
Rancher
Helm.sh
Docker
Google Kubernetes Engine
Docker Swarm
Amazon AWS
Docker Compose
Kubernetes is an open source orchestration system for Docker containers

AWS Lambda
Fission.io
Nuclio
Google Cloud Run
APeX
Knative
Dataphin
AWS Batch enables developers, scientists, and engineers to easily and efficiently run hundreds of thousands of batch computing jobs on AWS.

Which is more popular?
Based on our record, Kubernetes seems to be a lot more popular than AWS Batch. While we know about 394 links to Kubernetes, we've tracked only 16 mentions of AWS Batch.
Website, pricing, platforms and company facts side by side.
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|---|---|---|
| Website | kubernetes.io | aws.amazon.com |
| Pricing | — | |
| Company | Startup from the United States | — |
| Listed in |
What each product offers, as listed by its team.


Possible disadvantages
Possible disadvantages
An editorial look at what each product does well and who it suits.


Overall verdict
Why this product is good
Recommended for
No analysis of AWS Batch yet.
Walkthroughs and reviews on video.
Kubernetes Documentation
More videos
How AWS Batch Works
More videos
How often each product is chosen within a category, 0–100% relative to the other.


Share your experience with using Kubernetes and AWS Batch. For example, how are they different and which one is better?
External articles and on-site reviews we used to compare the two products.


Rancher RKE is an interface to the command line for Rancher Kubernetes Engine (RKE) and OpenShift. Both are software tools employed to deploy Kubernetes, an open source project that manages containers on several hosts.
Azure Kubernetes Service is a container orchestration platform that offers secure serverless Kubernetes. AKS helps to manage Kubernetes clusters and makes deploying containerized applications so much easier. In...
Google Kubernetes Engine (GKE) is a prominent choice for a Kubernetes alternative. It is provided and managed by Google Cloud, which offers fully managed Kubernetes services.
AWS Batch: This is used for batch computing jobs on AWS resources. It has insane scalability and is well-suited for engineers look to do large compute jobs.
Recommendations tracked on public social media and blogs since March 2021.


Kubernetes and Docker Desktop for the local execution environment. - Source: dev.to / 11 days ago
Suppose you do want the scalability, smooth CI deploys that just make sense, and all your code living in a GitHub repo you control. Welcome to Kubernetes and the 4,000 lines of YAML config that come with it. - Source: dev.to / 16 days ago
> but it's still a singleton instance, so where do you run it? Most hardware doesn't give you enough uptime for what you need here, because what you actually needed was a re-architecture for distribution / failover / whatever, and while... - Source: Hacker News / 3 months ago
Long-running workloads — A single Lambda invocation has a 15-minute maximum, and that applies to synchronous execution. For workloads that need to run longer — heavy video encoding, large data migrations, overnight batch jobs — you'd... - Source: dev.to / 5 months ago
Compute: This is the big one. It's the cost of running EC2 instances with GPUs (like the g5 or p4 series) for model training and deployment. It also includes the compute for services like Amazon SageMaker and AWS Batch. - Source: dev.to / about 1 year ago
After moving off Jenkins, I moved everything to AWS Batch with Fargate. This works quite well, but it is proving to be a little expensive, as I have to pay for:. Source: over 3 years ago
When comparing Kubernetes and AWS Batch, you can also consider the following products.

Open Source Platform for Running a Private Container Service
Compare Rancher to Kubernetes or AWS Batch:



Fission.io is a serverless framework for Kubernetes that supports many concepts such as event triggers, parallel execution, and statelessness.
Compare Fission.io to Kubernetes or AWS Batch:

Docker is an open platform that enables developers and system administrators to create distributed applications.
Compare Docker to Kubernetes or AWS Batch:
