We performed a comparison between Apache Pulsar and Google Cloud Dataflow 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 don't need a server running all the time while using the tool. It is also easy to setup. The product offers a pay-as-you-go service."
"It is a scalable solution."
"Google Cloud Dataflow is useful for streaming and data pipelines."
"The most valuable features of Google Cloud Dataflow are the integration, it's very simple if you have the complete stack, which we are using. It is overall very easy to use, user-friendly friendly, and cost-effective if you know how to use it. The solution is very flexible for programmers, if you know how to do scripts or program in Python or any other language, it's extremely easy to use."
"The best feature of Google Cloud Dataflow is its practical connectedness."
"The most valuable features of Google Cloud Dataflow are scalability and connectivity."
"The solution allows us to program in any language we desire."
"The product's installation process is easy...The tool's maintenance part is somewhat easy."
"Documentation is poor because much of it is in Chinese with no English translation."
"I would like Google Cloud Dataflow to be integrated with IT data flow and other related services to make it easier to use as it is a complex tool."
"There are certain challenges regarding the Google Cloud Composer which can be improved."
"They should do a market survey and then make improvements."
"Google Cloud Dataflow should include a little cost optimization."
"The technical support has slight room for improvement."
"When I deploy the product in local errors, a lot of errors pop up which are not always caught. The solution's error logging is bad. It can take a lot of time to debug the errors. It needs to have better logs."
"The deployment time could also be reduced."
"Google Cloud Data Flow can improve by having full simple integration with Kafka topics. It's not that complicated, but it could improve a bit. The UI is easy to use but the experience could be better. There are other tools available that do a better job."
Apache Pulsar is ranked 12th in Streaming Analytics with 1 review while Google Cloud Dataflow is ranked 7th in Streaming Analytics with 10 reviews. Apache Pulsar is rated 8.0, while Google Cloud Dataflow is rated 7.8. 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 Google Cloud Dataflow writes "Easy to use for programmers, user-friendly, and scalable". Apache Pulsar is most compared with Apache Flink, Apache Spark Streaming, Amazon Kinesis, Amazon MSK and Aiven for Apache Kafka, whereas Google Cloud Dataflow is most compared with Databricks, Apache NiFi, Amazon MSK, Amazon Kinesis and Starburst Enterprise.
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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.
