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Apache Spark vs npm comparison

 

Comparison Buyer's Guide

Executive Summary

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 Java Frameworks
2nd
Average Rating
8.4
Reviews Sentiment
6.9
Number of Reviews
68
Ranking in other categories
Hadoop (1st), Compute Service (5th)
npm
Ranking in Java Frameworks
10th
Average Rating
9.0
Number of Reviews
6
Ranking in other categories
No ranking in other categories
 

Mindshare comparison

As of January 2026, in the Java Frameworks category, the mindshare of Apache Spark is 9.0%, up from 7.7% compared to the previous year. The mindshare of npm is 0.9%, up from 0.1% compared to the previous year. It is calculated based on PeerSpot user engagement data.
Java Frameworks Market Share Distribution
ProductMarket Share (%)
Apache Spark9.0%
npm0.9%
Other90.1%
Java Frameworks
 

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.
Harsh Dabas - PeerSpot reviewer
Senior QA Automation Engineer at LogMeIn, Inc.
Automation has boosted test coverage and now supports reliable CI workflows
BrowserStack is able to solve every issue which we have been facing, so I would rate it as a 10 out of 10 in terms of my experience. Regarding pricing, I think the organization takes care of that. I am not really aware of the pricing of this, but I have made some personal projects as well in which I use GitHub Actions for free. We can push our code as well. As of now, I am using the free version for my personal use. For the organization, I think the organization is taking care of the same, so we do not need to bother about it.

Quotes from Members

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

Pros

"Apache Spark, specifically PySpark and the tools available there, have been quite helpful in my event analysis work."
"We use it for ETL purposes as well as for implementing the full transformation pipelines."
"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."
"It is useful for handling large amounts of data. It is very useful for scientific purposes."
"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."
"ETL and streaming capabilities."
"The solution has been very stable."
"The distribution of tasks, like the seamless map-reduce functionality, is quite impressive."
"The reversal build, gendered build, migrated PCA, and CT features are excellent."
"The solution is scalable."
"It's an open-source setting that's very scalable and easily approachable. I like that you can plug in many features to my product."
"The product's most valuable feature is dependency installation."
"The most valuable feature of NPM is to trigger APMs."
 

Cons

"We use big data manager but we cannot use it as conditional data so whenever we're trying to fetch the data, it takes a bit of time."
"The main concern is the overhead of Java when distributed processing is not necessary."
"In data analysis, you need to take real-time data from different data sources. You need to process this in a subsecond, do the transformation in a subsecond, and all that."
"The product could improve the user interface and make it easier for new users."
"When you are working with large, complex tasks, the garbage collection process is slow and affects performance."
"When you first start using this solution, it is common to run into memory errors when you are dealing with large amounts of data."
"This solution currently cannot support or distribute neural network related models, or deep learning related algorithms. We would like this functionality to be developed."
"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."
"The library could be updated."
"I would like to see compatible versions, and what new features they will be providing. If it is a useful feature I can merge it. If it is not a usable feature, then I can ignore the newer version."
"The product should be compatible with various programming languages, including both native and upcoming languages."
"Some of the libraries that we try to use in npm have issues with security. Also, because it's an open-source solution, I think there are lots of challenges with security. So, the security layer could be improved."
"NPM can improve the package manager. For the packages we download for our APM studio to trigger our APM driver, it would benefit if we could have the latest version of NuGet Package Manager within the package manager control. For example, Visual Studio would be good. Then it would be easy for us to get the package manager from there instead of Googling it out and matching it with the current version. It would be less time-consuming for us."
 

Pricing and Cost Advice

"On the cloud model can be expensive as it requires substantial resources for implementation, covering on-premises hardware, memory, and licensing."
"We are using the free version of the solution."
"Apache Spark is an expensive solution."
"Apache Spark is an open-source solution, and there is no cost involved in deploying the solution on-premises."
"Apache Spark is open-source. You have to pay only when you use any bundled product, such as Cloudera."
"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."
"The product is expensive, considering the setup."
"It is an open-source platform. We do not pay for its subscription."
"It's an open-source solution, and there are no hidden fees."
"We use the open-source version, so it is free."
"NPM is an open-source solution."
"The licensing cost is around one hundred and fifty dollars on a quarterly basis."
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Top Industries

By visitors reading reviews
Financial Services Firm
25%
Computer Software Company
9%
Manufacturing Company
7%
Comms Service Provider
6%
No data available
 

Company Size

By reviewers
Large Enterprise
Midsize Enterprise
Small Business
By reviewers
Company SizeCount
Small Business28
Midsize Enterprise15
Large Enterprise32
By reviewers
Company SizeCount
Small Business4
Midsize Enterprise2
Large Enterprise1
 

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...
Ask a question
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Comparisons

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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
slack, microsoft, netflix, adobe, docker, visa, splunk, zillow
Find out what your peers are saying about Apache Spark vs. npm and other solutions. Updated: December 2025.
881,114 professionals have used our research since 2012.