We performed a comparison between Apache Pulsar and Apache Spark Streaming 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."
"Apache Spark Streaming has features like checkpointing and Streaming API that are useful."
"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."
"The solution is very stable and reliable."
"The solution is better than average and some of the valuable features include efficiency and stability."
"As an open-source solution, using it is basically free."
"It's the fastest solution on the market with low latency data on data transformations."
"Apache Spark Streaming is versatile. You can use it for competitive intelligence, gathering data from competitors, or for internal tasks like monitoring workflows."
"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."
"Documentation is poor because much of it is in Chinese with no English translation."
"The cost and load-related optimizations are areas where the tool lacks and needs improvement."
"It was resource-intensive, even for small-scale applications."
"In terms of improvement, the UI could be better."
"The solution itself could be easier to use."
"The initial setup is quite complex."
"We would like to have the ability to do arbitrary stateful functions in Python."
"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 service structure of Apache Spark Streaming can improve. There are a lot of issues with memory management and latency. There is no real-time analytics. We recommend it for the use cases where there is a five-second latency, but not for a millisecond, an IOT-based, or the detection anomaly-based. Flink as a service is much better."
Apache Pulsar is ranked 12th in Streaming Analytics with 1 review while Apache Spark Streaming is ranked 8th in Streaming Analytics with 8 reviews. Apache Pulsar is rated 8.0, while Apache Spark Streaming is rated 8.0. 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 Apache Spark Streaming writes "Easy integration, beneficial auto-scaling, and good open-sourced support community". Apache Pulsar is most compared with Apache Flink, Amazon Kinesis, Amazon MSK, Azure Stream Analytics and Google Cloud Dataflow, whereas Apache Spark Streaming is most compared with Amazon Kinesis, Azure Stream Analytics, Spring Cloud Data Flow, Confluent 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.
