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Amazon EC2 vs Apache Spark comparison

 

Comparison Buyer's Guide

Executive SummaryUpdated on May 21, 2025

Review summaries and opinions

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

ROI

Sentiment score
6.5
Amazon EC2 reduces long-term costs through scalability, efficient resource management, and decreased infrastructure expenses, enhancing innovation and agility.
Sentiment score
6.1
Apache Spark enhances machine learning, cutting operational costs by up to 50%, with efficiency reliant on resources and expertise.
I would say I have saved more than a week with Amazon EC2 compared to my previous on-premises setup.
Architect at a outsourcing company with 1,001-5,000 employees
 

Customer Service

Sentiment score
6.7
Amazon EC2 customer service satisfaction varies; premium support praised, free support criticized, and experiences differ based on needs.
Sentiment score
5.9
Apache Spark support feedback varies, with mixed reviews on community forums, vendor support, and documentation adequacy.
I have received support via newsgroups or guidance on specific discussions, which is what I would expect in an open-source situation.
Data Architect at Devtech
 

Scalability Issues

Sentiment score
7.6
Amazon EC2's scalability impresses users with autoscaling, resource flexibility, and efficient cost-performance optimization for diverse organizational needs.
Sentiment score
7.5
Apache Spark excels in scalability, efficiently handling large data workloads with ease, though it requires skilled infrastructure management.
 

Stability Issues

Sentiment score
8.1
Amazon EC2 is highly stable and reliable, with minor issues mitigated by best practices like multiple availability zones.
Sentiment score
7.4
Apache Spark is generally stable, trusted by companies; newer versions enhance reliability, though memory issues may arise without proper configuration.
Apache Spark resolves many problems in the MapReduce solution and Hadoop, such as the inability to run effective Python or machine learning algorithms.
Data Engineer at a tech company with 10,001+ employees
Without a doubt, we have had some crashes because each situation is different, and while the prototype in my environment is stable, we do not know everything at other customer sites.
Data Architect at Devtech
 

Room For Improvement

Amazon EC2 faces criticism for complexity, high costs, and limited integration, with calls for better automation and innovation.
Apache Spark requires improvements in scalability, usability, documentation, memory efficiency, real-time processing, and broader language support for better performance.
I have heard from multiple people that if you have an Amazon EC2 instance running and you stop it, the billing continues unless you terminate the Amazon EC2 instance.
Senior Software Engineer at a tech vendor with 1,001-5,000 employees
I think improvements can be made to Amazon EC2 by increasing the memory, offering more instance types, and including GPUs as mentioned in the keynote.
Architect at a outsourcing company with 1,001-5,000 employees
Various tools like Informatica, TIBCO, or Talend offer specific aspects, licensing can be costly;
Data Architect at Devtech
 

Setup Cost

Amazon EC2 pricing is seen as cost-effective but complex, urging simplification for easier cost management and estimation.
Apache Spark is cost-effective but may incur expenses from hardware, cloud resources, or commercial support, impacting deployment costs.
 

Valuable Features

Amazon EC2 offers scalability, flexibility, and cost-efficiency with strong security, making it ideal for diverse workloads and AWS integration.
Apache Spark offers fast in-memory processing, scalable analytics, MLlib for machine learning, SQL support, and seamless integration with languages.
With the cloud, deployment is easy, and within a minute, we can deploy the server and give it to the developers so they can work on it right away after deployment.
Architect at a outsourcing company with 1,001-5,000 employees
Amazon EC2 offers flexibility.
Senior Software Engineer at a tech vendor with 1,001-5,000 employees
Not all solutions can make this data fast enough to be used, except for solutions such as Apache Spark Structured Streaming.
Data Engineer at a tech company with 10,001+ employees
The solution is beneficial in that it provides a base-level long-held understanding of the framework that is not variant day by day, which is very helpful in my prototyping activity as an architect trying to assess Apache Spark, Great Expectations, and Vault-based solutions versus those proposed by clients like TIBCO or Informatica.
Data Architect at Devtech
 

Categories and Ranking

Amazon EC2
Ranking in Compute Service
5th
Average Rating
8.6
Reviews Sentiment
6.8
Number of Reviews
71
Ranking in other categories
No ranking in other categories
Apache Spark
Ranking in Compute Service
3rd
Average Rating
8.4
Reviews Sentiment
6.9
Number of Reviews
68
Ranking in other categories
Hadoop (1st), Java Frameworks (2nd)
 

Mindshare comparison

As of December 2025, in the Compute Service category, the mindshare of Amazon EC2 is 10.8%, up from 6.5% compared to the previous year. The mindshare of Apache Spark is 11.4%, up from 11.1% compared to the previous year. It is calculated based on PeerSpot user engagement data.
Compute Service Market Share Distribution
ProductMarket Share (%)
Apache Spark11.4%
Amazon EC210.8%
Other77.8%
Compute Service
 

Featured Reviews

BS
AWS Architect at Corvit Networks
Elasticity and auto scaling enhance performance and cost efficiency
Amazon EC2 features that I have found the most valuable and useful include elasticity and scalability, a variety of instance types, pay-as-you-go pricing, security, isolation, AMIs, integration with other services, Spot Instances, and high availability of reliability, user data, and EC2 metadata. These include Amazon EC2 images, image builder, and auto scaling as instance types, pricing models, and security with VPC, IAM roles, and security groups. The most beneficial features of Amazon EC2 for cloud operations are EC2 Auto Scaling with Elastic Load Balancing, which allows scale up and scale down, maintains high availability, and optimizes costs. Auto Scaling provides fault tolerance, performance optimization, and cost efficiency. A real-world benefit is that an instance automatically handles the load. When traffic drops, it reduces the number of instances. Other highly beneficial Amazon EC2 features include Spot Instances, multiple instance types, custom AMIs, VPC security groups, strong network and access security, and Elastic IPs, which are the static IPs for dynamic instances.
Devindra Weerasooriya - PeerSpot reviewer
Data Architect at Devtech
Provides a consistent framework for building data integration and access solutions with reliable performance
The in-memory computation feature is certainly helpful for my processing tasks. It is helpful because while using structures that could be held in memory rather than stored during the period of computation, I go for the in-memory option, though there are limitations related to holding it in memory that need to be addressed, but I have a preference for in-memory computation. The solution is beneficial in that it provides a base-level long-held understanding of the framework that is not variant day by day, which is very helpful in my prototyping activity as an architect trying to assess Apache Spark, Great Expectations, and Vault-based solutions versus those proposed by clients like TIBCO or Informatica.
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Top Industries

By visitors reading reviews
Computer Software Company
10%
Manufacturing Company
8%
Transportation Company
8%
Educational Organization
7%
Financial Services Firm
25%
Computer Software Company
11%
Manufacturing Company
7%
Comms Service Provider
6%
 

Company Size

By reviewers
Large Enterprise
Midsize Enterprise
Small Business
By reviewers
Company SizeCount
Small Business30
Midsize Enterprise13
Large Enterprise28
By reviewers
Company SizeCount
Small Business28
Midsize Enterprise15
Large Enterprise32
 

Questions from the Community

What do you like most about Amazon EC2?
The scalability and elasticity are helpful.
What is your experience regarding pricing and costs for Amazon EC2?
Advice on Setup Cost, Pricing, and Licensing for EC2: 1. Start Small & Use Free Tier if Possible For new users or small applications, the AWS Free Tier offers limited EC2 usage free for 12 mont...
What needs improvement with Amazon EC2?
I think improvements can be made to Amazon EC2 by increasing the memory, offering more instance types, and including GPUs as mentioned in the keynote. In the future, I think you could explore quant...
What do you like most about Apache Spark?
We use Spark to process data from different data sources.
What is your experience regarding pricing and costs for Apache Spark?
Apache Spark is open-source, so it doesn't incur any charges.
What needs improvement with Apache Spark?
Areas for improvement are obviously ease of use considerations, though there are limitations in doing that, so while various tools like Informatica, TIBCO, or Talend offer specific aspects, licensi...
 

Comparisons

 

Also Known As

Amazon Elastic Compute Cloud, EC2
No data available
 

Overview

 

Sample Customers

Netflix, Expedia, TimeInc., Novaris, airbnb, Lamborghini
NASA JPL, UC Berkeley AMPLab, Amazon, eBay, Yahoo!, UC Santa Cruz, TripAdvisor, Taboola, Agile Lab, Art.com, Baidu, Alibaba Taobao, EURECOM, Hitachi Solutions
Find out what your peers are saying about Amazon EC2 vs. Apache Spark and other solutions. Updated: December 2025.
879,259 professionals have used our research since 2012.