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 #9 with an average rating of 8.0. Amazon Web Services (AWS) holds a 10.6% mindshare in SA, compared to Apache’s 3.7% mindshare. Additionally, 89% of Amazon Web Services (AWS) users are willing to recommend the solution, compared to 90% of Apache users who would recommend it.

Amazon Kinesis

Read 27 Amazon Kinesis reviews

8,771 Views
6,492 Comparison Views

89% willing to recommend

Apache Spark Streaming

Read 10 Apache Spark Streaming reviews

2,712 Views
1,973 Comparison Views

90% willing to recommend

Amazon Kinesis

Apache Spark Streaming

Comparison Buyer's Guide

Download the report

Executive Summary

We performed a comparison between Amazon Kinesis and Apache Spark Streaming based on real PeerSpot user reviews.

Find out in this report how the two Streaming Analytics solutions compare in terms of features, pricing, service and support, easy of deployment, and ROI.

To learn more, read our detailed Amazon Kinesis vs. Apache Spark Streaming Report (Updated: October 2024).

Buyer's Guide

Amazon Kinesis vs. Apache Spark Streaming

October 2024

Download the complete report

Helped 816,406 peers since 2012

Categories and Ranking

Amazon Kinesis

Ranking in Streaming Analytics

2nd

Average Rating

8.0

Reviews Sentiment

7.0

Number of Reviews

Ranking in other categories

No ranking in other categories

Apache Spark Streaming

Ranking in Streaming Analytics

9th

Average Rating

8.0

Reviews Sentiment

6.2

Number of Reviews

Ranking in other categories

No ranking in other categories

Mindshare comparison

As of November 2024, in the Streaming Analytics category, the mindshare of Amazon Kinesis is 10.6%, down from 15.4% compared to the previous year. The mindshare of Apache Spark Streaming is 3.7%, down from 4.7% 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.

Read full review

Oscar Estorach

Chief Data-strategist and Director at Theworkshop.es

Versatile and flexible when dealing with large-scale data streams

What I like about Spark is its versatility in supporting multiple languages and that makes it my preferred choice for building scalable and efficient systems, whether it is hooking databases with web applications or handling large-scale data transformations. Apache Spark Streaming is versatile. You can use it for competitive intelligence, gathering data from competitors, or for internal tasks like monitoring workflows. It works well in the cloud, and you can structure data using Databricks or Spark, providing flexibility for different projects. Spark Streaming's flexibility shines when dealing with large-scale data streams. It caters to different needs, offering real-time insights for tasks like online sales analytics. The ability to prioritize data streams is valuable, especially for monitoring competitor prices online.

Read full review

Quotes from Members

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

Pros

"The management and analytics are valuable features."

"Amazon Kinesis also provides us with plenty of flexibility."

"The solution's technical support is flawless."

"There is no problem with the tool's stability."

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

"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."

"Everything is hosted and simple."

"Great auto-scaling, auto-sharing, and auto-correction features."

More Amazon Kinesis pros

"It's the fastest solution on the market with low latency data on data transformations."

"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."

"The solution is better than average and some of the valuable features include efficiency and stability."

"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."

"The solution is very stable and reliable."

"Apache Spark Streaming has features like checkpointing and Streaming API that are useful."

"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."

More Apache Spark Streaming pros

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."

"If there were better documentation on optimal sharding strategies then it would be helpful."

"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."

"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."

"There could be valid data in Kinesis that is not being processed, which affects stability. Although it rarely happens, this issue has been observed in many deployments, making it not completely stable."

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

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

"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."

More Amazon Kinesis cons

"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 solution itself could be easier to use."

"The cost and load-related optimizations are areas where the tool lacks and needs improvement."

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

"The initial setup is quite complex."

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

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

"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

"The fee is based on the number of hours the service is running."

"The solution's pricing is fair."

"The product falls on a bit of an expensive side."

"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."

"Under $1,000 per month."

"Amazon Kinesis is an expensive solution."

"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."

More Amazon Kinesis pricing and cost advice

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

"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."

"Spark is an affordable solution, especially considering its open-source nature."

See which vendors are best for you

Use our free recommendation engine to learn which Streaming Analytics solutions are best for your needs.

See recommendations

816,406 professionals have used our research since 2012.

Top Industries

By visitors reading reviews

Computer Software Company

18%

Financial Services Firm

18%

Manufacturing Company

10%

Retailer

Financial Services Firm

22%

Computer Software Company

20%

University

Manufacturing 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?

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.

See all answers

What needs improvement with Amazon Kinesis?

There are some kind of hard limits on Amazon Kinesis, and if you hit that, then you will get the throughput exceed error. We have to deal with and reduce how many consumers are hitting Amazon Kines...

See all answers

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?

The product's event handling capabilities, particularly compared to Kaspersky, need improvement. Integrating event-level streaming capabilities could be beneficial. This aligns with the idea of exp...

See all answers

What is your primary use case for Apache Spark Streaming?

I've used it more for ETL. It's useful for creating data pipelines, streaming datasets, generating synthetic data, synchronizing data, creating data lakes, and loading and unloading data is fast an...

See all answers

Comparisons

Azure Stream Analytics vs Amazon Kinesis

Compared 31% of the time

Confluent vs Amazon Kinesis

Compared 23% of the time

Amazon MSK vs Amazon Kinesis

Compared 15% of the time

Apache Flink vs Amazon Kinesis

Compared 12% of the time

Google Cloud Dataflow vs Amazon Kinesis

Compared 5% of the time

More Amazon Kinesis Competitors

Spring Cloud Data Flow vs Apache Spark Streaming

Compared 20% of the time

Apache Pulsar vs Apache Spark Streaming

Compared 16% of the time

Azure Stream Analytics vs Apache Spark Streaming

Compared 15% of the time

Apache Flink vs Apache Spark Streaming

Compared 7% of the time

SAS Event Stream Processing vs Apache Spark Streaming

Compared 6% of the time

More Apache Spark Streaming Competitors

Product Reports

Buyer's Guide

Amazon Kinesis

November 2024

Download Amazon Kinesis product report

Buyer's Guide

Streaming Analytics

November 2024

Download Apache Spark Streaming product report

Also Known As

Amazon AWS Kinesis, AWS Kinesis, Kinesis

Spark Streaming

Learn More

Amazon Web Services (AWS)

Apache

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.

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

Sample Customers

Zillow, Netflix, Sonos

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

Buyer's Guide

Amazon Kinesis vs. Apache Spark Streaming

October 2024

Free Report: Amazon Kinesis vs. Apache Spark Streaming

Find out what your peers are saying about Amazon Kinesis vs. Apache Spark Streaming and other solutions. Updated: October 2024.

DOWNLOAD NOW

816,406 professionals have used our research since 2012.

See our Amazon Kinesis vs. Apache Spark Streaming report.

See our list of best Streaming Analytics vendors.

We monitor all Streaming Analytics reviews to prevent fraudulent reviews and keep review quality high. We do not post reviews by company employees or direct competitors. We validate each review for authenticity via cross-reference with LinkedIn, and personal follow-up with the reviewer when necessary.