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Apache Pulsar vs SAS Event Stream Processing comparison

 

Comparison Buyer's Guide

Executive Summary

Review summaries and opinions

We asked business professionals to review the solutions they use. Here are some excerpts of what they said:
 

Categories and Ranking

Apache Pulsar
Ranking in Streaming Analytics
20th
Average Rating
8.0
Reviews Sentiment
6.2
Number of Reviews
1
Ranking in other categories
No ranking in other categories
SAS Event Stream Processing
Ranking in Streaming Analytics
26th
Average Rating
8.0
Reviews Sentiment
6.7
Number of Reviews
1
Ranking in other categories
No ranking in other categories
 

Mindshare comparison

As of April 2026, in the Streaming Analytics category, the mindshare of Apache Pulsar is 2.8%, up from 2.0% compared to the previous year. The mindshare of SAS Event Stream Processing is 0.9%, up from 0.5% compared to the previous year. It is calculated based on PeerSpot user engagement data.
Streaming Analytics Mindshare Distribution
ProductMindshare (%)
Apache Pulsar2.8%
SAS Event Stream Processing0.9%
Other96.3%
Streaming Analytics
 

Featured Reviews

it_user1087029 - PeerSpot reviewer
Solution Architect at Vlaanderen connect.
The solution can mimic other APIs without changing a line of code
The solution operates as a classic message broker but also as a streaming platform. It operates differently than a traditional streaming platform with storage and computing handled separately. It scales easier and better than Kafka which can be stubborn. You can even make it act like Kafka because it understands Kafka APIs. There are even companies that will sell you Kafka but underneath it is Apache Pulsar. The solution is very compatible because it can mimic other APIs without changing a line of code.
Roi Jason Buela - PeerSpot reviewer
Lead Technical Consultant at Thakral One
A solution with useful windowing features and great for operations and marketing
The persistence could be better. Although ESP is designed for in-memory processing, it would be better if the solution is enhanced or improved on the persistence of the data that is kept in the memory. For example, if one server goes down and the information is stored in the memory, it is lost. Therefore, the persistence needs to be improved so that if there are more cases where the server is down, the information and data can still be intact.

Quotes from Members

We asked business professionals to review the solutions they use. Here are some excerpts of what they said:
 

Pros

"The solution operates as a classic message broker but also as a streaming platform."
"The solution operates as a classic message broker but also as a streaming platform."
"The solution is beneficial on an enterprise level."
"The solution is beneficial on an enterprise level."
 

Cons

"Documentation is poor because much of it is in Chinese with no English translation."
"Documentation is poor because much of it is in Chinese with no English translation."
"The persistence could be better."
"The persistence could be better."
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Top Industries

By visitors reading reviews
Financial Services Firm
16%
Comms Service Provider
9%
Government
9%
Insurance Company
7%
No data available
 

Company Size

By reviewers
Large Enterprise
Midsize Enterprise
Small Business
No data available
No data available
 

Overview

 

Sample Customers

Information Not Available
Honda, HSBC, Lufthansa, Nestle, 89Degrees.
Find out what your peers are saying about Databricks, Amazon Web Services (AWS), Microsoft and others in Streaming Analytics. Updated: March 2026.
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