We performed a comparison between Apache Spark Streaming 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."The platform’s most valuable feature for processing real-time data is its ability to handle continuous data streams."
"Apache Spark Streaming is versatile. You can use it for competitive intelligence, gathering data from competitors, or for internal tasks like monitoring workflows."
"The solution is better than average and some of the valuable features include efficiency and stability."
"The solution is very stable and reliable."
"Apache Spark Streaming was straightforward in terms of maintenance. It was actively developed, and migrating from an older to a newer version was quite simple."
"Apache Spark Streaming's most valuable feature is near real-time analytics. The developers can build APIs easily for a code-steaming pipeline. The solutions have an ecosystem of integration with other stock services."
"It's the fastest solution on the market with low latency data on data transformations."
"As an open-source solution, using it is basically free."
"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."
"There could be an improvement in the area of the user configuration section, it should be less developer-focused and more business user-focused."
"The cost and load-related optimizations are areas where the tool lacks and needs improvement."
"We would like to have the ability to do arbitrary stateful functions in Python."
"The solution itself could be easier to use."
"Integrating event-level streaming capabilities could be beneficial."
"In terms of improvement, the UI could be better."
"It was resource-intensive, even for small-scale applications."
"The initial setup is quite complex."
"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
Apache Spark Streaming is ranked 8th in Streaming Analytics with 9 reviews while Starburst Enterprise is ranked 14th in Streaming Analytics with 1 review. Apache Spark Streaming is rated 8.0, while Starburst Enterprise is rated 8.0. The top reviewer of Apache Spark Streaming writes "Easy integration, beneficial auto-scaling, and good open-sourced support community". On the other hand, the top reviewer of Starburst Enterprise writes "Handles complex data and improves performance ". Apache Spark Streaming is most compared with Amazon Kinesis, Spring Cloud Data Flow, Azure Stream Analytics, Apache Pulsar and Apache Flink, whereas Starburst Enterprise is most compared with Dremio, Starburst Galaxy, Alteryx, Databricks and Informatica Data Engineering Streaming.
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.