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Apache Hadoop vs Kovair Data Lake 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
6.7
Number of Reviews
40
Ranking in other categories
No ranking in other categories
Kovair Data Lake
Ranking in Data Warehouse
19th
Average Rating
8.0
Reviews Sentiment
7.2
Number of Reviews
2
Ranking in other categories
No ranking in other categories
 

Mindshare comparison

As of August 2025, in the Data Warehouse category, the mindshare of Apache Hadoop is 4.8%, down from 4.9% compared to the previous year. The mindshare of Kovair Data Lake is 0.7%, up from 0.3% 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.
LuizKazan - PeerSpot reviewer
Ability to interact with teachers in real-time and manage lessons after class
The deployment process is very fast. We have prepared the product to be easily installed, and we have had successful cases where it could be implemented in less than a few weeks. Moreover, Around three or four people in a call center are involved in maintaining the solution. We have a project manager, a service manager, and at least two or three system analysts who handle the maintenance. If there are any issues, we can open a support ticket for them to address.

Quotes from Members

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

Pros

"Initially, with RDBMS alone, we had a lot of work and few servers running on-premise and on cloud for the PoC and incubation. With the use of Hadoop and ecosystem components and tools, and managing it in Amazon EC2, we have created a Big Data "lab" which helps us to centralize all our work and solutions into a single repository. This has cut down the time in terms of maintenance, development and, especially, data processing challenges."
"The ability to add multiple nodes without any restriction is the solution's most valuable aspect."
"The scalability of Apache Hadoop is very good."
"The tool's stability is good."
"Apache Hadoop can manage large amounts and volumes of data with relative ease, which is a feature that is beneficial."
"One valuable feature is that we can download data."
"Hadoop is a distributed file system, and it scales reasonably well provided you give it sufficient resources."
"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."
"The most valuable feature is the ability to interact with teachers in real-time and manage lessons after class."
"The tool's most valuable features for us are its combination of formatting, ETL, analytics, and storage capabilities."
 

Cons

"Hadoop's security could be better."
"The solution is very expensive."
"The upgrade path should be improved because it is not as easy as it should be."
"In certain cases, the configurations for dealing with data skewness do not make any sense."
"There is a lack of virtualization and presentation layers, so you can't take it and implement it like a radio solution."
"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."
"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."
"In the next release, I would like to see Hive more responsive for smaller queries and to reduce the latency."
"Maybe the chat conversation feature could be improved."
"The solution is expensive. For future releases, it would be beneficial if Kovair Data Lake could enhance its ETL and data capabilities."
 

Pricing and Cost Advice

"​There are no licensing costs involved, hence money is saved on the software infrastructure​."
"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."
"This is a low cost and powerful solution."
"The product is open-source, but some associated licensing fees depend on the subscription level."
"It's reasonable, but there's room for improvement in cost-effectiveness."
"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 price of Apache Hadoop could be less expensive."
"We just use the free version."
"I rate the tool's pricing a five out of ten."
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Top Industries

By visitors reading reviews
Financial Services Firm
35%
Computer Software Company
11%
University
6%
Energy/Utilities Company
5%
No data available
 

Company Size

By reviewers
Large Enterprise
Midsize Enterprise
Small Business
No data available
 

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 do you like most about Kovair Data Lake?
The tool's most valuable features for us are its combination of formatting, ETL, analytics, and storage capabilities.
What needs improvement with Kovair Data Lake?
The solution is expensive. For future releases, it would be beneficial if Kovair Data Lake could enhance its ETL and data capabilities.
What is your primary use case for Kovair Data Lake?
I primarily use Kovair Data Lake for data analytics use cases. This involves data cleansing and gaining business intelligence.
 

Comparisons

No data available
 

Overview

 

Sample Customers

Amazon, Adobe, eBay, Facebook, Google, Hulu, IBM, LinkedIn, Microsoft, Spotify, AOL, Twitter, University of Maryland, Yahoo!, Cornell University Web Lab
HSBC, NVIDIA, APPLIED MATERIALS, Allscripts, CISCO, Honeywell
Find out what your peers are saying about Apache Hadoop vs. Kovair Data Lake and other solutions. Updated: July 2025.
865,384 professionals have used our research since 2012.