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 initial setup is very easy."
"The user interface is good and makes it easy to design very popular workflows."
"We can integrate the tool with other applications easily."
"It's an automated flow, where you can build a flow from source to destination, then do the transformation in between."
"The most valuable feature has been the range of clients and the range of connectors that we could use."
"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 features of this solution are ease of use and implementation."
"Apache NiFi is user-friendly. Its most valuable features for handling large volumes of data include its multitude of integrated endpoints and clients and the ability to create cron jobs to run tasks at regular intervals."
"The solution has a lot of functionality that can be pushed out to companies."
"I like all the connected ecosystems of Microsoft, it is really good with other BI tools that are easy to connect."
"It provides the capability to streamline multiple output components."
"The most valuable features of Azure Stream Analytics are the ease of provisioning and the interface is not terribly complex."
"I like the way the UI looks, and the real-time analytics service is aligned to this. That can be helpful if I have to use this on a production service."
"We use Azure Stream Analytics for simulation and internal activities."
"The most valuable features are the IoT hub and the Blob storage."
"It's a product that can scale."
"More features must be added to the product."
"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."
"There should be a better way to integrate a development environment with local tools."
"The tool should incorporate more tutorials for advanced use cases. It has tutorials for simple use cases."
"I think the UI interface needs to be more user-friendly."
"There are some claims that NiFi is cloud-native but we have tested it, and it's not."
"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."
"Azure Stream Analytics could improve by having clearer metrics as to the scale, more metrics around the data set size that is flowing through it, and performance tuning recommendations."
"Early in the process, we had some issues with stability."
"The solution’s customer support could be improved."
"I would like to have a contact individual at Microsoft."
"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."
"The solution offers a free trial, however, it is too short."
"The solution doesn't handle large data packets very efficiently, which could be improved upon."
"The collection and analysis of historical data could be better."
Apache NiFi is ranked 8th in Compute Service with 11 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.
We monitor all Compute Service 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.