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Amazon Kinesis 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 Kinesis
Ranking in Streaming Analytics
2nd
Average Rating
8.0
Reviews Sentiment
7.0
Number of Reviews
29
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 Kinesis is 5.2%, down from 9.0% 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 Market Share Distribution
ProductMarket Share (%)
Amazon Kinesis5.2%
Apache Spark Streaming3.9%
Other90.9%
Streaming Analytics
 

Featured Reviews

CD
AWS Cloud Architect at a healthcare company with 10,001+ employees
Real-time streaming and seamless integration enhance workloads with room for competitive pricing improvements
Amazon Kinesis is easy to get started with, provides good documentation, and has a multilang daemon interface that makes it programming-language agnostic. The throughput is convenient for processing volumes out of the box and does not require complex configurations. It also provides auto-scaling with different partition keys into various shards. Lambda's scalability, seamless integration with other AWS services, and support for multiple programming languages are very beneficial.
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

"The Kinesis VideoStream and DataStream are the most important features."
"From my experience, one of the most valuable features is the ability to track silent events on endpoints. Previously, these events might have gone unnoticed, but now we can access them within the product range. For example, if a customer reports that their calls are not reaching the portal files, we can use this feature to troubleshoot and optimize the system."
"The solution works well in rather sizable environments."
"I have worked in companies that build tools in-house. They face scaling challenges."
"There is no problem with the tool's stability."
"Amazon Kinesis also provides us with plenty of flexibility."
"The integration capabilities of the product are good."
"The scalability is pretty good."
"It's the fastest solution on the market with low latency data on data transformations."
"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."
"Apache Spark Streaming has features like checkpointing and Streaming API that are useful."
"Spark Streaming is critical, quite stable, full-featured, and scalable."
"Apache Spark's capabilities for machine learning are quite extensive and can be used in a low-code way."
"As an open-source solution, using it is basically free."
"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 main benefits of Apache Spark Streaming include cost savings, time savings, and efficiency improvements about data storage."
 

Cons

"Kinesis Data Analytics needs to be improved somewhat. It's SQL based data but it is not as user friendly as MySQL or Athena tools."
"It would be beneficial if Amazon Kinesis provided document based support on the internet to be able to read the data from the Kinesis site."
"Amazon Kinesis could improve its pricing to be more competitive, especially for large volumes."
"There are certain shortcomings in the machine learning capacity offered by the product, making it an area where improvements are required."
"Could include features that make it easier to scale."
"One area for improvement in the solution is the file size limitation of 10 Mb. My company works with files with a larger file size. The batch size and throughput also need improvement in Amazon Kinesis."
"If there were better documentation on optimal sharding strategies then it would be helpful."
"Something else to mention is that we use Kinesis with Lambda a lot and the fact that you can only connect one Stream to one Lambda, I find is a limiting factor. I would definitely recommend to remove that constraint."
"We don't have enough experience to be judgmental about its flaws."
"The downside is when you have this the other way around in the columns, it becomes really hard to use."
"We would like to have the ability to do arbitrary stateful functions in Python."
"Integrating event-level streaming capabilities could be beneficial."
"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."
"When dealing with various data types including COBOL, Excel, JSON, video, audio, and MPG files, challenges can arise with incomplete or missing values."
"The initial setup is quite complex."
"When dealing with various data types including COBOL, Excel, JSON, video, audio, and MPG files, challenges can arise with incomplete or missing values."
 

Pricing and Cost Advice

"Amazon Kinesis is an expensive solution."
"The pricing depends on the use cases and the level of usage. If you wanted to use Kinesis for different use cases, there's definitely a cheaper base cost involved. However, it's not entirely cheap, as different use cases might require different levels of Kinesis usage."
"In general, cloud services are very convenient to use, even if we have to pay a bit more, as we know what we are paying for and can focus on other tasks."
"The tool's pricing is cheap."
"Under $1,000 per month."
"I rate the product price a five on a scale of one to ten, where one is cheap, and ten is expensive."
"The tool's entry price is cheap. However, pricing increases with data volume."
"It was actually a fairly high volume we were spending. We were spending about 150 a month."
"I was using the open-source community version, which was self-hosted."
"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."
"Spark is an affordable solution, especially considering its open-source nature."
"People pay for Apache Spark Streaming as a service."
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Top Industries

By visitors reading reviews
Computer Software Company
16%
Financial Services Firm
14%
Manufacturing Company
6%
Educational Organization
5%
Computer Software Company
22%
Financial Services Firm
19%
Healthcare Company
6%
University
6%
 

Company Size

By reviewers
Large Enterprise
Midsize Enterprise
Small Business
By reviewers
Company SizeCount
Small Business8
Midsize Enterprise10
Large Enterprise9
By reviewers
Company SizeCount
Small Business9
Midsize Enterprise2
Large Enterprise7
 

Questions from the Community

What do you like most about Amazon Kinesis?
Amazon Kinesis's main purpose is to provide near real-time data streaming at a consistent 2Mbps rate, which is really impressive.
What is your experience regarding pricing and costs for Amazon Kinesis?
Amazon Kinesis and Lambda pricing is competitive, but we noticed that scaling and large volumes could potentially increase costs significantly.
What needs improvement with Amazon Kinesis?
We are contemplating moving away from Amazon Kinesis primarily because of the cost. It is very useful, but if we write our own analytics and data processing pipeline, it would be much cheaper for u...
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 AWS Kinesis, AWS Kinesis, Kinesis
Spark Streaming
 

Overview

 

Sample Customers

Zillow, Netflix, Sonos
UC Berkeley AMPLab, Amazon, Alibaba Taobao, Kenshoo, eBay Inc.
Find out what your peers are saying about Amazon Kinesis vs. Apache Spark Streaming and other solutions. Updated: February 2026.
883,011 professionals have used our research since 2012.