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.
"The scalability is pretty good."
"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."
"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."
"Great auto-scaling, auto-sharing, and auto-correction features."
"From my experience, one of the most valuable features is the ability to track silent events on endpoints. Previously, these events might have gone unnoticed, but now we can access them within the product range. For example, if a customer reports that their calls are not reaching the portal files, we can use this feature to troubleshoot and optimize the system."
"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."
"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."
"Amazon Kinesis's main purpose is to provide near real-time data streaming at a consistent 2Mbps rate, which is really impressive."
"It provides the capability to streamline multiple output components."
"The most valuable features are the IoT hub and the Blob storage."
"The solution's technical support is good."
"The life cycle, report management and crash management features are great."
"The solution has a lot of functionality that can be pushed out to companies."
"The way it organizes data into tables and dashboards is very helpful."
"I like all the connected ecosystems of Microsoft, it is really good with other BI tools that are easy to connect."
"We use Azure Stream Analytics for simulation and internal activities."
"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."
"I suggest integrating additional features, such as incorporating Amazon Pinpoint or Amazon Connect as bundled offerings, rather than deploying them as separate services."
"We were charged high costs for the solution’s enhanced fan-out feature."
"For me, especially with video streams, there's sometimes a kind of delay when the data has to be pumped to other services. This delay could be improved in Kinesis, or especially the Kinesis Video Streams, which is being used for different use cases for Amazon Connect. With that improvement, a lot of other use cases of Amazon Connect integrating with third-party analytic tools would be easier."
"Lacks first in, first out queuing."
"Could include features that make it easier to scale."
"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."
"The price is not much cheaper. So, there is room for improvement in the pricing."
"One area that could use improvement is the handling of data validation. Currently, there is a review process, but sometimes the validation fails even before the job is executed. This results in wasted time as we have to rerun the job to identify the failure."
"Early in the process, we had some issues with stability."
"The solution could be improved by providing better graphics and including support for UI and UX testing."
"The solution’s customer support could be improved."
"We would like to have centralized platform altogether since we have different kind of options for data ingestion. Sometimes it gets difficult to manage different platforms."
"If something goes wrong, it's very hard to investigate what caused it and why."
"Its features for event imports and architecture could be enhanced."
"The solution offers a free trial, however, it is too short."
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.
