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Apache Hadoop vs IBM Db2 Warehouse on Cloud comparison

 

Comparison Buyer's Guide

Executive Summary

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
Average Rating
7.8
Reviews Sentiment
6.7
Number of Reviews
40
Ranking in other categories
Data Warehouse (7th)
IBM Db2 Warehouse on Cloud
Average Rating
7.6
Reviews Sentiment
6.3
Number of Reviews
7
Ranking in other categories
Cloud Data Warehouse (16th)
 

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.
FM
Enhancing analytics with seamless data dumping and reliable support
Our primary use case is data storage and analytics The organization has decided to purchase a full stack solution from IBM due to positive responses, which helped them upgrade from the previous version. The data dumping into the raw zone and the feature of BigQuery is quite attractive. There…

Quotes from Members

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

Pros

"Hadoop is a distributed file system, and it scales reasonably well provided you give it sufficient resources."
"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."
"Hadoop is designed to be scalable, so I don't think that it has limitations in regards to scalability."
"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 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."
"The most valuable features are powerful tools for ingestion, as data is in multiple systems."
"Hadoop can store any kind of data—structured, unstructured, and semi-structured—and presents it using the relational model through Hive."
"The best thing about this solution is that it is very powerful and very cheap."
"The performance is okay as long as the volume of queries is not too high."
"It is stable when there is support from IBM."
"The way that it scales will help a lot of customers that are stuck with Netezza boxes that can't grow any larger.​"
"It will be MPP, so performance should improve."
 

Cons

"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."
"Since it is an open-source product, there won't be much support."
"We would like to have more dynamics in merging this machine data with other internal data to make more meaning out of it."
"Real-time data processing is weak. This solution is very difficult to run and implement."
"It needs better user interface (UI) functionalities."
"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."
"In the next release, I would like to see Hive more responsive for smaller queries and to reduce the latency."
"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."
"Tech support for dashDB is awful. We usually have tickets open for three to four weeks."
"Containers get corrupted very easily. Restoring them using GPFS can result in a lot of issues."
"Ultimately, the product itself has challenges and we are not currently satisfied with the support, either."
"There are some limitations in adding data files to table spaces, and improvements are needed for regional support."
"Right now, we are implementing on ESX VMware 6.0. Support for this platform is poor. Also, one of the backup/recovery options is broken and IBM is not addressing the issue."
 

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."
"​There are no licensing costs involved, hence money is saved on the software infrastructure​."
"This is a low cost and powerful solution."
"The price of Apache Hadoop could be less expensive."
"The product is open-source, but some associated licensing fees depend on the subscription level."
"We just use the free version."
"If your going to go with warehouse DB/dashDB, use the cloud or Sailfish version."
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Top Industries

By visitors reading reviews
Financial Services Firm
34%
Computer Software Company
12%
University
5%
Energy/Utilities Company
5%
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...
What advice do you have for others considering IBM Db2 Warehouse on Cloud?
Organizations of all sizes, especially those who are in need of powerful and elastic cloud data warehouse solutions that can help administrators maximize the efficiency of their data-based operatio...
What needs improvement with IBM Db2 Warehouse on Cloud?
There are some limitations in adding data files to table spaces, and improvements are needed for regional support.
What is your primary use case for IBM Db2 Warehouse on Cloud?
Our primary use case is data storage and analytics.
 

Also Known As

No data available
IBM dashDB
 

Overview

 

Sample Customers

Amazon, Adobe, eBay, Facebook, Google, Hulu, IBM, LinkedIn, Microsoft, Spotify, AOL, Twitter, University of Maryland, Yahoo!, Cornell University Web Lab
Copenhagen Business School, BPM Northwest, GameStop
Find out what your peers are saying about Apache Hadoop vs. IBM Db2 Warehouse on Cloud and other solutions. Updated: May 2025.
858,649 professionals have used our research since 2012.