Apache Camel is an open source integration platform.
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Google Cloud Run
Score 9.1 out of 10
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Google Cloud Run enables users to build and deploy scalable containerized apps written in any language (including Go, Python, Java, Node.js, .NET, and Ruby) on a fully managed platform. Cloud Run can be paired with other container ecosystem tools, including Google's Cloud Build, Cloud Code, Artifact Registry, and Docker. And it features out-of-the-box integration with Cloud Monitoring, Cloud Logging, Cloud Trace, and Error Reporting to ensure the health of an application.
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Pricing
Apache Camel
Google Cloud Run
Editions & Modules
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No answers on this topic
Offerings
Pricing Offerings
Apache Camel
Google Cloud Run
Free Trial
No
Yes
Free/Freemium Version
No
Yes
Premium Consulting/Integration Services
No
No
Entry-level Setup Fee
No setup fee
No setup fee
Additional Details
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Community Pulse
Apache Camel
Google Cloud Run
Considered Both Products
Apache Camel
Verified User
Anonymous
Chose Apache Camel
Easier to use, better routing system, but perhaps too basic dependant on business needs?
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 …
working with Apache's TomCat server, our developer found it most easy given the UI of Camel to perform integration and data processing tasks. when compared to the other two softwares they felt the need to learn new tools outside of Apache family can be avoided and with kafka, …
We did a comparison of the two products with an example application that tested about 10 distinct EIP pattern. We wrote Camel in XML and Java DSL and SI in XML. This was about 3 years ago. At the time, I found the threading model in SI to be more intuitive and Camel's seda. …
Akka or Spring Integration/ XD are alternatives to Apache Camel and very good frameworks on their own (especially Akka which provides a single threaded illusion).
We chose Apache Camel because it was lightweight, easy to get started with and because it had a groovy DSL since we were a grails shop when we started using it.
Apache Camel has been the integration framework of choice, but I was not the person to make the decision to use it. Compared to other competing products like Tibco Business Works, etc., it is free and open source and its licensing policy is acceptable to the management of Cox.
Esper is only similar in that they both are involved in complex even processing, however Esper's aim is a little more complex and specialized. In general however I found Apache Camel to be much easier to understand, implement and debug, whereas Esper's DSL can get very …
Most of our existing serverless services are deployed on Google to it was a natural choice. With the new artifact registry, its very easy to deploy. With git flows, its now even easier to update the deployment just with a commit to the main branch. The initial trial period is …
The other two obvious cloud providers have direct alternatives: AWS Lambda and Azure Functions. Both were also evaluated briefly (only to validate that they exist); however, the organization had settled on shifting to Google for business reasons, and therefore, the comparison …
Flexibility of features snd customzing options tha optimized the large process and make it on the the go to reuse the same process in multiple deployments ot rollouts
Cloud Run is just so much easier and straightforward to work with than EC2 when it comes to getting a Docker image up and running and serving requests.
Usage is easy and also we have GCP as out cloud partner hence we made up our mind to go with Cloud Run and so far no issues things are going fine with it. and getting good features from Google in it.
The Goolge docs for their products as well as the UI is a lot nicer than AWS or Azure and in general I found it much easy to work with. We selected Google mainly because of startup credits and the support offered but can confidently say we would choose them again without that …
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.
Microservices and RestFul API application as it is fast and reliant. Seamless integration with event triggers such as pubsub or event arc, so you can easily integrate that with usecases with file uploads, database changes, etc. Basically great with short-lived tasks, if however, you have long-running processses, Cloud Run might not be idle for this. For example if you have a long running data processing task, other solutions such as kubeflow pipelines or dataflow are more suited for this kind of tasks. Cloud Run is also stateless, so if you need memory, you will have to connect an external database.
Some of the documentation is a little sparse. In particular, its TCP-based routes use an underlying Netty server, and the interactions between Netty's decoder capabilities and Apache Camel's routing/handler capabilities can be a little muddy at times. In general it is clear which routes and endpoints are the more frequently used and which haven't been given as much attention.
The UI/console is great... the documentation is top-notch for developers, but the CLI itself when you have to script around it is very complex and easy to forget some options... the downside of a generic command line client.
Apache Camel has been the integration framework of choice, but I was not the person to make the decision to use it. Compared to other competing products like Tibco Business Works, etc., it is free and open source and its licensing policy is acceptable to the management of Cox.
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.