We performed a comparison between Amazon Kinesis and Azure Stream Analytics based on our users’ reviews in five categories. After reading all of the collected data, you can find our conclusion below.
Comparison Results: Amazon Kinesis ultimately wins out in this comparison. According to reviews, Amazon Kinesis appears to be a more robust and high performing solution.
"Amazon Kinesis has improved our ROI."
"The solution works well in rather sizable environments."
"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."
"I find almost all features valuable, especially the timing and fast pace movement."
"Great auto-scaling, auto-sharing, and auto-correction features."
"The management and analytics are valuable features."
"The scalability is pretty good."
"The integration capabilities of the product are good."
"The way it organizes data into tables and dashboards is very helpful."
"It's scalable as a cloud product."
"The solution has a lot of functionality that can be pushed out to companies."
"Provides deep integration with other Azure resources."
"The most valuable features of Azure Stream Analytics are the ease of provisioning and the interface is not terribly complex."
"The life cycle, report management and crash management features are great."
"I appreciate this solution because it leverages open-source technologies. It allows us to utilize the latest streaming solutions and it's easy to develop."
"It provides the capability to streamline multiple output components."
"If there were better documentation on optimal sharding strategies then it would be helpful."
"One thing that would be nice would be a policy for increasing the number of Kinesis streams because that's the one thing that's constant. You can change it in real time, but somebody has to change it, or you have to set some kind of meter. So, auto-scaling of adding and removing streams would be nice."
"There are certain shortcomings in the machine learning capacity offered by the product, making it an area where improvements are required."
"Kinesis can be expensive, especially when dealing with large volumes of data."
"Lacks first in, first out queuing."
"The solution has a two-minute maximum time delay for live streaming, which could be reduced."
"Kinesis is good for Amazon Cloud but not as suitable for other cloud vendors."
"Amazon Kinesis should improve its limits."
"Its features for event imports and architecture could be enhanced."
"The collection and analysis of historical data could be better."
"The only challenge was that the streaming analytics area in Azure Stream Analytics could not meet our company's expectations, making it a component where improvements are required."
"The solution could be improved by providing better graphics and including support for UI and UX testing."
"The initial setup is complex."
"The solution’s customer support could be improved."
"I would like to have a contact individual at Microsoft."
"The UI should be a little bit better from a usability perspective."
Amazon Kinesis is ranked 1st in Streaming Analytics with 24 reviews while Azure Stream Analytics is ranked 3rd in Streaming Analytics with 22 reviews. Amazon Kinesis is rated 8.0, while Azure Stream Analytics is rated 8.2. The top reviewer of Amazon Kinesis writes "Used for media streaming and live-streaming data". On the other hand, the top reviewer of Azure Stream Analytics writes "Easy to set up and user-friendly, but could be priced better". Amazon Kinesis is most compared with Amazon MSK, Confluent, Apache Flink, Google Cloud Dataflow and Apache Spark Streaming, whereas Azure Stream Analytics is most compared with Databricks, Amazon MSK, Apache Flink, Apache Spark and Apache Spark Streaming. See our Amazon Kinesis vs. Azure Stream Analytics 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.
