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  4. Code Collaboration Version Control
  5. AWS Batch vs Beanstalk

AWS Batch vs Beanstalk

OverviewComparisonAlternatives

Overview

Beanstalk
Beanstalk
Stacks85
Followers270
Votes51
AWS Batch
AWS Batch
Stacks84
Followers251
Votes6

AWS Batch vs Beanstalk: What are the differences?

Introduction

AWS Batch and Beanstalk are both services provided by Amazon Web Services (AWS) that are used to deploy and manage applications in the cloud. While they may have some similarities, there are key differences between the two that make them suited for different use cases.

  1. Deployment and Management: AWS Batch is a fully managed service that is designed for executing batch computing workloads, whereas AWS Elastic Beanstalk is a platform as a service (PaaS) that provides an easy way to deploy and manage applications.

  2. Application Architecture: AWS Batch is designed for running batch computing workloads, which are typically non-interactive and can be parallelized. On the other hand, Elastic Beanstalk is designed for running web applications that are interactive and require a user interface.

  3. Flexibility and Control: AWS Batch offers more flexibility and control over the underlying infrastructure, allowing users to have fine-grained control over the execution environment and infrastructure resources. Elastic Beanstalk, on the other hand, abstracts away the underlying infrastructure and provides a more simplified deployment and management experience.

  4. Scaling and Autoscaling: With AWS Batch, users have more control over scaling and autoscaling of their compute resources, as they can define their own scaling policies based on workload requirements. Elastic Beanstalk, on the other hand, provides built-in autoscaling capabilities that automatically scale resources based on traffic patterns.

  5. Pricing: AWS Batch is priced based on the resources consumed by batch jobs, including compute resources, storage, and data transfer. Elastic Beanstalk is priced based on the underlying resources provisioned for the application, including compute instances, storage, and data transfer.

  6. Integration with Other Services: AWS Batch integrates well with other AWS services, such as Amazon S3 for storing input and output data, and AWS CloudWatch for monitoring batch jobs. Elastic Beanstalk also integrates with various AWS services, such as Amazon RDS for database management and Amazon SES for email notification.

In summary, AWS Batch is designed for batch computing workloads and offers more control and flexibility over the underlying infrastructure, while Elastic Beanstalk is designed for web applications and provides an easy way to deploy and manage applications with built-in autoscaling capabilities.

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Detailed Comparison

Beanstalk
Beanstalk
AWS Batch
AWS Batch

A single process to commit code, review with the team, and deploy the final result to your customers.

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.

Setup and manage repositories- Import or create Subversion and Git repositories that are instantly available to your team.;Invite team members, partners & clients- Restrict access to certain repos and provide read-only or full read/write permissions.;Browse files and changes- Every version of every file you’ve committed to Beanstalk is just a click away. See a timeline of who made changes and view the differences between revisions. Syntax highlighting for over 70 languages.;Preview, Compare & Share- Instantly preview HTML and image files in Beanstalk, compare versions side by side, and share them with your team, colleagues or clients, even if they don’t have a Beanstalk account.;Code Editing- Make and commit changes directly in the web interface of Beanstalk.;Blame Tool- View the line-by-line history of every file using Beanstalk's blame tool. Quickly see who was responsible for each line of code and which revision it belonged to.;Instantly deploy static assets from Beanstalk to your development, staging and production servers via Amazon S3, Rackspace Cloud Files, Heroku, DreamObjects;
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Statistics
Stacks
85
Stacks
84
Followers
270
Followers
251
Votes
51
Votes
6
Pros & Cons
Pros
  • 14
    Ftp deploy
  • 9
    Deployment
  • 8
    Easy to navigate
  • 4
    Integrations
  • 4
    Code Editing
Pros
  • 3
    Scalable
  • 3
    Containerized
Cons
  • 3
    More overhead than lambda
  • 1
    Image management
Integrations
Amazon S3
Amazon S3
Amazon CloudFront
Amazon CloudFront
Basecamp
Basecamp
Campfire
Campfire
FogBugz
FogBugz
Lighthouse
Lighthouse
Harvest
Harvest
Zendesk
Zendesk
HipChat
HipChat
Bugify
Bugify
No integrations available

What are some alternatives to Beanstalk, AWS Batch?

GitHub

GitHub

GitHub is the best place to share code with friends, co-workers, classmates, and complete strangers. Over three million people use GitHub to build amazing things together.

Bitbucket

Bitbucket

Bitbucket gives teams one place to plan projects, collaborate on code, test and deploy, all with free private Git repositories. Teams choose Bitbucket because it has a superior Jira integration, built-in CI/CD, & is free for up to 5 users.

GitLab

GitLab

GitLab offers git repository management, code reviews, issue tracking, activity feeds and wikis. Enterprises install GitLab on-premise and connect it with LDAP and Active Directory servers for secure authentication and authorization. A single GitLab server can handle more than 25,000 users but it is also possible to create a high availability setup with multiple active servers.

AWS Lambda

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.

RhodeCode

RhodeCode

RhodeCode provides centralized control over distributed code repositories. Developers get code review tools and custom APIs that work in Mercurial, Git & SVN. Firms get unified security and user control so that their CTOs can sleep at night

AWS CodeCommit

AWS CodeCommit

CodeCommit eliminates the need to operate your own source control system or worry about scaling its infrastructure. You can use CodeCommit to securely store anything from source code to binaries, and it works seamlessly with your existing Git tools.

Gogs

Gogs

The goal of this project is to make the easiest, fastest and most painless way to set up a self-hosted Git service. With Go, this can be done in independent binary distribution across ALL platforms that Go supports, including Linux, Mac OS X, and Windows.

Gitea

Gitea

Git with a cup of tea! Painless self-hosted all-in-one software development service, including Git hosting, code review, team collaboration, package registry and CI/CD. It published under the MIT license.

Azure Functions

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

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.

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