We performed a comparison between Apache Pulsar and Azure Stream Analytics based on real PeerSpot user reviews.
Find out what your peers are saying about Databricks, Amazon Web Services (AWS), Confluent and others in Streaming Analytics."The solution operates as a classic message broker but also as a streaming platform."
"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."
"The integrations for this solution are easy to use and there is flexibility in integrating the tool with Azure Stream Analytics."
"Technical support is pretty helpful."
"The life cycle, report management and crash management features are great."
"We find the query editor feature of this solution extremely valuable for our business."
"Provides deep integration with other Azure resources."
"It provides the capability to streamline multiple output components."
"The way it organizes data into tables and dashboards is very helpful."
"Documentation is poor because much of it is in Chinese with no English translation."
"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."
"Early in the process, we had some issues with stability."
"Its features for event imports and architecture could be enhanced."
"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 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."
"If something goes wrong, it's very hard to investigate what caused it and why."
"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."
Apache Pulsar is ranked 12th in Streaming Analytics with 1 review while Azure Stream Analytics is ranked 4th in Streaming Analytics with 22 reviews. Apache Pulsar is rated 8.0, while Azure Stream Analytics is rated 8.2. The top reviewer of Apache Pulsar writes "The solution can mimic other APIs without changing a line of code". 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 Pulsar is most compared with Apache Flink, Apache Spark Streaming, Amazon Kinesis, Amazon MSK and Google Cloud Dataflow, whereas Azure Stream Analytics is most compared with Amazon Kinesis, Databricks, Amazon MSK, Apache Flink and Apache Storm.
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.