We performed a comparison between Amazon Kinesis and Cloudera DataFlow 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 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."
"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."
"Setting Amazon Kinesis up is quick and easy; it only takes a few minutes to configure the necessary settings and start using it."
"The scalability is pretty good."
"I find almost all features valuable, especially the timing and fast pace movement."
"Amazon Kinesis's main purpose is to provide near real-time data streaming at a consistent 2Mbps rate, which is really impressive."
"The most valuable feature of Amazon Kinesis is real-time data streaming."
"The most effective features are data management and analytics."
"DataFlow's performance is okay."
"The initial setup was not so difficult"
"This solution is very scalable and robust."
"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."
"There are certain shortcomings in the machine learning capacity offered by the product, making it an area where improvements are required."
"In general, the pain point for us was that once the data gets into Kinesis there is no way for us to understand what's happening because Kinesis divides everything into shards. So if we wanted to understand what's happening with a particular shard, whether it is published or not, we could not. Even with the logs, if we want to have some kind of logging it is in the shard."
"If there were better documentation on optimal sharding strategies then it would be helpful."
"Could include features that make it easier to scale."
"I suggest integrating additional features, such as incorporating Amazon Pinpoint or Amazon Connect as bundled offerings, rather than deploying them as separate services."
"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."
"Amazon Kinesis should improve its limits."
"It's an outdated legacy product that doesn't meet the needs of modern data analysts and scientists."
"Although their workflow is pretty neat, it still requires a lot of transformation coding; especially when it comes to Python and other demanding programming languages."
"It is not easy to use the R language. Though I don't know if it's possible, I believe it is possible, but it is not the best language for machine learning."
Amazon Kinesis is ranked 1st in Streaming Analytics with 24 reviews while Cloudera DataFlow is ranked 13th in Streaming Analytics with 4 reviews. Amazon Kinesis is rated 8.0, while Cloudera DataFlow is rated 7.2. The top reviewer of Amazon Kinesis writes "Used for media streaming and live-streaming data". On the other hand, the top reviewer of Cloudera DataFlow writes "Has good data management and analytics features". Amazon Kinesis is most compared with Azure Stream Analytics, Amazon MSK, Confluent, Apache Flink and Google Cloud Dataflow, whereas Cloudera DataFlow is most compared with Databricks, Confluent, Amazon MSK, Hortonworks Data Platform and Informatica Data Engineering Streaming. See our Amazon Kinesis vs. Cloudera DataFlow 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.
