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."What I like about Amazon Kinesis is that it's very effective for small businesses. It's a well-managed solution with excellent reporting. Amazon Kinesis is also easy to use, and even a novice developer can work with it, versus Apache Kafka, which requires expertise."
"One of the best features of Amazon Kinesis is the multi-partition."
"The solution works well in rather sizable environments."
"Its scalability is very high. There is no maintenance and there is no throughput latency. I think data scalability is high, too. You can ingest gigabytes of data within seconds or milliseconds."
"Amazon Kinesis also provides us with plenty of flexibility."
"The integration capabilities of the product are good."
"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."
"Kinesis is a fully managed program streaming application. You can manage any infrastructure. It is also scalable. Kinesis can handle any amount of data streaming and process data from hundreds, thousands of processes in every source with very low latency."
"Apache Spark Streaming is versatile. You can use it for competitive intelligence, gathering data from competitors, or for internal tasks like monitoring workflows."
"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."
"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."
"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."
"It's the fastest solution on the market with low latency data on data transformations."
"Amazon Kinesis should improve its limits."
"Kinesis can be expensive, especially when dealing with large volumes of data."
"Could include features that make it easier to scale."
"We were charged high costs for the solution’s enhanced fan-out feature."
"Amazon Kinesis involved a more complex setup and configuration than Azure Event Hub."
"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."
"Kinesis is good for Amazon Cloud but not as suitable for other cloud vendors."
"There are certain shortcomings in the machine learning capacity offered by the product, making it an area where improvements are required."
"Integrating event-level streaming capabilities could be beneficial."
"We would like to have the ability to do arbitrary stateful functions in Python."
"It was resource-intensive, even for small-scale applications."
"The solution itself could be easier to use."
"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."
"The cost and load-related optimizations are areas where the tool lacks and needs improvement."
"The initial setup is quite complex."
Amazon Kinesis is ranked 1st in Streaming Analytics with 24 reviews while Apache Spark Streaming is ranked 8th in Streaming Analytics with 9 reviews. Amazon Kinesis is rated 8.0, while Apache Spark Streaming is rated 8.0. The top reviewer of Amazon Kinesis writes "Used for media streaming and live-streaming data". On the other hand, the top reviewer of Apache Spark Streaming writes "Easy integration, beneficial auto-scaling, and good open-sourced support community". Amazon Kinesis is most compared with Azure Stream Analytics, Amazon MSK, Confluent, Apache Flink and Databricks, whereas Apache Spark Streaming is most compared with Spring Cloud Data Flow, Azure Stream Analytics, Apache Pulsar, Confluent and Starburst Enterprise. See our Amazon Kinesis vs. Apache Spark Streaming report.
See our list of best Streaming Analytics vendors.
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