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.
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TIBCO Rendezvous
Score 6.2 out of 10
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TIBCO's Rendezvous is message oriented middleware. The software uses messages to enable distributed application programs to communicate across a wide variety of hardware platforms and programming languages.
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.
TIBCO Rendezvous is a fast and reliable mode of communication, although they are already outdated by TIBCO FTL, which is even more faster and reliable than it's predecessor. They are more suitable for communication between the TIBCO products as all the TIBCO suite of products support the TIBCO Rendezvous. They are more widely used by banks and stock ticker applications to broadcast the ticker information. Most of the applications support Java JMS mode easily and out of the box than the TIBCO Rendezvous. Hence the TIBCO software themselves have their own version of the JMS server called Tibco EMS ( Tibco Enterprise messaging service).
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).
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
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
Attending an official TIBCO classroom training, where you can have an active participation with an expert teacher, you can find the answers to all yours needs. In any case, if you are not satisfied on your requests, the teacher takes the time to find the best solution.
I had the opportunity to attend one and I could learn all features I needed for my business: now I can say TIBCO Rendezvous is very usable.
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.
I never needed support for TIBCO Rendezvous. I always used it without any issue and until now I don't remember some situations where it interrupted its 24/7 uptime.
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.
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.
All a non-TIBCO based applications need to use the TIBCO Rendezvous APIs and reprogrammed to communicate with other application using the Tibco Rendezvous.
All applications and enterprises need to have an enterprise license to communicate with each other.
TIBCO offers their Rendezvous APIs in various programming languages. Hence any application can use these APIs to start using the Tibco Rendezvous. Although most application prefers not to as TIBCO Rendezvous is TIBCO 's closely guarded recipe.