Amazon Kinesis vs Apache Spark Streaming comparison

Amazon Web Services (AWS) and Apache are both solutions in the Streaming Analytics category. Amazon Web Services (AWS) is ranked #2 with an average rating of 7.8, while Apache is ranked #10 with an average rating of 8.2. Amazon Web Services (AWS) holds a 8.3% mindshare in SA, compared to Apache’s 2.6% mindshare. Additionally, 89% of Amazon Web Services (AWS) users are willing to recommend the solution, compared to 91% of Apache users who would recommend it.

Amazon Kinesis

Read 28 Amazon Kinesis reviews

5,080 Views
3,810 Comparison Views

89% willing to recommend

Apache Spark Streaming

Read 11 Apache Spark Streaming reviews

1,578 Views
1,126 Comparison Views

91% willing to recommend

Amazon Kinesis

Apache Spark Streaming

Comparison Buyer's Guide

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Executive SummaryUpdated on Dec 17, 2024

Apache Spark Streaming and Amazon Kinesis are both prominent contenders in the real-time data processing market. Despite the competitive pricing of Apache Spark Streaming, Amazon Kinesis is preferred due to its superior set of features.

Features: Apache Spark Streaming provides seamless integration with Hadoop ecosystems, fault tolerance, and scalability for complex analytics tasks. On the other hand, Amazon Kinesis offers extensive real-time analytics capabilities, customizable processing, and strong integration with the AWS ecosystem, making it highly adaptable for different use cases.

Room for Improvement: Apache Spark Streaming could enhance user-friendliness for those without extensive expertise, offer improved managed services, and simplify deployment to become more accessible. Amazon Kinesis might benefit from expanded documentation to assist beginners, enhanced integration with non-AWS services, and a reduction in potential costs associated with high data volumes.

Ease of Deployment and Customer Service: Amazon Kinesis simplifies deployment with a managed service model and provides robust customer support. In contrast, Apache Spark Streaming requires more manual configuration and expertise but offers extensive configuration flexibility.

Pricing and ROI: Apache Spark Streaming is cost-effective at the start due to its open-source nature but may incur higher operational costs over time with infrastructure management. Amazon Kinesis involves predictable monthly expenses that can lead to a higher ROI due to its ease of scaling and resource management.

To learn more, read our detailed Amazon Kinesis vs. Apache Spark Streaming Report (Updated: April 2025).

Buyer's Guide

Amazon Kinesis vs. Apache Spark Streaming

April 2025

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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

7.1

Number of Reviews

Ranking in other categories

No ranking in other categories

Apache Spark Streaming

Ranking in Streaming Analytics

10th

Average Rating

8.0

Reviews Sentiment

7.4

Number of Reviews

Ranking in other categories

No ranking in other categories

Mindshare comparison

As of May 2025, in the Streaming Analytics category, the mindshare of Amazon Kinesis is 8.3%, down from 13.6% compared to the previous year. The mindshare of Apache Spark Streaming is 2.6%, down from 3.8% compared to the previous year. It is calculated based on PeerSpot user engagement data.

Streaming Analytics

Featured Reviews

Rajni Kumar Jha

Senior Software Engineer at JPMorgan Chase & Co.

Used for media streaming and live-streaming data

It is not compulsory to use Amazon Kinesis. If you don't want to use the data streaming, you can use just the Kinesis data firehose. Using the Kinesis data firehose is compulsory because we can't store all chats and recordings in Amazon S3 without it. When a call comes in the Amazon Kinesis instance, it will go to Data Streams if we use it. Otherwise, it will go to the Kinesis data firehose, where we need to define the S3 bucket path, and it will go to Amazon S3. So, without the Kinesis data firehose, we can't store all the chats and recordings in Amazon S3. Using Amazon Kinesis totally depends upon the user's requirements. If you want to use live streaming for the data lake or data analyst team, you need to use Amazon Kinesis. If you don't want to use it, you can directly use the Kinesis data firehose, which will be stored in Amazon S3. Overall, I rate the solution an eight out of ten.

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AbhishekGupta

Engineering Leader at Walmart

Easy integration, beneficial auto-scaling, and good open-sourced support community

The service structure of Apache Spark Streaming can improve. There are a lot of issues with memory management and latency. There is no real-time analytics. We recommend it for the use cases where there is a five-second latency, but not for a millisecond, an IOT-based, or the detection anomaly-based. Flink as a service is much better. Apache Spark Streaming does not have auto-tuning. A customer needs to invest a lot, in terms of management and maintenance.

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Quotes from Members

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

Pros

"I find almost all features valuable, especially the timing and fast pace movement."

"The product's initial setup phase is not difficult because we are using the tool on the cloud."

"I have worked in companies that build tools in-house. They face scaling challenges."

"The most valuable feature of Amazon Kinesis is real-time data streaming."

"The solution has the capacity to store the data anywhere from one day to a week and provides limitless storage for us."

"The Kinesis VideoStream and DataStream are the most important features."

"The integration capabilities of the product are good."

"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."

More Amazon Kinesis pros

"Apache Spark Streaming is versatile. You can use it for competitive intelligence, gathering data from competitors, or for internal tasks like monitoring workflows."

"Apache Spark Streaming was straightforward in terms of maintenance. It was actively developed, and migrating from an older to a newer version was quite simple."

"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."

"Apache Spark's capabilities for machine learning are quite extensive and can be used in a low-code way."

"The platform’s most valuable feature for processing real-time data is its ability to handle continuous data streams."

"As an open-source solution, using it is basically free."

More Apache Spark Streaming pros

Cons

"Snapshot from the the from the the stream of the data analytic I have already on the cloud, do a snapshot to not to make great or to get the data out size of the web service. But to stop the process and restart a few weeks later when I have more data or more available of the client teams."

"Kinesis can be expensive, especially when dealing with large volumes of data."

"There are some kind of hard limits on Amazon Kinesis, and if you hit that, then you will get the throughput exceed error."

"Kinesis is good for Amazon Cloud but not as suitable for other cloud vendors."

"I think the default settings are far too low."

"There are certain shortcomings in the machine learning capacity offered by the product, making it an area where improvements are required."

"I suggest integrating additional features, such as incorporating Amazon Pinpoint or Amazon Connect as bundled offerings, rather than deploying them as separate services."

"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."

More Amazon Kinesis cons

"In terms of improvement, the UI could be better."

"The debugging aspect could use some improvement."

"The service structure of Apache Spark Streaming can improve. There are a lot of issues with memory management and latency. There is no real-time analytics. We recommend it for the use cases where there is a five-second latency, but not for a millisecond, an IOT-based, or the detection anomaly-based. Flink as a service is much better."

"The initial setup is quite complex."

"It was resource-intensive, even for small-scale applications."

"The solution itself could be easier to use."

"We would like to have the ability to do arbitrary stateful functions in Python."

"There could be an improvement in the area of the user configuration section, it should be less developer-focused and more business user-focused."

More Apache Spark Streaming cons

Pricing and Cost Advice

"I rate the product price a five on a scale of one to ten, where one is cheap, and ten is expensive."

"The solution's pricing is fair."

"Amazon Kinesis is an expensive solution."

"Under $1,000 per month."

"The tool's entry price is cheap. However, pricing increases with data volume."

"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."

"It was actually a fairly high volume we were spending. We were spending about 150 a month."

"The tool's pricing is cheap."

More Amazon Kinesis pricing and cost advice

"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."

"I was using the open-source community version, which was self-hosted."

"People pay for Apache Spark Streaming as a service."

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Top Industries

By visitors reading reviews

Computer Software Company

18%

Financial Services Firm

17%

Manufacturing Company

10%

Retailer

Financial Services Firm

28%

Computer Software Company

21%

Manufacturing Company

Healthcare Company

Company Size

By reviewers

Large Enterprise

Midsize Enterprise

Small Business

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.

See all answers

What is your experience regarding pricing and costs for Amazon Kinesis?

Amazon Kinesis is moderately priced. In comparison with other competitors, it is fairly priced, however, if they reduced the price a little, it could add more value to customers.

See all answers

What needs improvement with Amazon Kinesis?

I do not see any scope for improvement as it does what it is supposed to do. No changes are required. Since it's predominantly a back-end service, any end-user isn't going to interact with it direc...

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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.

See all answers

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...

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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.

See all answers

Comparisons

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Compared 23% of the time

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Compared 18% of the time

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Compared 8% of the time

PubSub+ Platform vs Amazon Kinesis

Compared 2% of the time

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Compared 21% of the time

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Compared 20% of the time

Azure Stream Analytics vs Apache Spark Streaming

Compared 13% of the time

Apache Flink vs Apache Spark Streaming

Compared 10% of the time

Starburst Enterprise vs Apache Spark Streaming

Compared 9% of the time

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Product Reports

Buyer's Guide

Amazon Kinesis

May 2025

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Buyer's Guide

Streaming Analytics

May 2025

Download Apache Spark Streaming product report

Also Known As

Amazon AWS Kinesis, AWS Kinesis, Kinesis

Spark Streaming

Overview

Amazon Kinesis makes it easy to collect, process, and analyze real-time, streaming data so you can get timely insights and react quickly to new information. Amazon Kinesis offers key capabilities to cost-effectively process streaming data at any scale, along with the flexibility to choose the tools that best suit the requirements of your application. With Amazon Kinesis, you can ingest real-time data such as video, audio, application logs, website clickstreams, and IoT telemetry data for machine learning, analytics, and other applications. Amazon Kinesis enables you to process and analyze data as it arrives and respond instantly instead of having to wait until all your data is collected before the processing can begin.

Amazon Web Services (AWS)

Spark Streaming makes it easy to build scalable fault-tolerant streaming applications.

Apache

Sample Customers

Zillow, Netflix, Sonos

UC Berkeley AMPLab, Amazon, Alibaba Taobao, Kenshoo, eBay Inc.

Buyer's Guide

Amazon Kinesis vs. Apache Spark Streaming

April 2025

Free Report: Amazon Kinesis vs. Apache Spark Streaming

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