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 most valuable feature of Amazon Kinesis is real-time data streaming."
"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."
"Amazon Kinesis also provides us with plenty of flexibility."
"The solution works well in rather sizable environments."
"One of the best features of Amazon Kinesis is the multi-partition."
"The solution has the capacity to store the data anywhere from one day to a week and provides limitless storage for us."
"The integration capabilities of the product are good."
"The solution's technical support is good."
"The solution has a lot of functionality that can be pushed out to companies."
"Real-time analytics is the most valuable feature of this solution. I can send the collected data to Power BI in real time."
"We use Azure Stream Analytics for simulation and internal activities."
"It's a product that can scale."
"The integrations for this solution are easy to use and there is flexibility in integrating the tool with Azure Stream Analytics."
"The life cycle, report management and crash management features are great."
"Provides deep integration with other Azure resources."
"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."
"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."
"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."
"There are certain shortcomings in the machine learning capacity offered by the product, making it an area where improvements are required."
"Lacks first in, first out queuing."
"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."
"Kinesis can be expensive, especially when dealing with large volumes of data."
"Amazon Kinesis involved a more complex setup and configuration than Azure Event Hub."
"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."
"There may be some issues when connecting with Microsoft Power BI because we are providing the input and output commands, and there's a chance of it being delayed while connecting."
"If something goes wrong, it's very hard to investigate what caused it and why."
"The solution doesn't handle large data packets very efficiently, which could be improved upon."
"The solution’s customer support could be improved."
"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."
"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."
"The solution's interface could be simpler to understand for non-technical people."
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.
