We performed a comparison between Google Cloud Dataflow and Starburst Enterprise based on real PeerSpot user reviews.
Find out what your peers are saying about Amazon Web Services (AWS), Databricks, Microsoft and others in Streaming Analytics."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."
"The most valuable features of Google Cloud Dataflow are scalability and connectivity."
"The support team is good and it's easy to use."
"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."
"The service is relatively cheap compared to other batch-processing engines."
"The best feature of Google Cloud Dataflow is its practical connectedness."
"We have noticed improvements in performance using Starburst Enterprise. It handles complex data, including reading and partitioning files. We can add a new catalog to Starburst Enterprise by providing connection details and service account information. This allows us to integrate with existing tools, such as the Snowflake database, which we use for data protection in our project."
"The technical support has slight room for improvement."
"The deployment time could also be reduced."
"The authentication part of the product is an area of concern where improvements are required."
"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 solution's setup process could be more accessible."
"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."
"They should do a market survey and then make improvements."
"Google Cloud Dataflow should include a little cost optimization."
"Starburst Enterprise could improve by offering additional features similar to those provided by other SQL query tools. For example, incorporating functionalities like pivot tables would make it more feasible to use."
Earn 20 points
Google Cloud Dataflow is ranked 7th in Streaming Analytics with 10 reviews while Starburst Enterprise is ranked 14th in Streaming Analytics with 1 review. Google Cloud Dataflow is rated 7.8, while Starburst Enterprise is rated 8.0. The top reviewer of Google Cloud Dataflow writes "Easy to use for programmers, user-friendly, and scalable". On the other hand, the top reviewer of Starburst Enterprise writes "Handles complex data and improves performance ". Google Cloud Dataflow is most compared with Databricks, Apache NiFi, Amazon MSK, Amazon Kinesis and Spring Cloud Data Flow, whereas Starburst Enterprise is most compared with Dremio, Starburst Galaxy, Alteryx, Databricks and Apache Spark Streaming.
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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.
