Amazon Kinesis vs Apache Spark Streaming comparison

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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: March 2024).
763,955 professionals have used our research since 2012.
Featured Review
Quotes From Members
We asked business professionals to review the solutions they use.
Here are some excerpts of what they said:
Pros
"The most valuable feature is that it has a pretty robust way of capturing things.""Everything is hosted and simple.""What turns out to be most valuable is its integration with Lambda functions because you can process the data as it comes in. As soon as data comes, you'll fire a Lambda function to process a trench of data.""The management and analytics are valuable features.""Amazon Kinesis also provides us with plenty of flexibility.""The solution works well in rather sizable environments.""One of the best features of Amazon Kinesis is the multi-partition.""The solution has the capacity to store the data anywhere from one day to a week and provides limitless storage for us."

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"The solution is better than average and some of the valuable features include efficiency and stability.""Apache Spark Streaming has features like checkpointing and Streaming API that are useful.""As an open-source solution, using it is basically free.""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.""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'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.""It's the fastest solution on the market with low latency data on data transformations.""The solution is very stable and reliable."

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Cons
"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.""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.""The services which are described in the documentation could use some visual presentation because for someone who is new to the solution the documentation is not easy to follow or beginner friendly and can leave a person feeling helpless.""Lacks first in, first out queuing.""The price is not much cheaper. So, there is room for improvement in the pricing.""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.""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."

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"The solution itself could be easier to use.""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 cost and load-related optimizations are areas where the tool lacks and needs improvement.""The initial setup is quite complex.""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.""It was resource-intensive, even for small-scale applications.""We would like to have the ability to do arbitrary stateful functions in Python."

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Pricing and Cost Advice
  • "Under $1,000 per month."
  • "The solution's pricing is fair."
  • "It was actually a fairly high volume we were spending. We were spending about 150 a month."
  • "The fee is based on the number of hours the service is running."
  • "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."
  • "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 entry price is cheap. However, pricing increases with data volume."
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  • "People pay for Apache Spark Streaming as a service."
  • "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."
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    Questions from the Community
    Top Answer:The management and analytics are valuable features.
    Top Answer:A snapshot from the stream of the data analytics I already have on the cloud. do a snapshot to stop the process and restart a few weeks later when I have more data or more availability of the client… more »
    Top Answer:Apache Spark Streaming is versatile. You can use it for competitive intelligence, gathering data from competitors, or for internal tasks like monitoring workflows.
    Top Answer:In terms of improvement, the UI could be better. Additionally, Spark Streaming works well for various use cases, but improvements could be made for ultra-fast scenarios where seconds matter. While… more »
    Top Answer:As a data engineer, I use Apache Spark Streaming to process real-time data for web page analytics and integrate diverse data sources into centralized data warehouses.
    Ranking
    2nd
    out of 38 in Streaming Analytics
    Views
    13,285
    Comparisons
    9,791
    Reviews
    8
    Average Words per Review
    562
    Rating
    7.9
    8th
    out of 38 in Streaming Analytics
    Views
    4,523
    Comparisons
    3,689
    Reviews
    6
    Average Words per Review
    473
    Rating
    8.2
    Comparisons
    Also Known As
    Amazon AWS Kinesis, AWS Kinesis, Kinesis
    Spark Streaming
    Learn More
    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.
    Top Industries
    VISITORS READING REVIEWS
    Computer Software Company17%
    Financial Services Firm16%
    Manufacturing Company8%
    Comms Service Provider5%
    VISITORS READING REVIEWS
    Financial Services Firm19%
    Computer Software Company19%
    Comms Service Provider7%
    Manufacturing Company6%
    Company Size
    REVIEWERS
    Small Business44%
    Midsize Enterprise38%
    Large Enterprise19%
    VISITORS READING REVIEWS
    Small Business21%
    Midsize Enterprise12%
    Large Enterprise67%
    REVIEWERS
    Small Business56%
    Midsize Enterprise11%
    Large Enterprise33%
    VISITORS READING REVIEWS
    Small Business21%
    Midsize Enterprise12%
    Large Enterprise67%
    Buyer's Guide
    Amazon Kinesis vs. Apache Spark Streaming
    March 2024
    Find out what your peers are saying about Amazon Kinesis vs. Apache Spark Streaming and other solutions. Updated: March 2024.
    763,955 professionals have used our research since 2012.

    Amazon Kinesis is ranked 2nd in Streaming Analytics with 8 reviews while Apache Spark Streaming is ranked 8th in Streaming Analytics with 6 reviews. Amazon Kinesis is rated 8.2, while Apache Spark Streaming is rated 8.0. The top reviewer of Amazon Kinesis writes "The solution is easy to deploy, scalable, and stable". On the other hand, the top reviewer of Apache Spark Streaming writes "Easy deployment as a cluster and good documentation". Amazon Kinesis is most compared with Azure Stream Analytics, Apache Flink, Confluent, Amazon MSK and Databricks, whereas Apache Spark Streaming is most compared with Azure Stream Analytics, Spring Cloud Data Flow, Confluent, Apache Pulsar and Starburst Enterprise. 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.