We performed a comparison between Apache NiFi and Azure Stream Analytics based on real PeerSpot user reviews.
Find out what your peers are saying about Amazon Web Services (AWS), Apache, Zadara and others in Compute Service."The user interface is good and makes it easy to design very popular workflows."
"Visually, this is a good product."
"The initial setup is very easy."
"It's an automated flow, where you can build a flow from source to destination, then do the transformation in between."
"The initial setup is very easy. I would rate my experience with the initial setup a ten out of ten, where one point is difficult, and ten points are easy."
"The most valuable feature has been the range of clients and the range of connectors that we could use."
"The most valuable features of this solution are ease of use and implementation."
"We can integrate the tool with other applications easily."
"It provides the capability to streamline multiple output components."
"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."
"Real-time analytics is the most valuable feature of this solution. I can send the collected data to Power BI in real time."
"Technical support is pretty helpful."
"The most valuable features are the IoT hub and the Blob storage."
"The integrations for this solution are easy to use and there is flexibility in integrating the tool with Azure Stream Analytics."
"The solution has a lot of functionality that can be pushed out to companies."
"We run many jobs, and there are already large tables. When we do not control NiFi on time, all reports fail for the day. So it's pretty slow to control, and it has to be improved."
"The use case templates could be more precise to typical business needs."
"More features must be added to the product."
"The overall stability of this solution could be improved. In a future release, we would like to have access to more features that could be used in a parallel way. This would provide more freedom with processing."
"I think the UI interface needs to be more user-friendly."
"There should be a better way to integrate a development environment with local tools."
"There is room for improvement in integration with SSO. For example, NiFi does not have any integration with SSO. And if I want to give some kind of rollback access control across the organization. That is not possible."
"There are some claims that NiFi is cloud-native but we have tested it, and it's not."
"The solution could be improved by providing better graphics and including support for UI and UX testing."
"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."
"Easier scalability and more detailed job monitoring features would be helpful."
"The solution doesn't handle large data packets very efficiently, which could be improved upon."
"The solution's interface could be simpler to understand for non-technical people."
"It is not complex, but it requires some development skills. When the data is sent from Azure Stream Analytics to Power BI, I don't have the access to modify the data. I can't customize or edit the data or do some queries. All queries need to be done in the Azure Stream Analytics."
"The collection and analysis of historical data could be better."
"Its features for event imports and architecture could be enhanced."
Apache NiFi is ranked 8th in Compute Service with 10 reviews while Azure Stream Analytics is ranked 3rd in Streaming Analytics with 22 reviews. Apache NiFi is rated 7.8, while Azure Stream Analytics is rated 8.2. The top reviewer of Apache NiFi writes "Allows the creation and use of custom functions to achieve desired functionality but limitation in handling monthly transactions due to a lack of partitioning for dates". On the other hand, the top reviewer of Azure Stream Analytics writes "Easy to set up and user-friendly, but could be priced better". Apache NiFi is most compared with Google Cloud Dataflow, AWS Lambda, Apache Spark, Apache Storm and AWS Fargate, whereas Azure Stream Analytics is most compared with Amazon Kinesis, Databricks, Amazon MSK, Apache Flink and AWS Lambda.
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