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Google App Engine VS CoCalc

Compare Google App Engine VS CoCalc and see what are their differences

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  2. » Videos
  3. » Reviews
  4. » Alternatives

Google App Engine logo Google App Engine

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

CoCalc logo CoCalc

Collaborative Calculation and Data Science
  • Google App Engine Landing page
    Landing page //
    2023-10-17
  • CoCalc Landing page
    Landing page //
    2023-07-29

CoCalc is a sophisticated online workspace that supports Jupyter notebooks, SageMath worksheets and LaTeX. It is a fully managed Python and R Statistics environments provide a lot of packages/libraries out of the box. It is also possible to edit LaTeX files and R documents right inside your browser. A full Linux terminal and an environment to run graphical applications complete CoCalc as a very versatile platform. Beyond that, CoCalc is made for teaching a class online! Avoid the hassle of installing software on every student's machine and help your students more precisely by collaborating on their notebooks.

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.

CoCalc features and specs

  • Collaboration
    CoCalc offers real-time collaboration, allowing multiple users to work on the same project simultaneously, making it ideal for group projects and teaching.
  • Integration with Jupyter Notebooks
    It supports Jupyter Notebooks, which are popular for data analysis and scientific computing, allowing users to easily share and execute their code.
  • Reproducibility
    CoCalc provides tools to help ensure that computational results can be easily reproduced, supporting both academic research and educational settings.
  • Wide Range of Tools
    The platform supports several programming languages and tools, including LaTeX, Python, R, and SageMath, offering a versatile working environment.
  • Accessibility
    As a cloud-based platform, CoCalc is accessible from anywhere with an internet connection, allowing users to work remotely.

Possible disadvantages of CoCalc

  • Performance Limitations
    As CoCalc is a cloud-based service, computational resources are shared, which can lead to performance limitations compared to local execution.
  • Cost
    While CoCalc offers a free version, advanced features and more computational resources require a subscription, which may not be affordable for all users.
  • Learning Curve
    New users might face a learning curve when getting started with CoCalc, especially if they are unfamiliar with similar platforms or the supported technologies.
  • Internet Dependency
    Since CoCalc is an online platform, a stable internet connection is necessary, which can be a disadvantage in areas with poor connectivity.
  • Limited Customization
    Compared to setting up a local environment, CoCalc may offer less flexibility in configuring the available software and environment settings.

Google App Engine videos

+ Add

Get to know Google App Engine

More videos:

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

CoCalc videos

+ Add

Real-time collaboration with Jupyter notebooks using CoCalc- William Stein (SageMath, Inc)

More videos:

  • Review - An overview of CoCalc
  • Review - CoCalc: Making open source data analysis software more collaborative

Category Popularity

0-100% (relative to Google App Engine and CoCalc)

Google App Engine

CoCalc

Cloud Computing
100 100%
Cloud Computing
0% 0
Mathematics
0 0%
Mathematics
100% 100
Cloud Hosting
100 100%
Cloud Hosting
0% 0
Python IDE
0 0%
Python IDE
100% 100

User comments

Share your experience with using Google App Engine and CoCalc. For example, how are they different and which one is better?
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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 CoCalc

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...
Source: blog.back4app.com
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...
Source: blog.appscale.com

CoCalc Reviews

Jupyter Notebook & 10 Alternatives: Data Notebook Review [2023]
CoCalc (previously called SageMathCloud) is a cloud-based collaborative platform that includes many of the same features as Jupyter Notebooks as well as a number of new ones.
Source: lakefs.io
12 Best Jupyter Notebook Alternatives [2023] – Features, pros & cons, pricing
CoCalc (formerly known as SageMathCloud) is a cloud-based platform for collaborative computing that offers many of the same features as Jupyter Notebooks, as well as a number of additional capabilities. It supports a wide variety of programming languages, including Python, R, and Julia, and provides access to powerful hardware resources, including GPUs. In addition to its...
Source: noteable.io

Social recommendations and mentions

CoCalc might be a bit more popular than Google App Engine. We know about 31 links to it since March 2021 and only 31 links to Google App Engine. 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 / 5 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 / 7 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 / 11 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 / 11 months ago
View more

CoCalc mentions (31)

  • Hetzner introduces GPU server for AI training
    CoCalc offers On-Demand GPU servers with H100s starting at $2.01 per hour (metered per second) through its integration with Hyperstack... It also has more budget-friendly options, like RTX A4000s at $0.18 per hour. https://cocalc.com/features/compute-server In case you are not familiar, CoCalc is a real-time collaborative environment for education and research that you can access via your web browser at... - Source: Hacker News / 8 months ago
  • Show HN: Adding Mistral Codestral and GPT-4o to Jupyter Notebooks
    Thank you for the list - I think I've come across all of these in my research! I'll try highlight the differences for each. - https://noteable.io/ - as you say, it doesn't exist anymore - https://deepnote.com - I actually mentioned this in the post but in my experience, the UX and features far behind what we've built already. I'd love to hear from anyone who's tried jupyter-ai to give us a shot and let me know... - Source: Hacker News / 11 months ago
  • Show HN: Adding Mistral Codestral and GPT-4o to Jupyter Notebooks
    - https://cocalc.com -- very extensive AI integration everywhere with all the main hosted models, mostly free or pay as you go; also has realtime collaboration. (Disclaimer: I co-authored this.). - Source: Hacker News / 11 months ago
  • Show HN: I made a better Perplexity for developers
    Is there something like this (maybe this?) that provides an API so I can integrate it like any other model into my own website (in this case, https://cocalc.com)? I tried asking the Phind.com devs, but got ignored. - Source: Hacker News / about 1 year ago
  • A list of SaaS, PaaS and IaaS offerings that have free tiers of interest to devops and infradev
    Cocalc.com — (formerly SageMathCloud at cloud.sagemath.com) — Collaborative calculation in the cloud. Browser access to full Ubuntu with built-in collaboration and lots of free software for mathematics, science, data science, preinstalled: Python, LaTeX, Jupyter Notebooks, SageMath, scikitlearn, etc. - Source: dev.to / over 1 year ago
View more

What are some alternatives?

When comparing Google App Engine and CoCalc, 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.

Overleaf - The online platform for scientific writing. Overleaf is free: start writing now with one click. No sign-up required. Great on your iPad.

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

ShareLaTeX - An online LaTeX editor that's easy to use. No installation, real-time collaboration, version control, hundreds of LaTeX templates, and more. Log InRegister - Reset Password - Documentation - .

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.

Colaboratory - Free Jupyter notebook environment in the cloud.

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