AWS Batch vs Apache OpenWhisk

Overview

AWS Batch

Stacks84

Followers251

Votes6

Apache OpenWhisk

Stacks58

Followers149

Votes7

AWS Batch vs Apache OpenWhisk: What are the differences?

Pricing Model: One key difference between AWS Batch and Apache OpenWhisk is their pricing model. AWS Batch follows a pay-as-you-go pricing model, where users pay for the computing resources they consume. In contrast, Apache OpenWhisk's pricing is based on the number of invocations and memory consumption, allowing for better cost predictability for users.
Service Architecture: Another important distinction between the two platforms is their service architecture. AWS Batch is a fully managed service provided by AWS, simplifying the process for users to run batch computing workloads. On the other hand, Apache OpenWhisk is an open-source serverless platform that can be deployed on various cloud environments, offering more flexibility in terms of where workloads can run.
Integration with Other AWS Services: AWS Batch has seamless integration with other AWS services, such as Amazon S3 and Amazon EC2, making it easier for users to build and run batch computing workflows. Apache OpenWhisk, although it can be integrated with various services, may require more effort in setting up and configuring connections with different services.
Supported Programming Languages: AWS Batch supports a wide range of programming languages, allowing users to choose the language that best fits their use case. On the other hand, Apache OpenWhisk has support for popular programming languages like Python, Node.js, and Swift, but may not be as extensive as AWS Batch in terms of language support.
Event-Driven Workflow Automation: Apache OpenWhisk is specifically designed for event-driven workflow automation, where functions are triggered by specific events or stimuli. This makes it well-suited for applications that require seamless integration between different components and services. AWS Batch, on the other hand, is more focused on batch computing workloads, making it ideal for data processing and analytical tasks that do not rely on real-time event triggers.

In Summary, AWS Batch and Apache OpenWhisk differ in their pricing model, service architecture, integration with other services, supported programming languages, and focus on event-driven workflow automation.

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Detailed Comparison

AWS Batch	Apache OpenWhisk
It enables developers, scientists, and engineers to easily and efficiently run hundreds of thousands of batch computing jobs on AWS. It dynamically provisions the optimal quantity and type of compute resources (e.g., CPU or memory optimized instances) based on the volume and specific resource requirements of the batch jobs submitted.	OpenWhisk is an open source serverless platform. It is enterprise grade and accessible to all developers thanks to its superior programming model and tooling. It powers IBM Cloud Functions, Adobe I/O Runtime, Naver, Nimbella among others.
-	Serverless functions;FaaS;Fine-grained resource consumption;Use any language;Containers as functions; service;Functions-as-a-Service;Function composition;Step Functions;Docker;Kubernetes;Open source community;Apache
Statistics
Stacks 84	Stacks 58
Followers 251	Followers 149
Votes 6	Votes 7
Pros & Cons
Pros 3 Containerized 3 Scalable Cons 3 More overhead than lambda 1 Image management	Pros 4 You are not tied to a provider. IBM available however 3 Still exploring... its just intresting
Integrations
No integrations available	Node.js Visual Studio Code JavaScript Python npm Kubernetes Docker Swift Java Slack

What are some alternatives to AWS Batch, Apache OpenWhisk?

AWS Lambda

AWS Lambda is a compute service that runs your code in response to events and automatically manages the underlying compute resources for you. You can use AWS Lambda to extend other AWS services with custom logic, or create your own back-end services that operate at AWS scale, performance, and security.

Azure Functions

Azure Functions is an event driven, compute-on-demand experience that extends the existing Azure application platform with capabilities to implement code triggered by events occurring in virtually any Azure or 3rd party service as well as on-premises systems.

Google Cloud Run

A managed compute platform that enables you to run stateless containers that are invocable via HTTP requests. It's serverless by abstracting away all infrastructure management.

Serverless

Build applications comprised of microservices that run in response to events, auto-scale for you, and only charge you when they run. This lowers the total cost of maintaining your apps, enabling you to build more logic, faster. The Framework uses new event-driven compute services, like AWS Lambda, Google CloudFunctions, and more.

Google Cloud Functions

Construct applications from bite-sized business logic billed to the nearest 100 milliseconds, only while your code is running

Knative

Knative provides a set of middleware components that are essential to build modern, source-centric, and container-based applications that can run anywhere: on premises, in the cloud, or even in a third-party data center

OpenFaaS

Serverless Functions Made Simple for Docker and Kubernetes

Nuclio

nuclio is portable across IoT devices, laptops, on-premises datacenters and cloud deployments, eliminating cloud lock-ins and enabling hybrid solutions.

Cloud Functions for Firebase

Cloud Functions for Firebase lets you create functions that are triggered by Firebase products, such as changes to data in the Realtime Database, uploads to Cloud Storage, new user sign ups via Authentication, and conversion events in Analytics.

Fission

Write short-lived functions in any language, and map them to HTTP requests (or other event triggers). Deploy functions instantly with one command. There are no containers to build, and no Docker registries to manage.

Related Comparisons

AWS Batch vs Apache OpenWhisk: What are the differences?

Pricing Model: One key difference between AWS Batch and Apache OpenWhisk is their pricing model. AWS Batch follows a pay-as-you-go pricing model, where users pay for the computing resources they consume. In contrast, Apache OpenWhisk's pricing is based on the number of invocations and memory consumption, allowing for better cost predictability for users.
Service Architecture: Another important distinction between the two platforms is their service architecture. AWS Batch is a fully managed service provided by AWS, simplifying the process for users to run batch computing workloads. On the other hand, Apache OpenWhisk is an open-source serverless platform that can be deployed on various cloud environments, offering more flexibility in terms of where workloads can run.
Integration with Other AWS Services: AWS Batch has seamless integration with other AWS services, such as Amazon S3 and Amazon EC2, making it easier for users to build and run batch computing workflows. Apache OpenWhisk, although it can be integrated with various services, may require more effort in setting up and configuring connections with different services.
Supported Programming Languages: AWS Batch supports a wide range of programming languages, allowing users to choose the language that best fits their use case. On the other hand, Apache OpenWhisk has support for popular programming languages like Python, Node.js, and Swift, but may not be as extensive as AWS Batch in terms of language support.
Event-Driven Workflow Automation: Apache OpenWhisk is specifically designed for event-driven workflow automation, where functions are triggered by specific events or stimuli. This makes it well-suited for applications that require seamless integration between different components and services. AWS Batch, on the other hand, is more focused on batch computing workloads, making it ideal for data processing and analytical tasks that do not rely on real-time event triggers.

AWS Batch vs Apache OpenWhisk

Overview