Apache Camel vs. Google Cloud Run vs. IBM Cloud Kubernetes Service

Overview
ProductRatingMost Used ByProduct SummaryStarting Price
Apache Camel
Score 7.5 out of 10
N/A
Apache Camel is an open source integration platform.N/A
Google Cloud Run
Score 8.7 out of 10
N/A
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.N/A
IBM Cloud Kubernetes Service
Score 7.9 out of 10
Mid-Size Companies (51-1,000 employees)
IBM Cloud Kubernetes Service is a managed Kubernetes offering, delivering user tools and built-in security for rapid delivery of applications that users can bind to cloud services related to IBM Watson®, IoT, DevOps and data analytics. As a certified K8s provider, IBM Cloud Kubernetes Service provides intelligent scheduling, self-healing, horizontal scaling, service discovery and load balancing, automated rollouts and rollbacks, and secret and configuration management. The Kubernetes…N/A
Pricing
Apache CamelGoogle Cloud RunIBM Cloud Kubernetes Service
Editions & Modules
No answers on this topic
No answers on this topic
No answers on this topic
Offerings
Pricing Offerings
Apache CamelGoogle Cloud RunIBM Cloud Kubernetes Service
Free Trial
NoYesNo
Free/Freemium Version
NoYesYes
Premium Consulting/Integration Services
NoNoYes
Entry-level Setup FeeNo setup feeNo setup feeOptional
Additional Details
More Pricing Information
Community Pulse
Apache CamelGoogle Cloud RunIBM Cloud Kubernetes Service
Considered Multiple Products
Apache Camel

No answer on this topic

Google Cloud Run

No answer on this topic

IBM Cloud Kubernetes Service
Features
Apache CamelGoogle Cloud RunIBM Cloud Kubernetes Service
Container Management
Comparison of Container Management features of Product A and Product B
Apache Camel
-
Ratings
Google Cloud Run
7.3
17 Ratings
11% below category average
IBM Cloud Kubernetes Service
8.0
20 Ratings
2% below category average
Security and Isolation00 Ratings8.117 Ratings8.020 Ratings
Container Orchestration00 Ratings7.716 Ratings8.520 Ratings
Cluster Management00 Ratings6.41 Ratings7.820 Ratings
Storage Management00 Ratings2.71 Ratings7.920 Ratings
Resource Allocation and Optimization00 Ratings8.517 Ratings8.020 Ratings
Discovery Tools00 Ratings7.413 Ratings7.819 Ratings
Update Rollouts and Rollbacks00 Ratings8.316 Ratings7.720 Ratings
Self-Healing and Recovery00 Ratings8.614 Ratings8.318 Ratings
Analytics, Monitoring, and Logging00 Ratings8.117 Ratings8.220 Ratings
User Ratings
Apache CamelGoogle Cloud RunIBM Cloud Kubernetes Service
Likelihood to Recommend
7.9
(11 ratings)
8.6
(17 ratings)
7.9
(86 ratings)
Likelihood to Renew
-
(0 ratings)
9.0
(1 ratings)
8.9
(16 ratings)
Usability
-
(0 ratings)
7.7
(2 ratings)
8.7
(16 ratings)
Availability
-
(0 ratings)
8.0
(1 ratings)
9.1
(1 ratings)
Performance
-
(0 ratings)
8.0
(1 ratings)
9.1
(1 ratings)
Support Rating
-
(0 ratings)
-
(0 ratings)
7.7
(4 ratings)
Online Training
-
(0 ratings)
-
(0 ratings)
8.7
(15 ratings)
Implementation Rating
-
(0 ratings)
8.0
(1 ratings)
7.6
(3 ratings)
Configurability
-
(0 ratings)
8.0
(1 ratings)
-
(0 ratings)
Contract Terms and Pricing Model
-
(0 ratings)
8.0
(1 ratings)
-
(0 ratings)
Product Scalability
-
(0 ratings)
8.0
(1 ratings)
1.0
(1 ratings)
Professional Services
-
(0 ratings)
8.0
(1 ratings)
-
(0 ratings)
Vendor post-sale
-
(0 ratings)
8.0
(1 ratings)
-
(0 ratings)
Vendor pre-sale
-
(0 ratings)
9.0
(1 ratings)
-
(0 ratings)
User Testimonials
Apache CamelGoogle Cloud RunIBM Cloud Kubernetes Service
Likelihood to Recommend
Apache
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.
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Google
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.
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IBM
IBM Cloud Kubernetes Service also stands out in environments where the workloads vary continuously and require befitting scale. The product excels particularly in microservices structures, wherein the companies would harness the capacity for container orchestration and automated scaling. Still, it may face the challenges due to monolith applications that have not been originally developed for using container technology.
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Pros
Apache
  • 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.
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Google
  • Auto scaling is the best one
  • provide direct VPC connectivity and rigid network
  • Cloud SQL and Pub/Sub services
  • Handling latency issues
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IBM
  • IBM has a strong focus on serverless and Kubernetes. This shows in the platform. Deploying containers to Kubernetes was very easy.
  • Deploying a Kubernetes cluster through the GUI is very easy and quick. On top of that, IBM Cloud offers a single node cluster for Free.
  • Container Registry is a very good product for managing container images. Integration with Kubernetes was seemless.
  • Portability. To transition from Google Cloud Kubernetes to IBM Cloud Kubernetes took almost no effort. We mostly use the CLI and the standard tools such as kubectl were present.
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Cons
Apache
  • 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
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Google
  • The UI can be made simpler. Currently the UI is bloated and it takes time to find out what you want
  • More integrations with container registry providers (ECR, dockerhub)
  • Better permissions UX. Currently GCP requires service accounts to be used with cloud products, the experience adding/removing permissions is difficult to navigate
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IBM
  • I constantly get this error even when everything is well configured prefect.exceptions.AuthorizationError: [{'path': ['auth_info'], 'message': 'AuthenticationError: Forbidden', 'extensions': {'code': 'UNAUTHENTICATED'}}]
  • Then sometimes the error disapear without changine anything, happened twice to me. Should there be an issue with the authentication service? Please let's improve or let users know why this may be happening.
  • Improve the UX in the browse console when removing many images at once
  • UX on the process of installing KeyCloack operator
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Likelihood to Renew
Apache
No answers on this topic
Google
We definitely need to renew it because we dont own our own infrastructure and storage and we are happy with Cloud Run features
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IBM
We have our application running on a CentOS compartment on IBM Cloud Kubernetes Service. We have been utilizing the help since IBM Cloud initially dispatched. We liked the adaptability and versatility that IBM Cloud Kubernetes Service give us. Since we are tiny, the Kubernetes administration is just utilized at present inside my venture bunch.
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Usability
Apache
No answers on this topic
Google
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.
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IBM
We actually haven't had any real problems in our clusters recently and the results we have gotten from adopting IBM Cloud Kubernetes Service have been beyond even our greatest expectations. The community has helped optimize the use of the system and make it relatively simpler to use.
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Reliability and Availability
Apache
No answers on this topic
Google
Not seen any major issues when we run applications its good
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IBM
IBM's cloud is almost infallible.
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Performance
Apache
No answers on this topic
Google
Initially we felt slow but slowly it picked up and easy to manage
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IBM
IBM's cloud has a site in my conuntry (MEXICO) so the network latency was almost 0
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Support Rating
Apache
No answers on this topic
Google
No answers on this topic
IBM
The self-guided support was solid, and there are plenty of online videos to guide first time users, but I think one area of improvement is a faster way to transfer a large quantity of files from our local machine to the cloud for storage (Aspera)
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Online Training
Apache
No answers on this topic
Google
No answers on this topic
IBM
Online training is really an important resource for using these tools. IBM's help center is rich in useful information and tips. Also, external guides and tutorials are available (e.g. on youtube), but I followed only IBM ones and I had no difficulties.
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Implementation Rating
Apache
No answers on this topic
Google
I was involved in the initial implementation setup, Its easy with the given documentaiton we can do ourself. Not that critical
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IBM
Ease of use. Very intuitive. We have been looking for a product that allows us to orchestrate our docker containers in a way where it allows us to effectively scale our applications to production. It also provides us a way of monitoring all our infrastructure in a very clear concise way.
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Alternatives Considered
Apache
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.
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Google
AWS Lambda supports code zip package, enabling lower cold start time. Also, AWS Lambda pricing is much simpler, easier to understand.
Other than that, the 2 products are very similar, including the Docker image support: the image must be built based on proprietary base image.
Obviously, if your other services are running in GCP, then Google Cloud Run is your only choice for tight integration, & private networking.
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IBM
We mainly selected [IBM Cloud Kubernetes Service] because IBM fabric blockchain service is mostly compatible with it. To have all the infrastructure in a single cloud to get the best output we selected the [IBM Cloud Kubernetes Service].
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Contract Terms and Pricing Model
Apache
No answers on this topic
Google
Not part of purchase.
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IBM
No answers on this topic
Scalability
Apache
No answers on this topic
Google
It has good auto scale feature and reliable also
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IBM
IBM's CKS does not offers automatic autoscaling nor vertical scaling (automatic). Other services like Google Kubernetes Engine scales up and down very well
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Professional Services
Apache
No answers on this topic
Google
We have very good support when needed
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IBM
No answers on this topic
Return on Investment
Apache
  • 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.
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Google
  • Built in support for auto scaling helps reduce operational overhead
  • Any application performance issues can be addressed quickly by allocating more resources while a proper fix can be planned and rolled out later
  • Using Google Cloud Run enables development of microservices which provides granular control for scaling critical services in the platform
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IBM
  • Increased development speed and agility allows to build features faster and more economically.
  • Improved resource utilization helps keep applications running very efficiently, which saves on cloud service expenses.
  • Scalability and resilience allows for scaling up or down based on demand, which keeps applications running efficiently and more economically.
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ScreenShots