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Amazon EMR vs Dremio 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

Amazon EMR
Ranking in Cloud Data Warehouse
12th
Average Rating
7.8
Reviews Sentiment
7.2
Number of Reviews
23
Ranking in other categories
Hadoop (3rd)
Dremio
Ranking in Cloud Data Warehouse
9th
Average Rating
8.6
Reviews Sentiment
7.1
Number of Reviews
8
Ranking in other categories
Data Science Platforms (9th)
 

Mindshare comparison

As of May 2025, in the Cloud Data Warehouse category, the mindshare of Amazon EMR is 3.3%, down from 3.5% compared to the previous year. The mindshare of Dremio is 11.0%, up from 5.3% compared to the previous year. It is calculated based on PeerSpot user engagement data.
Cloud Data Warehouse
 

Featured Reviews

Prashant  Singh - PeerSpot reviewer
Seamless data integration enhances reporting efficiency and an easy setup
Amazon EMR has multiple connectors that can connect to various data sources. The service charges are based on processing only, depending on the resources used, which can help save money. It is easy to integrate with other services for storage, allowing data to be shifted to cheaper storage based on usage.
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

"Amazon EMR is a good solution that can be used to manage big data."
"In Amazon EMR it is easy to rebuild anything, easy to upgrade and has good fault tolerance."
"The solution is pretty simple to set up."
"The initial setup is straightforward."
"The project management is very streamlined."
"The solution helps us manage huge volumes of data."
"We are using applications, such as Splunk, Livy, Hadoop, and Spark. We are using all of these applications in Amazon EMR and they're helping us a lot."
"One of the valuable features about this solution is that it's managed services, so it's pretty stable, and scalable as much as you wish. It has all the necessary distributions. With some additional work, it's also possible to change to a Spark version with the latest version of EMR. It also has Hudi, so we are leveraging Apache Hudi on EMR for change data capture, so then it comes out-of-the-box in EMR."
"Dremio enables you to manage changes more effectively than any other data warehouse platform. There are two things that come into play. One is data lineage. If you are looking at data in Dremio, you may want to know the source and what happened to it along the way or how it may have been transformed in the data pipeline to get to the point where you're consuming it."
"Dremio gives you the ability to create services which do not require additional resources and sterilization."
"Everyone uses Dremio in my company; some use it only for the analytics function."
"We primarily use Dremio to create a data framework and a data queue."
"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."
"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."
 

Cons

"There is room for improvement in pricing."
"Spark jobs take longer on Amazon EMR compared to previous experiences."
"The legacy versions of the solution are not supported in the new versions."
"The most complicated thing is configuring to the cluster and ensure it's running correctly."
"The solution can become expensive if you are not careful."
"As people are shifting from legacy solutions to other technologies, Amazon EMR needs to add more features that give more flexibility in managing user data."
"Modules and strategies should be better handled and notified early in advance."
"There is room for improvement with respect to retries, handling the volume of data on S3 buckets, cluster provisioning, scaling, termination, security, and integration between services like S3, Glue, Lake Formation, and DynamoDB."
"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."
"It shows errors sometimes."
"They need to have multiple connectors. Starburst is rich in connectors, however, they are lacking Salesforce connectivity as of today."
"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."
"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."
"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 need to have multiple connectors."
 

Pricing and Cost Advice

"I rate the tool's pricing a five out of ten. It can be expensive since it's a managed service, and if you are not careful, you can run into unexpected charges. You can make a mistake that costs you tens of thousands of dollars. That's happened to us twice, so I'm sensitive to it. We're still trying to work on that. Our smallest client probably spends a hundred thousand dollars yearly on licensing, while our largest is well over a million."
"There is a small fee for the EMR system, but major cost components are the underlying infrastructure resources which we actually use."
"There is no need to pay extra for third-party software."
"The product is not cheap, but it is not expensive."
"You don't need to pay for licensing on a yearly or monthly basis, you only pay for what you use, in terms of underlying instances."
"Amazon EMR is not very expensive."
"Amazon EMR's price is reasonable."
"The price of the solution is expensive."
"Dremio is less costly competitively to Snowflake or any other tool."
"Right now the cluster costs approximately $200,000 per month and is based on the volume of data we have."
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Top Industries

By visitors reading reviews
Financial Services Firm
26%
Computer Software Company
14%
Educational Organization
9%
Manufacturing Company
8%
Financial Services Firm
31%
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 Amazon EMR?
Amazon EMR is a good solution that can be used to manage big data.
What is your experience regarding pricing and costs for Amazon EMR?
Compared to others, Amazon seems efficient and is considered good for Big Data workloads. Costs are involved based on cluster resources, data volumes, EC2 ( /products/amazon-ec2-reviews ) instances...
What needs improvement with Amazon EMR?
There is room for improvement with respect to retries, handling the volume of data on S3 ( /products/amazon-s3-reviews ) buckets, cluster provisioning, scaling, termination, security, and integrati...
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

 

Also Known As

Amazon Elastic MapReduce
No data available
 

Overview

 

Sample Customers

Yelp
UBS, TransUnion, Quantium, Daimler, OVH
Find out what your peers are saying about Amazon EMR vs. Dremio and other solutions. Updated: April 2025.
850,028 professionals have used our research since 2012.