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Amazon MSK vs Apache Spark Streaming comparison

 

Comparison Buyer's Guide

Executive SummaryUpdated on Dec 17, 2024

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 MSK
Ranking in Streaming Analytics
6th
Average Rating
7.2
Reviews Sentiment
6.5
Number of Reviews
14
Ranking in other categories
No ranking in other categories
Apache Spark Streaming
Ranking in Streaming Analytics
9th
Average Rating
7.8
Reviews Sentiment
6.4
Number of Reviews
17
Ranking in other categories
No ranking in other categories
 

Mindshare comparison

As of March 2026, in the Streaming Analytics category, the mindshare of Amazon MSK is 4.9%, down from 7.9% compared to the previous year. The mindshare of Apache Spark Streaming is 3.9%, up from 2.9% compared to the previous year. It is calculated based on PeerSpot user engagement data.
Streaming Analytics Mindshare Distribution
ProductMindshare (%)
Amazon MSK4.9%
Apache Spark Streaming3.9%
Other91.2%
Streaming Analytics
 

Featured Reviews

SYED SHAAZ - PeerSpot reviewer
Co-Founder & CTO at Photios AI
Improved data streaming and integration challenges prompt search for alternatives
The integration capabilities of Amazon MSK are not very flexible. If you have your own self-managed Kafka, that helps significantly because you can set up configurations. We are considering self-managed Kafka since our product is only one year old. The Kafka integrations are fine, but the configurations are an issue. The only issue with Amazon MSK that we are facing is the configurations. There are preset configurations and limited configurations that we can set for our unique use case. The product could improve by allowing us to set different configurations. I would also like to see Amazon MSK improve in the area of connectors. We are considering Confluent Cloud because they have many more connectors. They have KSQL DB and governance features. It is slightly costlier, but Confluent offers more flexibility with their connectors.
Himansu Jena - PeerSpot reviewer
Sr Project Manager at Raj Subhatech
Efficient real-time data management and analysis with advanced features
There are various ways we can improve Apache Spark Streaming through best practices. The initial part requires attention to batch interval tuning, which helps small intervals in micro batches based on latency requirements and helps prevent back pressure. We can use data formats such as Parquet or ORC for storage that needs faster reads and leveraging feature predicate push-down optimizations. We can implement serialization which helps with any Kyro in terms of .NET or Java. We have boxing and unboxing serialization for XML and JSON for converting key-pair values stored in browser. We can also implement caching mechanisms for storing and recomputing multiple operations. We can use specified joins which help with smaller databases, and distributed joins can minimize users. We can implement project optimization memory for CPU efficiency, known as Tungsten. Additionally, load balancing, checkpointing, and schema evaluation are areas to consider based on performance and bottlenecks. We can use Bugzilla tools for tracking and Splunk to monitor the performance of process systems, utilization, and performance based on data frames or data sets.

Quotes from Members

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

Pros

"Amazon MSK's separation of concerns and ease of creating and deploying new features are highly valuable. It just requires to assign them to the topic, and then anyone who needs to consume these messages can do so directly from Amazon MSK. This separation of concerns makes it very convenient, especially for new feature development, as developers can easily access the messages they need without having to deal with complex server communications or protocol setups."
"The scalability and usability are quite remarkable."
"Overall, it is very cost-effective based on the workflow."
"Amazon MSK has good integration because our team has been undergoing significant changes. Coupling it with MSK within AWS is helpful. We don't have to set up additionals or monitor external environments. This"
"Amazon MSK has significantly improved our organization by building seamless integration between systems."
"What I appreciate most about Amazon MSK is that it doesn't require extensive concern about the configurations; it starts checking how the brokers are functioning, and automatically, Amazon MSK tries to resolve all the problems."
"Amazon MSK has contributed positively to our real-time analytics capabilities because Fortis's dashboards have dashboard health that needs to be maintained, user logs that need to be maintained, and usage tracking."
"It provides installations, scaling, and other functionalities straight out of the box."
"By integrating Apache Spark Streaming, the data freshness rate, and latency have significantly improved from 24-hour batch processing to less than one minute, facilitating faster communication to downstream systems, aiding marketing campaigns."
"As an open-source solution, using it is basically free."
"The main benefits of Apache Spark Streaming include cost savings, time savings, and efficiency improvements about data storage."
"The solution is very stable and reliable."
"The solution is better than average and some of the valuable features include efficiency and stability."
"Apache Spark's capabilities for machine learning are quite extensive and can be used in a low-code way."
"Apache Spark Streaming is versatile. You can use it for competitive intelligence, gathering data from competitors, or for internal tasks like monitoring workflows."
"I appreciate Apache Spark Streaming's micro-batching capabilities; the watermarking functionality and related features are quite good."
 

Cons

"We need to create connectors in Amazon MSK, but there are no default connectors in AWS for that purpose."
"The cost of using Amazon MSK is high, which is a significant disadvantage, as the increase in cloud costs by 50% to 60% does not justify the savings."
"One of the reasons why we prefer Kafka is because the support is a little bit difficult to manage with Amazon MSK."
"In my opinion, there are areas in Amazon MSK that could be improved, particularly in terms of configuration. Initially setting it up and getting it connected was quite challenging. The naming conventions for policies were updated by AWS, and some were undocumented, leading to confusion with outdated materials. It took us weeks of trial and error before discovering new methods through hidden tutorials and official documentation."
"Amazon MSK could improve on the features they offer. They are still lagging behind Confluence."
"The product's schema support needs enhancement. It will help enhance integration with many kinds of languages of programming languages, especially for environments using languages like .NET."
"It would be really helpful if Amazon MSK could provide a single installation that covers all the servers."
"It should be more flexible, integration-wise."
"The solution itself could be easier to use."
"When dealing with various data types including COBOL, Excel, JSON, video, audio, and MPG files, challenges can arise with incomplete or missing values."
"One improvement I would expect is real-time processing instead of micro-batch or near real-time."
"Monitoring is an area where they could definitely improve Apache Spark Streaming. When you have a streaming application, it generates numerous logs. After some time, the logs become meaningless because they're quite large and impossible to open."
"We don't have enough experience to be judgmental about its flaws."
"The problem is we need to use it in a certain manner. After that, we need to apply another pipeline for the machine learning processes, and that's what we work on."
"It was resource-intensive, even for small-scale applications."
"While it is reliable, there are some issues with Apache Spark Streaming as it is not 100% reliable."
 

Pricing and Cost Advice

"The platform has better pricing than one of its competitors."
"The price of Amazon MSK is less than some competitor solutions, such as Confluence."
"When you create a complete enterprise-driven architecture that is deployable on an enterprise scale, I would say that the prices of Amazon MSK and Confluent Platform become comparable."
"Spark is an affordable solution, especially considering its open-source nature."
"People pay for Apache Spark Streaming as a service."
"On a scale from one to ten, where one is expensive, or not cost-effective, and ten is cheap, I rate the price a seven."
"I was using the open-source community version, which was self-hosted."
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Top Industries

By visitors reading reviews
Financial Services Firm
21%
Computer Software Company
12%
Manufacturing Company
6%
Retailer
5%
Financial Services Firm
23%
Computer Software Company
9%
Healthcare Company
7%
Marketing Services Firm
7%
 

Company Size

By reviewers
Large Enterprise
Midsize Enterprise
Small Business
By reviewers
Company SizeCount
Small Business4
Midsize Enterprise7
Large Enterprise4
By reviewers
Company SizeCount
Small Business9
Midsize Enterprise2
Large Enterprise7
 

Questions from the Community

What needs improvement with Amazon MSK?
The integration capabilities of Amazon MSK are not very flexible. If you have your own self-managed Kafka, that helps significantly because you can set up configurations. We are considering self-ma...
What is your primary use case for Amazon MSK?
We are recently working with Amazon MSK at Fortis, where we have multiple dashboards in our revenue intelligence platform. We are streaming data from different apps into those dashboards. The data ...
What advice do you have for others considering Amazon MSK?
We are working with Amazon MSK product, Managed Streaming for Apache Kafka. The main benefits I have seen from using Amazon MSK is that as a B2B enterprise client, we have many SLAs to fulfill. Tra...
What needs improvement with Apache Spark Streaming?
One of the improvements we need is in Spark SQL and the machine learning library. I don't think there is too much to work on, but the issue is when we want to use machine learning, we always need t...
What is your primary use case for Apache Spark Streaming?
We work with Apache Spark Streaming for our project because we use that as one of the landing data sources, and we work with it to ensure we can get all of the data before it goes through our data ...
What advice do you have for others considering Apache Spark Streaming?
One thing I would share with other organizations considering Apache Spark Streaming is the necessity of having effective data storage. We want to ensure we acquire and manage our data storage effec...
 

Also Known As

Amazon Managed Streaming for Apache Kafka
Spark Streaming
 

Overview

 

Sample Customers

Expedia, Intuit, Royal Dutch Shell, Brooks Brothers
UC Berkeley AMPLab, Amazon, Alibaba Taobao, Kenshoo, eBay Inc.
Find out what your peers are saying about Amazon MSK vs. Apache Spark Streaming and other solutions. Updated: March 2026.
884,873 professionals have used our research since 2012.