Software Alternatives, Accelerators & Startups

Google App Engine VS Apache Mesos

Compare Google App Engine VS Apache Mesos and see what are their differences

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Google App Engine logo Google App Engine

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

Apache Mesos logo Apache Mesos

Apache Mesos abstracts resources away from machines, enabling fault-tolerant and elastic distributed systems to easily be built and run effectively.
  • Google App Engine Landing page
    Landing page //
    2023-10-17
  • Apache Mesos Landing page
    Landing page //
    2018-09-30

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.

Apache Mesos features and specs

  • Scalability
    Apache Mesos is designed to scale to thousands of nodes, making it ideal for large-scale distributed systems.
  • Resource Isolation
    Mesos uses containerization techniques (like Docker and Mesos containers) to provide resource isolation, ensuring applications run in their own secure environments.
  • Fault Tolerance
    The framework is built with fault tolerance in mind. It continuously monitors the health of all nodes and can move tasks from failing nodes to healthy ones.
  • Multi-Framework Support
    Mesos can manage multiple types of workloads through different frameworks like Apache Spark, Apache Hadoop, and Kubernetes simultaneously on the same cluster.
  • Resource Efficient
    It provides fine-grained resource allocation, allowing multiple applications to share a single cluster, which leads to more efficient resource utilization.

Possible disadvantages of Apache Mesos

  • Steep Learning Curve
    Setting up and managing a Mesos cluster can be complex and requires a thorough understanding of the framework and its components.
  • Operational Complexity
    Mesos requires additional components like Marathon (for container orchestration) which adds to the operational overhead.
  • Maturity
    While Mesos is a robust system, it may not be as mature or feature-rich as some cloud-native solutions like Kubernetes, which have seen wider adoption.
  • Community Support
    As Mesos is somewhat overshadowed by Kubernetes, it has a smaller community and fewer third-party integrations compared to more popular orchestration tools.
  • Ecosystem Integration
    Many new-age DevOps tools and CI/CD pipelines are primarily designed with Kubernetes in mind, which might result in limited integration capabilities with Mesos.

Analysis of Google App Engine

Overall verdict

  • Google App Engine is generally considered a good choice for developers looking for a serverless platform to deploy their applications quickly without managing underlying infrastructure. Its ease of use, scalability, and integration with Google's ecosystem make it a strong option, especially for projects expecting to scale significantly or require integration with other Google Cloud services.

Why this product is good

  • Google App Engine is a fully managed serverless platform that allows developers to build scalable web applications and mobile backends. It abstracts away infrastructure management, handles scaling automatically, and offers integration with other Google Cloud services, providing a high degree of flexibility and efficiency. Its key strengths include support for multiple programming languages, built-in security features, and seamless connectivity to Google's machine learning and data analytics tools.

Recommended for

    Google App Engine is recommended for developers building web applications who prefer a Platform as a Service (PaaS) model, startups who need a solution that can grow with them without worrying about scaling issues, teams wanting to leverage Google's robust data and analytics offerings, and businesses that require a global reach with reliable performance.

Analysis of Apache Mesos

Overall verdict

  • Apache Mesos is a strong choice for organizations looking for a scalable and flexible resource management system, especially if they have diverse workloads that require efficient orchestration. However, its complexity might pose a challenge for smaller teams or use cases that do not require such extensive features.

Why this product is good

  • Apache Mesos is known for its ability to abstract the entire data center into a single pool of resources, thus simplifying resource management and allocation for distributed systems. It allows for efficient sharing of resources across different applications and offers strong support for container orchestration, microservices, and big data applications. Mesos is highly adaptable and can work with a variety of different workload types, making it suitable for diverse environments.

Recommended for

  • Large organizations with complex infrastructure needs.
  • Teams that require high scalability and flexibility.
  • Projects that involve big data frameworks like Apache Spark or Hadoop.
  • Development environments necessitating custom resource scheduling.

Google App Engine videos

Get to know Google App Engine

More videos:

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

Apache Mesos videos

Reactive Stream Processing Using Apache Mesos

Category Popularity

0-100% (relative to Google App Engine and Apache Mesos)
Cloud Computing
100 100%
0% 0
Developer Tools
31 31%
69% 69
Cloud Hosting
100 100%
0% 0
Containers As A Service
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 Apache Mesos

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...

Apache Mesos Reviews

Docker Alternatives
Another Docker alternative is Apache Mesos. This tool is designed to leverage the features of modern kernels in order to carry out functions like resource isolation, prioritization, limiting & accounting. These functions are generally carried out by groups in the Linux or zones in the Solaris. What Mesos does is, it provides isolation for the Memory, I/O devices, file...
Source: www.educba.com

Social recommendations and mentions

Based on our record, Google App Engine should be more popular than Apache Mesos. It has been mentiond 32 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 (32)

  • Unlocking the Cloud: Your Essential Guide to IaaS, PaaS, and SaaS Models
    Google App Engine - Google's fully managed platform for building scalable web and mobile backends. - Source: dev.to / 3 months ago
  • 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 / 9 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 / 11 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 / 12 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 / over 1 year ago
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Apache Mesos mentions (11)

  • Erlang's not about lightweight processes and message passing
    Erlang, OTP, and the BEAM offer much more than just behaviours. The VM is similar to a virtual kernel with supervisor, isolated processes, and distributed mode that treats multiple (physical or virtual) machines as a single pool of resources. OTP provides numerous useful modes, such as Mnesia (database) and atomic counters/ETS tables (for caching), among others. The runtime also supports bytecode hot-reloading, a... - Source: Hacker News / 6 months ago
  • Kubernetes Simplified: A Comprehensive Introduction for Beginners
    Apache Mesos, a robust cluster manager, excels at handling diverse workloads beyond just containers, offering flexibility for organizations with varying needs. - Source: dev.to / about 1 year ago
  • Containers Orchestration and Kubernetes
    Even though this article will be focused on Kubernetes I want to mention that there are multiple container orchestration platforms such as Mesos, Docker Swarm, OpenShift, Rancher, Hashicorp Nomad, etc. - Source: dev.to / over 1 year ago
  • eBPF, sidecars, and the future of the service mesh
    I worked at several Bay Area startups, mainly in NLP and machine learning roles. I was part of a company called PowerSet, which was building a natural language processing engine and was acquired by Microsoft. I then joined Twitter in its early days, around 2010, when it had about 200 employees. I started on the AI side but transitioned to infrastructure because I found it more satisfying and challenging. We were... - Source: dev.to / over 1 year ago
  • Upgrading Hundreds of Kubernetes Clusters
    When we adopted Kubernetes at Criteo, we encountered initial hurdles. In 2018, Kubernetes operators were still new, and there was internal competition from Mesos. We addressed these challenges by validating Kubernetes performance for our specific needs and building custom Chef recipes, StatefulSet hooks, and startup scripts. - Source: dev.to / over 1 year ago
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What are some alternatives?

When comparing Google App Engine and Apache Mesos, 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.

Kubernetes - Kubernetes is an open source orchestration system for Docker containers

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

Docker - Docker is an open platform that enables developers and system administrators to create distributed applications.

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.

Charity Engine - Charity Engine takes enormous, expensive computing jobs and chops them into 1000s of small pieces...