We performed a comparison between Amazon Kinesis and Apache Pulsar 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."Its scalability is very high. There is no maintenance and there is no throughput latency. I think data scalability is high, too. You can ingest gigabytes of data within seconds or milliseconds."
"The solution's technical support is flawless."
"Everything is hosted and simple."
"I have worked in companies that build tools in-house. They face scaling challenges."
"The integration capabilities of the product are good."
"From my experience, one of the most valuable features is the ability to track silent events on endpoints. Previously, these events might have gone unnoticed, but now we can access them within the product range. For example, if a customer reports that their calls are not reaching the portal files, we can use this feature to troubleshoot and optimize the system."
"Setting Amazon Kinesis up is quick and easy; it only takes a few minutes to configure the necessary settings and start using it."
"The solution has the capacity to store the data anywhere from one day to a week and provides limitless storage for us."
"The solution operates as a classic message broker but also as a streaming platform."
"Could include features that make it easier to scale."
"The services which are described in the documentation could use some visual presentation because for someone who is new to the solution the documentation is not easy to follow or beginner friendly and can leave a person feeling helpless."
"Lacks first in, first out queuing."
"Amazon Kinesis involved a more complex setup and configuration than Azure Event Hub."
"One thing that would be nice would be a policy for increasing the number of Kinesis streams because that's the one thing that's constant. You can change it in real time, but somebody has to change it, or you have to set some kind of meter. So, auto-scaling of adding and removing streams would be nice."
"It would be beneficial if Amazon Kinesis provided document based support on the internet to be able to read the data from the Kinesis site."
"In general, the pain point for us was that once the data gets into Kinesis there is no way for us to understand what's happening because Kinesis divides everything into shards. So if we wanted to understand what's happening with a particular shard, whether it is published or not, we could not. Even with the logs, if we want to have some kind of logging it is in the shard."
"Kinesis is good for Amazon Cloud but not as suitable for other cloud vendors."
"Documentation is poor because much of it is in Chinese with no English translation."
Amazon Kinesis is ranked 1st in Streaming Analytics with 24 reviews while Apache Pulsar is ranked 12th in Streaming Analytics with 1 review. Amazon Kinesis is rated 8.0, while Apache Pulsar is rated 8.0. The top reviewer of Amazon Kinesis writes "Used for media streaming and live-streaming data". On the other hand, the top reviewer of Apache Pulsar writes "The solution can mimic other APIs without changing a line of code". Amazon Kinesis is most compared with Azure Stream Analytics, Amazon MSK, Confluent, Apache Flink and PubSub+ Event Broker, whereas Apache Pulsar is most compared with Apache Flink, Apache Spark Streaming, Amazon MSK, Azure Stream Analytics and Google Cloud Dataflow.
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.
