Amazon EC2 vs Apache Spark comparison

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Amazon Web Services (AWS) Logo
2,668 views|1,702 comparisons
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3,209 views|2,461 comparisons
Comparison Buyer's Guide
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 2024).
765,386 professionals have used our research since 2012.
Featured Review
Quotes From Members
We asked business professionals to review the solutions they use.
Here are some excerpts of what they said:
Pros
"The solution offers good access policies.""The product is easy to set up.""Configuration can be changed at any time and it's very scalable.""We don't have to worry about scalability issues or maintenance or security. It's all taken care of.""EC2 has the typical advantages of using the cloud. It's easy to provision and set up.""An advantage of Amazon is that it offers a wide range of infrastructure services with an easy way to configure them.""The most valuable feature is EC2 is scalable, so when you want to move to market, you don't need to wait until your provision is fast, you can just go and provision it and then easily install your application.""The scalability of Amazon EC2 is good. However, the stability can depend on what service I am using."

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"Now, when we're tackling sentiment analysis using NLP technologies, we deal with unstructured data—customer chats, feedback on promotions or demos, and even media like images, audio, and video files. For processing such data, we rely on PySpark. Beneath the surface, Spark functions as a compute engine with in-memory processing capabilities, enhancing performance through features like broadcasting and caching. It's become a crucial tool, widely adopted by 90% of companies for a decade or more.""The processing time is very much improved over the data warehouse solution that we were using.""It is useful for handling large amounts of data. It is very useful for scientific purposes.""The solution has been very stable.""It's easy to prepare parallelism in Spark, run the solution with specific parameters, and get good performance.""The product’s most valuable feature is the SQL tool. It enables us to create a database and publish it.""The deployment of the product is easy.""The product is useful for analytics."

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Cons
"They have to provide clarity on pricing. It's not transparent.""Amazon EC2 could improve the console view. The ability to see the console view directly would be helpful, similar to what VMware has. Additionally, when the system is rebooting we are able to see a screenshot of the UI, but it would be a lot better if we could interact directly with the console level.""Amazon EC2 could improve by reducing the price.""Nothing is really missing in terms of features.""I would like to see improvement in the information available up-front for users around tailoring the package to their actual requirements. At present it can take time to work with the on demand instance until you are used to what features are right for the user.""We're expecting to have Graviton instances. Graviton means it's not internal, it's a low-cost instance. At present time, Graviton is not supported for a few packages.""Its price can be reduced.""In terms of improvement, they could build some client-side desktop tools that provide easier connectivity to Amazon."

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"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.""Include more machine learning algorithms and the ability to handle streaming of data versus micro batch processing.""When you first start using this solution, it is common to run into memory errors when you are dealing with large amounts of data.""If you have a Spark session in the background, sometimes it's very hard to kill these sessions because of D allocation.""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.""We are building our own queries on Spark, and it can be improved in terms of query handling.""The setup I worked on was really complex.""When you are working with large, complex tasks, the garbage collection process is slow and affects performance."

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Pricing and Cost Advice
  • "Pricing appears to be cheap, however, it is extremely difficult in calculating what something will cost."
  • "It has helped to reduce costs with infrastructure."
  • "EC2 pricing is somewhat transparent, in that AWS provides pricing for all instance types. However, the number of pricing options can be confusing."
  • "For our usage, the cost is approximately $20,000 to $23,000 per month."
  • "There is a license required to use this solution and we pay on a monthly basis."
  • "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."
  • "Amazon EC2 has a pay-as-you-use cost model."
  • "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."
  • More Amazon EC2 Pricing and Cost Advice →

  • "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."
  • "Apache Spark is open-source. You have to pay only when you use any bundled product, such as Cloudera."
  • "We are using the free version of the solution."
  • "Apache Spark is not too cheap. You have to pay for hardware and Cloudera licenses. Of course, there is a solution with open source without Cloudera."
  • "Apache Spark is an expensive solution."
  • "Spark is an open-source solution, so there are no licensing costs."
  • "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 solution, it is free of charge."
  • More Apache Spark Pricing and Cost Advice →

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    Questions from the Community
    Top Answer:Amazon EC2 is really reliable and provides great flexibility.
    Top Answer:The solution has different pricing models, and its cost differs when you purchase it for one year or three years.
    Top Answer:The solution’s pricing and downtimes could be improved. I would like to have a better pricing model for Amazon EC2 instances because it comes with different pricing models. The solution's cost differs… more »
    Top Answer:The product’s most valuable features are lazy evaluation and workload distribution.
    Top Answer:They provide an open-source license for the on-premise version. However, we have to pay for the cloud version including data centers and virtual machines.
    Top Answer:They could improve the issues related to programming language for the platform.
    Ranking
    3rd
    out of 16 in Compute Service
    Views
    2,668
    Comparisons
    1,702
    Reviews
    46
    Average Words per Review
    347
    Rating
    8.6
    5th
    out of 16 in Compute Service
    Views
    3,209
    Comparisons
    2,461
    Reviews
    20
    Average Words per Review
    387
    Rating
    8.6
    Comparisons
    AWS Fargate logo
    Compared 64% of the time.
    AWS Lambda logo
    Compared 12% of the time.
    Apache NiFi logo
    Compared 7% of the time.
    AWS Batch logo
    Compared 4% of the time.
    Google App Engine logo
    Compared 2% of the time.
    Spring Boot logo
    Compared 32% of the time.
    AWS Batch logo
    Compared 10% of the time.
    Spark SQL logo
    Compared 10% of the time.
    SAP HANA logo
    Compared 7% of the time.
    Jakarta EE logo
    Compared 2% of the time.
    Also Known As
    Amazon Elastic Compute Cloud, EC2
    Learn More
    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.

    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

    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
    Top Industries
    REVIEWERS
    Computer Software Company32%
    Financial Services Firm16%
    Comms Service Provider12%
    Government8%
    VISITORS READING REVIEWS
    Financial Services Firm20%
    Computer Software Company18%
    Educational Organization7%
    University6%
    REVIEWERS
    Computer Software Company30%
    Financial Services Firm15%
    University9%
    Marketing Services Firm6%
    VISITORS READING REVIEWS
    Financial Services Firm25%
    Computer Software Company13%
    Manufacturing Company7%
    Comms Service Provider6%
    Company Size
    REVIEWERS
    Small Business45%
    Midsize Enterprise16%
    Large Enterprise38%
    VISITORS READING REVIEWS
    Small Business20%
    Midsize Enterprise12%
    Large Enterprise67%
    REVIEWERS
    Small Business40%
    Midsize Enterprise19%
    Large Enterprise40%
    VISITORS READING REVIEWS
    Small Business17%
    Midsize Enterprise12%
    Large Enterprise71%
    Buyer's Guide
    Amazon EC2 vs. Apache Spark
    March 2024
    Find out what your peers are saying about Amazon EC2 vs. Apache Spark and other solutions. Updated: March 2024.
    765,386 professionals have used our research since 2012.

    Amazon EC2 is ranked 3rd in Compute Service with 56 reviews while Apache Spark is ranked 5th in Compute Service with 58 reviews. Amazon EC2 is rated 8.6, while Apache Spark is rated 8.4. The top reviewer of Amazon EC2 writes "Highly stable, is auto-scaling, and can be utilized in under five minutes". On the other hand, the top reviewer of Apache Spark writes "Reliable, able to expand, and handle large amounts of data well". Amazon EC2 is most compared with AWS Fargate, AWS Lambda, Apache NiFi, AWS Batch and Google App Engine, whereas Apache Spark is most compared with Spring Boot, AWS Batch, Spark SQL, SAP HANA and Jakarta EE. See our Amazon EC2 vs. Apache Spark report.

    See our list of best Compute Service vendors.

    We monitor all Compute Service reviews to prevent fraudulent reviews and keep review quality high. We do not post reviews by company employees or direct competitors. We validate each review for authenticity via cross-reference with LinkedIn, and personal follow-up with the reviewer when necessary.