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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
10th
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 April 2026, in the Streaming Analytics category, the mindshare of Amazon Kinesis is 4.7%, down from 8.7% compared to the previous year. The mindshare of Apache Spark Streaming is 4.2%, up from 2.7% compared to the previous year. It is calculated based on PeerSpot user engagement data.
Streaming Analytics Mindshare Distribution
ProductMindshare (%)
Amazon Kinesis4.7%
Apache Spark Streaming4.2%
Other91.1%
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 scalability is pretty good."
"Setting Amazon Kinesis up is quick and easy; it only takes a few minutes to configure the necessary settings and start using it."
"We have been able to drop our costs for ingesting data by about 60 to 70%."
"One of the best features of Amazon Kinesis is the multi-partition."
"The Kinesis VideoStream and DataStream are the most important features."
"The most valuable feature is that it has a pretty robust way of capturing things."
"The feature that I've found most valuable is the replay. That is one of the most valuable in our business. We are business-to-business so replay was an important feature - being able to replay for 24 hours. That's an important feature."
"Amazon Kinesis's main purpose is to provide near real-time data streaming at a consistent 2Mbps rate, which is really impressive."
"The solution is very stable and reliable."
"The platform’s most valuable feature for processing real-time data is its ability to handle continuous data streams."
"The main benefits of Apache Spark Streaming include cost savings, time savings, and efficiency improvements about data storage."
"The main benefits of Apache Spark Streaming include cost savings, time savings, and efficiency improvements about data storage."
"It is the most scalable tool that I have seen before."
"Spark Streaming is critical, quite stable, full-featured, and scalable."
"As an open-source solution, using it is basically free."
"The solution is better than average and some of the valuable features include efficiency and stability."
 

Cons

"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."
"The default limit that they have, which at the moment is 5,000 records per second seems too low."
"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."
"In general, the pain point for us was that once the data gets into Kinesis there is no way for us to understand what's happening because Kinesis divides everything into shards."
"Amazon Kinesis involved a more complex setup and configuration than Azure Event Hub."
"In general, the pain point for us was that once the data gets into Kinesis there is no way for us to understand what's happening because Kinesis divides everything into shards. So if we wanted to understand what's happening with a particular shard, whether it is published or not, we could not. Even with the logs, if we want to have some kind of logging it is in the shard."
"Kinesis is good for Amazon Cloud but not as suitable for other cloud vendors."
"I suggest integrating additional features, such as incorporating Amazon Pinpoint or Amazon Connect as bundled offerings, rather than deploying them as separate services."
"In terms of improvement, the UI could be better."
"It was resource-intensive, even for small-scale applications."
"One improvement I would expect is real-time processing instead of micro-batch or near real-time."
"The initial setup is quite complex."
"The cost and load-related optimizations are areas where the tool lacks and needs improvement."
"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."
"We would like to have the ability to do arbitrary stateful functions in Python."
"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

"The solution's pricing is fair."
"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."
"Amazon Kinesis is an expensive solution."
"The tool's pricing is cheap."
"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."
"The fee is based on the number of hours the service is running."
"I think for us, with Amazon Kinesis, if we have to set up our own Kafka or cluster, it will be very time-consuming. If one considers the aforementioned aspect, Amazon Kinesis is a cheap tool."
"Amazon Kinesis pricing is sometimes reasonable and sometimes could be better, depending on the planning, so it's a five out of ten for me."
"Spark is an affordable solution, especially considering its open-source nature."
"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."
"People pay for Apache Spark Streaming as a service."
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Top Industries

By visitors reading reviews
Financial Services Firm
15%
Computer Software Company
13%
Manufacturing Company
7%
Construction Company
5%
Financial Services Firm
23%
Comms Service Provider
8%
Computer Software Company
8%
Marketing Services Firm
7%
 

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: April 2026.
890,088 professionals have used our research since 2012.