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.
"Setting Amazon Kinesis up is quick and easy; it only takes a few minutes to configure the necessary settings and start using it."
"One of the best features of Amazon Kinesis is the multi-partition."
"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 have worked in companies that build tools in-house. They face scaling challenges."
"Amazon Kinesis also provides us with plenty of flexibility."
"The scalability is pretty good."
"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."
"Everything is hosted and simple."
"I like all the connected ecosystems of Microsoft, it is really good with other BI tools that are easy to connect."
"The solution's technical support is good."
"It's a product that can scale."
"The most valuable features of Azure Stream Analytics are the ease of provisioning and the interface is not terribly complex."
"It's scalable as a cloud product."
"Technical support is pretty helpful."
"Real-time analytics is the most valuable feature of this solution. I can send the collected data to Power BI in real time."
"The solution has a lot of functionality that can be pushed out to companies."
"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."
"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."
"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."
"In order to do a successful setup, the person handling the implementation needs to know the solution very well. You can't just come into it blind and with little to no experience."
"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."
"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."
"Lacks first in, first out queuing."
"The UI should be a little bit better from a usability perspective."
"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."
"I would like to have a contact individual at Microsoft."
"Easier scalability and more detailed job monitoring features would be helpful."
"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."
"The collection and analysis of historical data could be better."
"The solution doesn't handle large data packets very efficiently, which could be improved upon."
"Its features for event imports and architecture could be enhanced."
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 Confluent, Amazon MSK, 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.
