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."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."
"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."
"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."
"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."
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.
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