"The key shortcoming is its inability to handle queries when there is insufficient memory. This limitation can be bypassed by processing the data in chunks."
"I would like to see more direct integration of visualization applications."
"I mentioned it definitely, and this is probably the only feature we can improve a little bit because the terminal and coding screen on Hadoop is a little outdated, and it looks like the old C++ bio screen. If the UI and UX can be improved slightly, I believe it will go a long way toward increasing adoption and effectiveness."
"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

"This is a low cost and powerful solution."
"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."
"The product is open-source, but some associated licensing fees depend on the subscription level."
"​There are no licensing costs involved, hence money is saved on the software infrastructure​."
"The price of Apache Hadoop could be less expensive."
"We just use the free version."
"The price could be better. Hortonworks no longer exists, and Cloudera killed the free version of Hadoop."
"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."
"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
34%
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

No data available
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.
846,617 professionals have used our research since 2012.