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Apache Hadoop vs Dremio 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)
Dremio
Average Rating
8.6
Reviews Sentiment
7.1
Number of Reviews
8
Ranking in other categories
Cloud Data Warehouse (9th), Data Science Platforms (9th)
 

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.
KamleshPant - PeerSpot reviewer
Solution offers quick data connection with an edge in computation
It's almost similar, yet it's better than Starburst in spinning up or connecting to the new source since it's on SaaS. It is a similar experience between the based application and cloud-based application. You just get the source, connect the data, get visualization, get connected, and do whatever you want. They say data reflection is one way where they do the caching and all that. Starburst also does the caching. In Starburst, you have a data product. Here, the data product comes from a reflection perspective. The y are working on a columnar memory map, columnar computation. That will have some edge in computation.

Quotes from Members

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

Pros

"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."
"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."
"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."
"Hadoop is a distributed file system, and it scales reasonably well provided you give it sufficient resources."
"Hadoop File System is compatible with almost all the query engines."
"The tool's stability is good."
"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."
"Two valuable features are its scalability and parallel processing. There are jobs that cannot be done unless you have massively parallel processing."
"We primarily use Dremio to create a data framework and a data queue."
"Everyone uses Dremio in my company; some use it only for the analytics function."
"The most valuable feature of Dremio is it can sit on top of any other data storage, such as Amazon S3, Azure Data Factory, SGFS, or Hive. The memory competition is good. If you are running any kind of materialized view, you'd be running in memory."
"Dremio is very easy to use for building queries."
"Dremio gives you the ability to create services which do not require additional resources and sterilization."
"Overall, you can rate it as eight out of ten."
"It's almost similar, yet it's better than Starburst in spinning up or connecting to the new source since it's on SaaS."
"Dremio allows querying the files I have on my block storage or object storage."
 

Cons

"Real-time data processing is weak. This solution is very difficult to run and implement."
"In the next release, I would like to see Hive more responsive for smaller queries and to reduce the latency."
"The stability of the solution needs improvement."
"Based on our needs, we would like to see a tool for data visualization and enhanced Ambari for management, plus a pre-built IoT hub/model. These would reduce our efforts and the time needed to prove to a customer that this will help them."
"I would like to see more direct integration of visualization applications."
"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."
"The product's availability of comprehensive training materials could be improved for faster onboarding and skill development among team members."
"We would like to have more dynamics in merging this machine data with other internal data to make more meaning out of it."
"Dremio takes a long time to execute large queries or the executing of correlated queries or nested queries. Additionally, the solution could improve if we could read data from the streaming pipelines or if it allowed us to create the ETL pipeline directly on top of it, similar to Snowflake."
"I cannot use the recursive common table expression (CTE) in Dremio because the support page says it's currently unsupported."
"They need to have multiple connectors."
"It shows errors sometimes."
"Dremio doesn't support the Delta connector. Dremio writes the IT support for Delta, but the support isn't great. There is definitely room for improvement."
"They have an automated tool for building SQL queries, so you don't need to know SQL. That interface works, but it could be more efficient in terms of the SQL generated from those things. It's going through some growing pains. There is so much value in tools like these for people with no SQL experience. Over time, Dermio will make these capabilities more accessible to users who aren't database people."
"We've faced a challenge with integrating Dremio and Databricks, specifically regarding authentication. It is not shaking hands very easily."
"There are performance issues at times due to our limited experience with Dremio, and the fact that we are running it on single nodes using a community version."
 

Pricing and Cost Advice

"The price of Apache Hadoop could be less expensive."
"​There are no licensing costs involved, hence money is saved on the software infrastructure​."
"The price could be better. Hortonworks no longer exists, and Cloudera killed the free version of Hadoop."
"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 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."
"It's reasonable, but there's room for improvement in cost-effectiveness."
"Right now the cluster costs approximately $200,000 per month and is based on the volume of data we have."
"Dremio is less costly competitively to Snowflake or any other tool."
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Top Industries

By visitors reading reviews
Financial Services Firm
33%
Computer Software Company
11%
University
7%
Energy/Utilities Company
6%
Financial Services Firm
32%
Computer Software Company
10%
Manufacturing Company
7%
Healthcare Company
4%
 

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 do you like most about Dremio?
Dremio allows querying the files I have on my block storage or object storage.
What is your experience regarding pricing and costs for Dremio?
The licensing is very expensive. We need a license to scale as we are currently using the community version.
What needs improvement with Dremio?
They need to have multiple connectors. Starburst is rich in connectors, however, they are lacking Salesforce connectivity as of today. They don't have Salesforce connectivity. However, Starburst do...
 

Comparisons

 

Overview

 

Sample Customers

Amazon, Adobe, eBay, Facebook, Google, Hulu, IBM, LinkedIn, Microsoft, Spotify, AOL, Twitter, University of Maryland, Yahoo!, Cornell University Web Lab
UBS, TransUnion, Quantium, Daimler, OVH
Find out what your peers are saying about Apache Hadoop vs. Dremio and other solutions. Updated: March 2025.
847,862 professionals have used our research since 2012.