Amazon EC2 vs Apache Spark comparison

Amazon Web Services (AWS) and Apache are both solutions in the Compute Service category. Amazon Web Services (AWS) is ranked #5 with an average rating of 8.8, while Apache is ranked #4 with an average rating of 8.6. Amazon Web Services (AWS) holds a 6.0% mindshare in CS, compared to Apache’s 11.3% mindshare. Additionally, 98% of Amazon Web Services (AWS) users are willing to recommend the solution, compared to 90% of Apache users who would recommend it.

Amazon EC2

Read 65 Amazon EC2 reviews

1,301 Views
879 Comparison Views

98% willing to recommend

Apache Spark

Read 65 Apache Spark reviews

1,646 Views
1,251 Comparison Views

90% willing to recommend

Amazon EC2

Apache Spark

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Executive Summary

We performed a comparison between Amazon EC2 and Apache Spark based on real PeerSpot user reviews.

Find out in this report how the two Compute Service solutions compare in terms of features, pricing, service and support, easy of deployment, and ROI.

To learn more, read our detailed Amazon EC2 vs. Apache Spark Report (Updated: March 2025).

Buyer's Guide

Amazon EC2 vs. Apache Spark

March 2025

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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 EC2

Ranking in Compute Service

5th

Average Rating

8.6

Reviews Sentiment

7.2

Number of Reviews

Ranking in other categories

No ranking in other categories

Apache Spark

Ranking in Compute Service

4th

Average Rating

8.4

Reviews Sentiment

7.7

Number of Reviews

Ranking in other categories

Hadoop (1st), Java Frameworks (2nd)

Mindshare comparison

As of March 2025, in the Compute Service category, the mindshare of Amazon EC2 is 6.0%, down from 7.1% compared to the previous year. The mindshare of Apache Spark is 11.3%, up from 9.2% compared to the previous year. It is calculated based on PeerSpot user engagement data.

Compute Service

Featured Reviews

KatlegoMabila

Senior AWS Account Manager at Silicon Overdrive

Offers customization and flexibility with great support

Scalability depends on whether the client wants to scale up or scale down. It decreases resources based on demand. The great aspect of scalability is the flexibility to allow business success to optimize resource solutions and cost efficiency. Another crucial aspect of scalability is auto-scaling. When you have the opportunity to auto-scale, it can't always be available for everything. If you have chosen to integrate with auto-scaling, it's marvellous and doesn't require additional effort. Auto-scaling gives you the edge by using the capacity you have efficiently, scaling up or down as needed. These flexibilities within the EC2 feature instances of AWS play a crucial role in helping me utilize AWS EC2 Intelligent efficiently.

Read full review

Ilya Afanasyev

Senior Software Development Engineer at Yahoo!

Reliable, able to expand, and handle large amounts of data well

We use batch processing. It works well with our formats and file versions. There's a lot of functionality. In our pipeline each hour, we make a copy of data from MongoDB, of the changes from MongoDB to some specific file. Each time pipeline copied all of the data, it would do it each time without changes to all of the tables. Tables have a lot of data, and in the last MongoDB version, there is a possibility to read only changed data. This reduced the cost and configuration of the cluster, and we saved about $150,000. The solution is scalable. It's a stable product.

Read full review

Quotes from Members

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

Pros

"What we have found most valuable is that we have not lost stability in the program."

"The scalability of the solution is fantastic. It's one of our favorite features."

"The product is easy and quick to set up."

"The most valuable features of Amazon EC2 are ease of use and the services offered."

"EC2 has helped us to deploy various Microsoft applications efficiently. It has also facilitated our workstation operations."

"The most valuable feature is autoscaling."

"I believe that cloud solutions are better than physical servers."

"One of the most valuable features of EC2 is its accessibility; I can easily access it through various tools like GIT and use it on mobile devices."

More Amazon EC2 pros

"The good performance. The nice graphical management console. The long list of ML algorithms."

"With Spark, we parallelize our operations, efficiently accessing both historical and real-time data."

"It is highly scalable, allowing you to efficiently work with extensive datasets that might be problematic to handle using traditional tools that are memory-constrained."

"The scalability has been the most valuable aspect of the solution."

"The product's initial setup phase was easy."

"I feel the streaming is its best feature."

"The product’s most valuable feature is the SQL tool. It enables us to create a database and publish it."

"With Hadoop-related technologies, we can distribute the workload with multiple commodity hardware."

More Apache Spark pros

Cons

"The tool’s stability could be better."

"This solution could be improved with better pricing. If you continue using this solution over a long period of time, your costs may accumulate."

"Built-in and/or integration with other services to proactively identify potential failures before they occur."

"Currently in the autoscaling process if we have multiple issues we are not able to connect some of the VPC through the SMS."

"Support doesn't share or give insights on OS-based issues. That needs to improve because if someone is buying an EC2 instance with the Windows server and SQL license, the client expects that there will be a minimum level of support."

"We found Amazon EC2 to be pricey."

"The GUI used to deploy EC2 must be improved."

"Regarding availability, a noticeable improvement would be the possibility of more load balancing configurations and the deployment of more datacenters, mainly in Latin America."

More Amazon EC2 cons

"Its UI can be better. Maintaining the history server is a little cumbersome, and it should be improved. I had issues while looking at the historical tags, which sometimes created problems. You have to separately create a history server and run it. Such things can be made easier. Instead of separately installing the history server, it can be made a part of the whole setup so that whenever you set it up, it becomes available."

"Technical expertise from an engineer is required to deploy and run high-tech tools, like Informatica, on Apache Spark, making it an area where improvements are required to make the process easier for users."

"When you first start using this solution, it is common to run into memory errors when you are dealing with large amounts of data."

"Apache Spark is very difficult to use. It would require a data engineer. It is not available for every engineer today because they need to understand the different concepts of Spark, which is very, very difficult and it is not easy to learn."

"It should support more programming languages."

"Apache Spark could improve the connectors that it supports. There are a lot of open-source databases in the market. For example, cloud databases, such as Redshift, Snowflake, and Synapse. Apache Spark should have connectors present to connect to these databases. There are a lot of workarounds required to connect to those databases, but it should have inbuilt connectors."

"Apache Spark's GUI and scalability could be improved."

"Stability in terms of API (things were difficult, when transitioning from RDD to DataFrames, then to DataSet)."

More Apache Spark cons

Pricing and Cost Advice

"Amazon EC2 has a pay-as-you-use cost model."

"EC2 pricing is somewhat transparent, in that AWS provides pricing for all instance types. However, the number of pricing options can be confusing."

"The solution has different pricing models, and its cost differs when you purchase it for one year or three years."

"The licensing of Amazon EC2 is expensive. Microsoft Windows Servers are expensive to license."

"The clients have found the billing of Amazon EC2 good, but the price could be less high. There is a monthly subscription to use the solution."

"It is not an expensive solution."

"The price is reasonable, but there is definitely an opportunity to lower it in instances which are of a higher configuration, because they have been typically used for the long term."

"I use the free tier, although I have paid for some services that are not free. The overall cost of this solution depends on the services you use."

More Amazon EC2 pricing and cost advice

"Apache Spark is an open-source tool."

"On the cloud model can be expensive as it requires substantial resources for implementation, covering on-premises hardware, memory, and licensing."

"It is an open-source platform. We do not pay for its subscription."

"Since we are using the Apache Spark version, not the data bricks version, it is an Apache license version, the support and resolution of the bug are actually late or delayed. The Apache license is free."

"It is quite expensive. In fact, it accounts for almost 50% of the cost of our entire project."

"It is an open-source solution, it is free of charge."

"Apache Spark is open-source. You have to pay only when you use any bundled product, such as Cloudera."

"The product is expensive, considering the setup."

More Apache Spark pricing and cost advice

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Top Industries

By visitors reading reviews

Computer Software Company

20%

Financial Services Firm

15%

Retailer

University

Financial Services Firm

27%

Computer Software Company

13%

Manufacturing Company

Comms Service Provider

Company Size

By reviewers

Large Enterprise

Midsize Enterprise

Small Business

Questions from the Community

What do you like most about Amazon EC2?

The scalability and elasticity are helpful.

See all answers

What is your experience regarding pricing and costs for Amazon EC2?

I'm going to mention again that there is quite a bit of complexity within the pricing of EC2 instances. I'm just going to give it six out of ten since there are various standards, upfront and commi...

See all answers

What needs improvement with Amazon EC2?

There is not much to be improved or enhanced. One of the things that need to be looked into is the complex pricing, which is rather intense. Sometimes, clients don't understand the structures. Thes...

See all answers

What do you like most about Apache Spark?

We use Spark to process data from different data sources.

See all answers

What is your experience regarding pricing and costs for Apache Spark?

Compared to other solutions like Doc DB, Spark is more costly due to the need for extensive infrastructure. It requires significant investment in infrastructure, which can be expensive. While cloud...

See all answers

What needs improvement with Apache Spark?

The Spark solution could improve in scheduling tasks and managing dependencies. Spark alone cannot handle sequential tasks, requiring environments like Airflow scheduler or scripts. For instance, o...

See all answers

Comparisons

AWS Fargate vs Amazon EC2

Compared 44% of the time

AWS Batch vs Amazon EC2

Compared 25% of the time

AWS Lambda vs Amazon EC2

Compared 18% of the time

More Amazon EC2 Competitors

Spring Boot vs Apache Spark

Compared 27% of the time

SAP HANA vs Apache Spark

Compared 12% of the time

AWS Batch vs Apache Spark

Compared 12% of the time

Cloudera Distribution for Hadoop vs Apache Spark

Compared 8% of the time

Spark SQL vs Apache Spark

Compared 7% of the time

More Apache Spark Competitors

Product Reports

Buyer's Guide

Amazon EC2

March 2025

Download Amazon EC2 product report

Buyer's Guide

Apache Spark

March 2025

Download Apache Spark product report

Also Known As

Amazon Elastic Compute Cloud, EC2

No data available

Overview

Amazon Elastic Compute Cloud (Amazon EC2) is a web service that provides secure, resizable compute capacity in the cloud. It is designed to make web-scale cloud computing easier for developers.

Amazon EC2’s simple web service interface allows you to obtain and configure capacity with minimal friction. It provides you with complete control of your computing resources and lets you run on Amazon’s proven computing environment. Amazon EC2 reduces the time required to obtain and boot new server instances to minutes, allowing you to quickly scale capacity, both up and down, as your computing requirements change. Amazon EC2 changes the economics of computing by allowing you to pay only for capacity that you actually use. Amazon EC2 provides developers the tools to build failure resilient applications and isolate them from common failure scenarios.

Amazon Web Services (AWS)

Spark provides programmers with an application programming interface centered on a data structure called the resilient distributed dataset (RDD), a read-only multiset of data items distributed over a cluster of machines, that is maintained in a fault-tolerant way. It was developed in response to limitations in the MapReduce cluster computing paradigm, which forces a particular linear dataflowstructure on distributed programs: MapReduce programs read input data from disk, map a function across the data, reduce the results of the map, and store reduction results on disk. Spark's RDDs function as a working set for distributed programs that offers a (deliberately) restricted form of distributed shared memory

Apache

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

Buyer's Guide

Amazon EC2 vs. Apache Spark

March 2025

Free Report: Amazon EC2 vs. Apache Spark

Find out what your peers are saying about Amazon EC2 vs. Apache Spark and other solutions. Updated: March 2025.

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