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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
7.4
Reviews Sentiment
6.6
Number of Reviews
12
Ranking in other categories
No ranking in other categories
Apache Spark Streaming
Ranking in Streaming Analytics
11th
Average Rating
8.0
Reviews Sentiment
7.1
Number of Reviews
12
Ranking in other categories
No ranking in other categories
 

Mindshare comparison

As of August 2025, in the Streaming Analytics category, the mindshare of Amazon MSK is 6.5%, down from 9.6% compared to the previous year. The mindshare of Apache Spark Streaming is 3.1%, down from 3.7% compared to the previous year. It is calculated based on PeerSpot user engagement data.
Streaming Analytics
 

Featured Reviews

FNU AKSHANSH - PeerSpot reviewer
Streamlines our processes, and we don't need to configure any VPCs; it's automatic
We don't have many use cases involving ingesting large amounts of data and scaling up and down. We have a clear understanding of our data volume, which remains relatively constant throughout the week. While we're aware of other features Amazon MSK offers, we feel confident in our current setup. If our requirements change significantly in the future, we'll reassess our needs and consider adopting Amazon MSK.
Venkata Phaneendra Reddy Janga - PeerSpot reviewer
Improved data latency and integration with diverse data sources enables robust real-time processing
The best feature of Apache Spark Streaming is that it's built upon the Spark SQL engine. This is easy for someone coming from a SQL background to work with real-time data, even if they are new to real-time processing. They can quickly get started using the Spark SQL engine. Another valuable feature is that we can control many aspects such as the configuration of the engine, memory management, and have a checkpointing mechanism that allows us to manually start or restart jobs from a specific point. This is particularly useful for restoring messages of a Kafka topic from a specific date and time using the checkpointing mechanism. The integration with Spark's ecosystems such as MLlib and GraphX has significant potential, although I have not worked on that part as we focus mainly on data engineering. We can handle late-arriving data with Apache Spark Streaming. Sometimes aggregation results might be missed if data arrives out of order, but features such as windowing allow us to manage out-of-order data by specifying a watermark time. Recently released mechanisms to query the state make it easier to handle data programmatically.

Quotes from Members

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

Pros

"Amazon MSK has significantly improved our organization by building seamless integration between systems."
"MSK has a private network that's an out-of-box feature."
"It offers good stability."
"The scalability and usability are quite remarkable."
"Amazon MSK's scalability is very good."
"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."
"Overall, it is very cost-effective based on the workflow."
"It provides installations, scaling, and other functionalities straight out of the box."
"Apache Spark Streaming's most valuable feature is near real-time analytics. The developers can build APIs easily for a code-steaming pipeline. The solutions have an ecosystem of integration with other stock services."
"The platform’s most valuable feature for processing real-time data is its ability to handle continuous data streams."
"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."
"The solution is very stable and reliable."
"As an open-source solution, using it is basically free."
"Apache Spark Streaming is versatile. You can use it for competitive intelligence, gathering data from competitors, or for internal tasks like monitoring workflows."
"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."
 

Cons

"Amazon MSK could improve on the features they offer. They are still lagging behind Confluence."
"It does not autoscale. Because if you do keep it manually when you add a note to the cluster and then you register it, then it is scalable, but the fact that you have to go and do it, I think, makes it, again, a bit of some operational overhead when managing the cluster."
"We need to create connectors in Amazon MSK, but there are no default connectors in AWS for that purpose."
"One of the reasons why we prefer Kafka is because the support is a little bit difficult to manage with Amazon MSK."
"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."
"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."
"Horizontal scale-out is actually not easy, making it an area where improvements are required."
"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."
"Integrating event-level streaming capabilities could be beneficial."
"One improvement I would expect is real-time processing instead of micro-batch or near real-time."
"The initial setup is quite complex."
"The solution itself could be easier to use."
"In terms of improvement, the UI could be better."
"There could be an improvement in the area of the user configuration section, it should be less developer-focused and more business user-focused."
"We don't have enough experience to be judgmental about its flaws."
"We would like to have the ability to do arbitrary stateful functions in Python."
 

Pricing and Cost Advice

"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."
"The platform has better pricing than one of its competitors."
"The price of Amazon MSK is less than some competitor solutions, such as Confluence."
"I was using the open-source community version, which was self-hosted."
"People pay for Apache Spark Streaming as a service."
"Spark is an affordable solution, especially considering its open-source nature."
"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."
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Top Industries

By visitors reading reviews
Financial Services Firm
23%
Computer Software Company
15%
Manufacturing Company
6%
Comms Service Provider
4%
Computer Software Company
22%
Financial Services Firm
21%
University
5%
Manufacturing Company
5%
 

Company Size

By reviewers
Large Enterprise
Midsize Enterprise
Small Business
 

Questions from the Community

What do you like most about Amazon MSK?
Amazon MSK has significantly improved our organization by building seamless integration between systems.
What needs improvement with Amazon MSK?
I'm not sure exactly what benefit we have because we are using multiple AWS tools. We have AWS DMS, which is also the same as Amazon MSK, and we have Fivetran, which is a third-party website provid...
What is your primary use case for Amazon MSK?
We are currently using Amazon MSK to transfer data from our PostgreSQL database to our DynamoDB, acting as a mediator between those two databases for migration purposes. Our data is in an on-premis...
What do you like most about Apache Spark Streaming?
Apache Spark Streaming is versatile. You can use it for competitive intelligence, gathering data from competitors, or for internal tasks like monitoring workflows.
What needs improvement with Apache Spark Streaming?
We don't have enough experience to be judgmental about its flaws, as we've only used stable features like batch micro-batch. Integration poses no problem; however, I don't use some features and can...
What is your primary use case for Apache Spark Streaming?
We use Spark Streaming in a micro-batch region. It's not a full real-time system, but it offers high performance and low latency.
 

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: July 2025.
865,295 professionals have used our research since 2012.