Apache Kafka vs. Red Hat Fuse

Overview
ProductRatingMost Used ByProduct SummaryStarting Price
Apache Kafka
Score 8.4 out of 10
N/A
Apache Kafka is an open-source stream processing platform developed by the Apache Software Foundation written in Scala and Java. The Kafka event streaming platform is used by thousands of companies for high-performance data pipelines, streaming analytics, data integration, and mission-critical applications.N/A
Red Hat Fuse
Score 8.7 out of 10
N/A
Red Hat Fuse (formerly Red Hat JBoss Fuse), based on open source communities like Apache Camel and Apache ActiveMQ, is part of an agile integration solution. Its distributed approach allows teams to deploy integrated services where required. The API-centric, container-based architecture decouples services so they can be created, extended, and deployed independently.N/A
Pricing
Apache KafkaRed Hat Fuse
Editions & Modules
No answers on this topic
No answers on this topic
Offerings
Pricing Offerings
Apache KafkaRed Hat Fuse
Free Trial
NoNo
Free/Freemium Version
NoNo
Premium Consulting/Integration Services
NoNo
Entry-level Setup FeeNo setup feeNo setup fee
Additional Details
More Pricing Information
Community Pulse
Apache KafkaRed Hat Fuse
Top Pros
Top Cons
Best Alternatives
Apache KafkaRed Hat Fuse
Small Businesses

No answers on this topic

No answers on this topic

Medium-sized Companies
IBM MQ
IBM MQ
Score 9.1 out of 10
Anypoint Platform
Anypoint Platform
Score 8.3 out of 10
Enterprises
IBM MQ
IBM MQ
Score 9.1 out of 10
Anypoint Platform
Anypoint Platform
Score 8.3 out of 10
All AlternativesView all alternativesView all alternatives
User Ratings
Apache KafkaRed Hat Fuse
Likelihood to Recommend
8.3
(18 ratings)
9.0
(1 ratings)
Likelihood to Renew
9.0
(2 ratings)
-
(0 ratings)
Usability
10.0
(1 ratings)
-
(0 ratings)
Support Rating
8.4
(4 ratings)
-
(0 ratings)
User Testimonials
Apache KafkaRed Hat Fuse
Likelihood to Recommend
Apache
Apache Kafka is well-suited for most data-streaming use cases. Amazon Kinesis and Azure EventHubs, unless you have a specific use case where using those cloud PaAS for your data lakes, once set up well, Apache Kafka will take care of everything else in the background. Azure EventHubs, is good for cross-cloud use cases, and Amazon Kinesis - I have no real-world experience. But I believe it is the same.
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Red Hat
RedHat Jboss Fuse can be used perfectly to solve application integration or microservices implementation at the departmental or enterprise level. The wide quantity of connectors it provides allows any application to be integrated. Specific technical and programming knowledge is required to build the interfaces, therefore it is not so appropriate for those companies that do not have these employee profiles.
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Pros
Apache
  • Really easy to configure. I've used other message brokers such as RabbitMQ and compared to them, Kafka's configurations are very easy to understand and tweak.
  • Very scalable: easily configured to run on multiple nodes allowing for ease of parallelism (assuming your queues/topics don't have to be consumed in the exact same order the messages were delivered)
  • Not exactly a feature, but I trust Kafka will be around for at least another decade because active development has continued to be strong and there's a lot of financial backing from Confluent and LinkedIn, and probably many other companies who are using it (which, anecdotally, is many).
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Red Hat
  • Hybrid deployment (on-premise, private or public cloud) deployed on OpenShift.
  • More than 200 connectors to connect practically everything.
  • Scalability
  • Pricing and Support
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Cons
Apache
  • Sometimes it becomes difficult to monitor our Kafka deployments. We've been able to overcome it largely using AWS MSK, a managed service for Apache Kafka, but a separate monitoring dashboard would have been great.
  • Simplify the process for local deployment of Kafka and provide a user interface to get visibility into the different topics and the messages being processed.
  • Learning curve around creation of broker and topics could be simplified
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Red Hat
  • Better UI for drag and drop or no-coding integration.
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Likelihood to Renew
Apache
Kafka is quickly becoming core product of the organization, indeed it is replacing older messaging systems. No better alternatives found yet
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Red Hat
No answers on this topic
Usability
Apache
Apache Kafka is highly recommended to develop loosely coupled, real-time processing applications. Also, Apache Kafka provides property based configuration. Producer, Consumer and broker contain their own separate property file
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Red Hat
No answers on this topic
Support Rating
Apache
Support for Apache Kafka (if willing to pay) is available from Confluent that includes the same time that created Kafka at Linkedin so they know this software in and out. Moreover, Apache Kafka is well known and best practices documents and deployment scenarios are easily available for download. For example, from eBay, Linkedin, Uber, and NYTimes.
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Red Hat
No answers on this topic
Alternatives Considered
Apache
I used other messaging/queue solutions that are a lot more basic than Confluent Kafka, as well as another solution that is no longer in the market called Xively, which was bought and "buried" by Google. In comparison, these solutions offer way fewer functionalities and respond to other needs.
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Red Hat
RedHat JBoss Fuse has a strong user community, it's fully opensource and it's easy to license with world-class support. It also has strong integration with AMQP messaging system to bring much more control and visibility over integration patterns, messaging flows, and the overall system topology.
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Return on Investment
Apache
  • Positive: Get a quick and reliable pub/sub model implemented - data across components flows easily.
  • Positive: it's scalable so we can develop small and scale for real-world scenarios
  • Negative: it's easy to get into a confusing situation if you are not experienced yet or something strange has happened (rare, but it does). Troubleshooting such situations can take time and effort.
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Red Hat
  • Improve business process outcomes
  • Improve process agility
  • Reduce integration costs
  • Reduces operations and monitoring costs
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