Software Alternatives, Accelerators & Startups

Google App Engine VS AWS Batch

Compare Google App Engine VS AWS Batch and see what are their differences

Google App Engine logo Google App Engine

A powerful platform to build web and mobile apps that scale automatically.

AWS Batch logo AWS Batch

AWS Batch enables developers, scientists, and engineers to easily and efficiently run hundreds of thousands of batch computing jobs on AWS.
  • Google App Engine Landing page
    Landing page //
    2023-10-17
  • AWS Batch Landing page
    Landing page //
    2023-02-21

Google App Engine features and specs

  • Auto-scaling
    Google App Engine automatically scales your application based on the traffic it receives, ensuring that your application can handle varying workloads without manual intervention.
  • Managed environment
    App Engine provides a fully managed environment, covering infrastructure management tasks like server provisioning, patching, monitoring, and managing app versions.
  • Integrated services
    Seamlessly integrates with other Google Cloud services such as Datastore, Cloud SQL, Pub/Sub, and more, offering a comprehensive ecosystem for building and deploying applications.
  • Multiple languages support
    Supports multiple programming languages including Java, Python, PHP, Node.js, Go, Ruby, and .NET, giving developers flexibility in choosing their preferred language.
  • Security
    Offers robust security features including Identity and Access Management (IAM), Cloud Identity, and automated security updates, which help protect your applications from vulnerabilities.
  • Developer productivity
    App Engine allows rapid development and deployment, letting developers focus on writing code without worrying about infrastructure management, thus boosting productivity.
  • Versioning
    Supports versioning of applications, allowing multiple versions of the application to be hosted simultaneously, which helps in A/B testing and rollback capabilities.

Possible disadvantages of Google App Engine

  • Cost
    While you pay for what you use, costs can escalate quickly with high traffic or resource-intensive applications. Detailed cost prediction can be challenging.
  • Vendor lock-in
    Relying heavily on Google App Engine's proprietary services and APIs can make it difficult to migrate applications to other platforms, leading to vendor lock-in.
  • Limited control
    Being a fully managed service, App Engine provides limited control over the underlying infrastructure which might be a limitation for certain advanced use cases.
  • Environment constraints
    Certain restrictions and limitations are imposed on the runtime environment, such as request timeout limits and specific resource quotas, which can affect application performance.
  • Complex debugging
    Debugging issues in a highly abstracted managed environment can be more complex and difficult compared to traditional server-hosted applications.
  • Cold start latency
    Serverless environments like App Engine can suffer from cold start latency, where the initial request triggers a delay as the environment spins up resources.
  • Configuration complexity
    Despite its benefits, configuring and optimizing App Engine for specific scenarios can be more complex than expected, requiring a steep learning curve.

AWS Batch features and specs

  • Scalability
    AWS Batch automatically provisions the optimal quantity and type of compute resources based on the volume and specific resource requirements of the batch jobs submitted.
  • Cost-Effectiveness
    By using AWS Batch, you only pay for the resources you consume, and it provides integration with Spot Instances which can significantly lower costs.
  • No Infrastructure Management
    AWS Batch removes the need to manage server clusters or other infrastructure, allowing users to focus entirely on jobs and workloads.
  • Flexible Job Definitions
    Users can easily specify job definitions to model their machine learning, batch processing, or other computational tasks, allowing for flexibility in resource allocation.
  • Integration with AWS Services
    AWS Batch integrates with various AWS services like Amazon CloudWatch, AWS Lambda, and AWS IAM to provide a comprehensive and secure batch processing solution.

Possible disadvantages of AWS Batch

  • Complexity
    Setting up and configuring AWS Batch can be complex for new users unfamiliar with AWS services, requiring a learning curve.
  • Limited to AWS Ecosystem
    AWS Batch is deeply integrated into the AWS ecosystem, which might not be ideal for users looking for a multi-cloud strategy or those using different cloud service providers.
  • Vendor Lock-in
    Heavy reliance on AWS Batch can lead to vendor lock-in, making it potentially difficult to migrate workloads to other platforms if needed.
  • Potential for Hidden Costs
    While AWS Batch can be cost-effective, there is the potential for unexpected costs if jobs are not efficiently managed or optimized, especially when scaling up resources.
  • Limited Control Over Infrastructure
    Since AWS Batch manages infrastructure automatically, users have limited control over the underlying compute resources, which may not be suitable for all use cases.

Google App Engine videos

Get to know Google App Engine

More videos:

  • Review - Developing apps that scale automatically with Google App Engine

AWS Batch videos

How AWS Batch Works

More videos:

  • Review - Live from the London Loft | AWS Batch: Simplifying Batch Computing in the Cloud
  • Review - AWS re:Invent 2018: AWS Batch & How AQR leverages AWS to Identify New Investment Signals (CMP372)

Category Popularity

0-100% (relative to Google App Engine and AWS Batch)
Cloud Computing
91 91%
9% 9
Cloud Hosting
91 91%
9% 9
Backend As A Service
100 100%
0% 0
Development
0 0%
100% 100

User comments

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Reviews

These are some of the external sources and on-site user reviews we've used to compare Google App Engine and AWS Batch

Google App Engine Reviews

Top 5 Alternatives to Heroku
Google App Engine is fast, easy, but not that very cheap. The pricing is reasonable, and it comes with a free tier, which is great for small projects that are right for beginner developers who want to quickly set up their apps. It can also auto scale, create new instances as needed and automatically handle high availability. App Engine gets a positive rating for performance...
AppScale - The Google App Engine Alternative
AppScale is open source Google App Engine and allows you to run your GAE applications on any infrastructure, anywhere that makes sense for your business. AppScale eliminates lock-in and makes your GAE application portable. This way you can choose which public or private cloud platform is the best fit for your business requirements. Because we are literally the GAE...

AWS Batch Reviews

Python & ETL 2020: A List and Comparison of the Top Python ETL Tools
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.
Source: www.xplenty.com

Social recommendations and mentions

Based on our record, Google App Engine should be more popular than AWS Batch. It has been mentiond 31 times since March 2021. We are tracking product recommendations and mentions on various public social media platforms and blogs. They can help you identify which product is more popular and what people think of it.

Google App Engine mentions (31)

  • Guide to modern app-hosting without servers on Google Cloud
    If Google App Engine (GAE) is the "OG" serverless platform, Cloud Run (GCR) is its logical successor, crafted for today's modern app-hosting needs. GAE was the 1st generation of Google serverless platforms. It has since been joined, about a decade later, by 2nd generation services, GCR and Cloud Functions (GCF). GCF is somewhat out-of-scope for this post so I'll cover that another time. - Source: dev.to / 4 months ago
  • Security in the Cloud: Your Role in the Shared Responsibility Model
    As Windsales Inc. expands, it adopts a PaaS model to offload server and runtime management, allowing its developers and engineers to focus on code development and deployment. By partnering with providers like Heroku and Google App Engine, Windsales Inc. Accesses a fully managed runtime environment. This choice relieves Windsales Inc. Of managing servers, OS updates, or runtime environment behavior. Instead,... - Source: dev.to / 6 months ago
  • Hosting apps in the cloud with Google App Engine in 2024
    Google App Engine (GAE) is their original serverless solution and first cloud product, launching in 2008 (video), giving rise to Serverless 1.0 and the cloud computing platform-as-a-service (PaaS) service level. It didn't do function-hosting nor was the concept of containers mainstream yet. GAE was specifically for (web) app-hosting (but also supported mobile backends as well). - Source: dev.to / 7 months ago
  • Fixing A Broken Deployment to Google App Engine
    In 2014, I took a web development on Udacity that was taught by Steve Huffman of Reddit fame. He taught authentication, salting passwords, the difference between GET and POST requests, basic html and css, caching techniques. It was a fantastic introduction to web dev. To pass the course, students deployed simple python servers to Google App Engine. When I started to look for work, I opted to use code from that... - Source: dev.to / 10 months ago
  • Next.js Deployment: Vercel's Charm vs. GCP's Muscle
    GCP offers a comprehensive suite of cloud services, including Compute Engine, App Engine, and Cloud Run. This translates to unparalleled control over your infrastructure and deployment configurations. Designed for large-scale applications, GCP effortlessly scales to accommodate significant traffic growth. Additionally, for projects heavily reliant on Google services like BigQuery, Cloud Storage, or AI/ML tools,... - Source: dev.to / 10 months ago
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AWS Batch mentions (14)

  • Looking for a decent (self hostable) program to orchestrate scripts, notify on failures, etc
    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: almost 2 years ago
  • Hosting strategy suggestions
    If you're looking for more control over your infrastructure and want to run a full computing environment, EC2 might be the right choice for you. With EC2, you have complete control over the operating system, network, and storage, which can be useful if you need to install custom software or use specific hardware configurations. Additionally, EC2 + Batch processing provide a wider range of instance types, including... Source: about 2 years ago
  • Questions for bioinformatics researchers that use AWS
    AWS Batch is the equivalent of a university cluster you submit to with slurm/sge/lsf/etc. But does not use those schedulers as AWS has their own. Source: about 2 years ago
  • Scheduling "Fetch & Run" Batch Jobs with AWS Batch and CloudWatch Rules
    Developers frequently use batch computing to access significant amounts of processing power. You may perform batch computing workloads in the AWS Cloud with the aid of AWS Batch, a fully managed service provided by AWS. It is a powerful solution that can plan, schedule, and execute containerized batch or machine learning workloads across the entire spectrum of AWS compute capabilities, including Amazon ECS, Amazon... - Source: dev.to / about 2 years ago
  • can you run OS applications in lambda layers?
    As others mentioned, you *can*. It might be easier with AWS Batch (https://aws.amazon.com/batch/) depending on what you're trying to do. Source: over 2 years ago
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What are some alternatives?

When comparing Google App Engine and AWS Batch, you can also consider the following products

Salesforce Platform - Salesforce Platform is a comprehensive PaaS solution that paves the way for the developers to test, build, and mitigate the issues in the cloud application before the final deployment.

Fission.io - Fission.io is a serverless framework for Kubernetes that supports many concepts such as event triggers, parallel execution, and statelessness.

Dokku - Docker powered mini-Heroku in around 100 lines of Bash

Nuclio - Nuclio is an open source serverless platform.

Heroku - Agile deployment platform for Ruby, Node.js, Clojure, Java, Python, and Scala. Setup takes only minutes and deploys are instant through git. Leave tedious server maintenance to Heroku and focus on your code.

AWS Lambda - Automatic, event-driven compute service