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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
7th
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
18th
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 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 Kovair Data Lake is 0.6%, up from 0.2% 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

"High throughput and low latency. We start with data mashing on Hive and finally use this for KPI visualization."
"It's good for storing historical data and handling analytics on a huge amount of data."
"Since both Apache Hadoop and Amazon EC2 are elastic in nature, we can scale and expand on demand for a specific PoC, and scale down when it's done."
"Its flexibility in handling and storing large volumes of data is particularly beneficial, as is its resilience, which ensures data redundancy and fault tolerance."
"The platform's quick data processing capabilities have been instrumental in supporting our AI-driven projects."
"They have integrated other tools as well, like Power BI and Oracle BI, both on Azure, for reporting. Oracle BI is difficult to integrate."
"The most valuable features are the ability to process the machine data at a high speed, and to add structure to our data so that we can generate relevant analytics."
"The tool's stability is good."
"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

"Improvements in security measures would be beneficial, given the large volumes of data handled."
"The load optimization capabilities of the product are an area of concern where improvements are required."
"The price could be better. I think we would use it more, but the company didn't want to pay for it. Hortonworks doesn't exist anymore, and Cloudera killed the free version of Hadoop."
"I would like to see more direct integration of visualization applications."
"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."
"In certain cases, the configurations for dealing with data skewness do not make any sense."
"It could be more user-friendly."
"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."
"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

"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."
"This is a low cost and powerful solution."
"The price of Apache Hadoop could be less expensive."
"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 product is open-source, but some associated licensing fees depend on the subscription level."
"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​."
"I rate the tool's pricing a five out of ten."
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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
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: April 2025.
846,617 professionals have used our research since 2012.