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Apache Spark vs Spot comparison

 

Comparison Buyer's Guide

Executive SummaryUpdated on Oct 19, 2025

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 Spark
Ranking in Compute Service
5th
Average Rating
8.4
Reviews Sentiment
6.9
Number of Reviews
68
Ranking in other categories
Hadoop (1st), Java Frameworks (2nd)
Spot
Ranking in Compute Service
9th
Average Rating
8.8
Reviews Sentiment
7.6
Number of Reviews
4
Ranking in other categories
Cloud Management (23rd), Server Virtualization Software (14th), Cloud Operations Analytics (1st), Cloud Analytics (2nd), Containers as a Service (CaaS) (4th), Cloud Cost Management (5th)
 

Mindshare comparison

As of January 2026, in the Compute Service category, the mindshare of Apache Spark is 11.2%, down from 11.4% compared to the previous year. The mindshare of Spot is 3.8%, up from 0.9% compared to the previous year. It is calculated based on PeerSpot user engagement data.
Compute Service Market Share Distribution
ProductMarket Share (%)
Apache Spark11.2%
Spot3.8%
Other85.0%
Compute Service
 

Featured Reviews

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.
KS
Dev Ops Engineer at a construction company with 11-50 employees
Intelligent autoscaling has cut compute costs and now manages ephemeral workloads efficiently
I think overall Spot is quite good. The UI is powerful, but it can feel a bit dense for some new users. More guided onboarding would help teams adopt advanced features faster, and deeper insights into Kubernetes resource usage would be beneficial. Overall, it is a really good platform that is quite mature and stable. I chose a rating of nine because it may sometimes be a bit overwhelming for newcomers, and there are also a few areas in which the EKS Kubernetes level granularity is a little missing. Overall, I think Spot is a really good and stable tool.

Quotes from Members

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

Pros

"The solution has been very stable."
"The product's deployment phase is easy."
"The most significant advantage of Spark 3.0 is its support for DataFrame UDF Pandas UDF features."
"ETL and streaming capabilities."
"The product’s most valuable feature is the SQL tool. It enables us to create a database and publish it."
"Spark is used for transformations from large volumes of data, and it is usefully distributed."
"This solution provides a clear and convenient syntax for our analytical tasks."
"The main feature that we find valuable is that it is very fast."
"Spot has positively impacted our organization by automating cloud resource management, which has significantly cut costs and improved efficiency."
"My compute costs have reduced, capacity and production output have increased, and my overhead for maintaining custom scripts or doing some of the tasks manually has been saved."
"The solution offers both block access and file access, making it a nice solution for customers."
"The solution helps us to manage and scale automatically whenever there is a limit to the increase in the application workflow."
 

Cons

"Stability in terms of API (things were difficult, when transitioning from RDD to DataFrames, then to DataSet)."
"The migration of data between different versions could be improved."
"The Spark solution could improve in scheduling tasks and managing dependencies."
"The initial setup was not easy."
"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 lacks geospatial data."
"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."
"Apache Spark provides very good performance The tuning phase is still tricky."
"The solution doesn't have support from OCI, and it should start working to onboard OCI."
"There are no particular areas for improvement I can identify."
 

Pricing and Cost Advice

"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."
"Considering the product version used in my company, I feel that the tool is not costly since the product is available for free."
"It is an open-source platform. We do not pay for its subscription."
"I did not pay anything when using the tool on cloud services, but I had to pay on the compute side. The tool is not expensive compared with the benefits it offers. I rate the price as an eight out of ten."
"We are using the free version of the solution."
"Spark is an open-source solution, so there are no licensing costs."
"Apache Spark is an open-source tool."
Information not available
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Top Industries

By visitors reading reviews
Financial Services Firm
25%
Computer Software Company
11%
Manufacturing Company
7%
Comms Service Provider
6%
Manufacturing Company
19%
Computer Software Company
17%
Healthcare Company
7%
Financial Services Firm
7%
 

Company Size

By reviewers
Large Enterprise
Midsize Enterprise
Small Business
By reviewers
Company SizeCount
Small Business28
Midsize Enterprise15
Large Enterprise32
No data available
 

Questions from the Community

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...
What do you like most about Spot Ocean?
The solution helps us to manage and scale automatically whenever there is a limit to the increase in the application workflow.
What needs improvement with Spot Ocean?
Spot can be improved by adding deeper multi-cloud integrations, enhancing real-time security automation, and continuously making advancements based on customer feedback.
What is your primary use case for Spot Ocean?
I have been using Spot for five years. My main use case for Spot is cloud optimization.We use Spot for optimization by leveraging real-time optimization as well as auto-optimization. The company al...
 

Comparisons

 

Also Known As

No data available
Spot Ocean, Spot Elastigroup, Spot Eco
 

Overview

 

Sample Customers

NASA JPL, UC Berkeley AMPLab, Amazon, eBay, Yahoo!, UC Santa Cruz, TripAdvisor, Taboola, Agile Lab, Art.com, Baidu, Alibaba Taobao, EURECOM, Hitachi Solutions
Freshworks, Zalando, Red Spark, News, Trax, ETAS, Demandbase, BeesWa, Duolingo, intel, IBM, N26, Wix, EyeEm, moovit, SAMSUNG, News UK, ticketmaster
Find out what your peers are saying about Apache Spark vs. Spot and other solutions. Updated: December 2025.
879,927 professionals have used our research since 2012.