Apache Camel vs. Apache Kafka vs. Mule ESB

Message brokering across different systems, with transactionality and the ability to have fine tuned control over what happens using Java (or other languages), instead of a heavy, proprietary languages. One situation that it doesn't fit very well (as far as I have experienced) is when your workflow requires significant data mapping. While possible when using Java tooling, some other visual data mapping tools in other integration frameworks are easier to work with.

Incentivized

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.

If you’re bringing anything into Salesforce you should just invest now into Mule, you will get your money’s worth and find a myriad of uses to build APIs between many other systems. Once you build a component you can easily reuse it as a building block to attach to another source/destination. This makes it easy to ramp up quickly and spread usage of Mule throughout your enterprise. A good value for medium to large companies, but probably cheaper to outsource your job to a consulting firm if you are smaller.

Incentivized

• Camel has an easy learning curve. It is fairly well documented and there are about 5-6 books on Camel.
• There is a large user group and blogs devoted to all things Camel and the developers of Camel provide quick answers and have also been very quick to patch Camel, when bugs are reported.
• Camel integrates well with well known frameworks like Spring, and other middleware products like Apache Karaf and Servicemix.
• There are over 150 components for the Camel framework that help integrate with diverse software platforms.
• Camel is also good for creating microservices.

Incentivized

• 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).

Incentivized

• It is best suited for Rest API development. Mule ESB uses RAML as an API descriptor which is less complex and easy to understand. RAML is an open standard majorly supported by Mulesoft. Once RAML is developed, it is very easy (a few clicks)to create flows corresponding to the resources defined in the RAML. One can also include JSON schema validation in RAML, and with the use of APIkit router, Mule ESB makes the request validation very easy (it's automatic basically.)
• Mule ESB comes with a large spectrum of community and enterprise connectors. We have connectors for all the major platforms like Facebook, Twitter, Salesforce, SAP, etc. This enables Mule ESB to integrate with the other systems in a faster and more robust way. Mule ESB has many components to fulfill the requirements of each integration (for example batch processing, parallel processing, choice, etc.)
• Mule API gateway is one of the best tools (modules) of Mulesoft's offering. It supports API governance and management very well. One can easily enforce policies on their APIs with API gateway. It enables some of the must-have features in an API solution (i.e. throttling, oAuth, access levels, etc.)
• Implementing a CI/CD (DevOps) environment for Mule ESB is a very easy task. Mule majorly uses MAVEN as its build tool, which in turn makes it best suitable for CI/CD approach. Mule also provides MAVEN plugins for auto deployments to the servers. Mule also has a best Unit testing module which is MUnit. MUnit can be used for both Unit and Functional testing, and it is easy to write and generates coverage reports in various formats.

Incentivized

• didn't work well when our developers tried to transform heavy data sets
• Apache Camel's whole logic is based on java so team needs to have a great skill set in java
• if there are a handful of workflows then Apache Camel's full potential can't be realized

Incentivized

• 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

• Make sure to not over-engineer shared components. It can complicate development
• Create a roadmap for where you are going - if not, you may miss components
• I suggest getting support, otherwise it could be a difficult learning curve

Incentivized

Kafka is quickly becoming core product of the organization, indeed it is replacing older messaging systems. No better alternatives found yet

Incentivized

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

Incentivized

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.

Incentivized

If you are looking for a Java-based open source low cost equivalent to webMethods or Azure Logic Apps, Apache Camel is an excellent choice as it is mature and widely deployed, and included in many vendored Java application servers too such as Redhat JBoss EAP. Apache Camel is lacking on the GUI tooling side compared to commercial products such as webMethods or Azure Logic Apps.

Incentivized

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.

Incentivized

It doesn't have API . We have to go for another API manager. But in Mule, it has both API manager and ESB

Incentivized

• Very fast time to market in that so many components are available to use immediately.
• Error handling mechanisms and patterns of practice are robust and easy to use which in turn has made our application more robust from the start, so fewer bugs.
• However, testing and debugging routes is more challenging than working is standard Java so that takes more time (less time than writing the components from scratch).
• Most people don't know Camel coming in and many junior developers find it overwhelming and are not enthusiastic to learn it. So finding people that want to develop/maintain it is a challenge.

Incentivized

• 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.

Incentivized

• Overall a great tool for complex integrations

Incentivized