Software Alternatives, Accelerators & Startups

Google App Engine VS AWS Step Functions

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

Note: These products don't have any matching categories. If you think this is a mistake, please edit the details of one of the products and suggest appropriate categories.

Google App Engine logo Google App Engine

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

AWS Step Functions logo AWS Step Functions

AWS Step Functions makes it easy to coordinate the components of distributed applications and microservices using visual workflows.
  • Google App Engine Landing page
    Landing page //
    2023-10-17
  • AWS Step Functions Landing page
    Landing page //
    2023-04-29

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 Step Functions features and specs

  • Orchestration
    AWS Step Functions provide a way to coordinate multiple AWS services into serverless workflows, making it easier to build and run distributed applications and microservices.
  • Visual Workflow
    The service offers a visual interface to build, run, and monitor multi-step workflows, allowing for easier debugging and comprehension of complex processes.
  • Error Handling
    Step Functions offer built-in error handling, retry logic, and state management, which simplifies the process of managing failures and ensures more robust applications.
  • Scalability
    As a fully managed service, AWS Step Functions handle the scaling of operations automatically, allowing workflows to scale based on demand without manual intervention.
  • Integration
    Deep integration with other AWS services such as Lambda, ECS, SNS, SQS, and DynamoDB, making it straightforward to build complex, integrated workflows.
  • Cost-Effectiveness
    Pay-as-you-go pricing model means you only pay for each state transition, which can be more cost-effective compared to maintaining your own orchestration layer.
  • Audit and Logging
    Automatically logs the state of each execution, which can be used for auditing, debugging, and monitoring purposes.
  • Serverless
    Being a serverless service, it eliminates the need for server management and scaling concerns, ensuring a simpler operational setup.

Possible disadvantages of AWS Step Functions

  • Complexity
    For simple tasks, the overhead of creating and managing workflows with Step Functions can be excessive compared to using straightforward AWS Lambda functions or other simple services.
  • Cold Start Latency
    Like other serverless services, AWS Step Functions can suffer from cold start latency, especially in low-usage scenarios.
  • Cost
    While the pay-as-you-go model can be cost-effective, for workflows with a high number of state transitions, costs can accumulate quickly, making it potentially expensive.
  • Service Limits
    AWS Step Functions have certain limits, such as the number of active state machines per account and state transition limits, that could impact very large scale operations.
  • Learning Curve
    There can be a significant learning curve associated with mastering the service, particularly for those unfamiliar with AWS or similar orchestration tools.
  • JSON-Based Definitions
    State machines are defined in JSON, which can become complex and less readable when dealing with large workflows involving multiple states.
  • Limited Regional Availability
    As with many AWS services, Step Functions are not available in all regions, which can limit its use for global applications.

Google App Engine videos

Get to know Google App Engine

More videos:

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

AWS Step Functions videos

Orchestrating Distributed Business Workflows with AWS Step Functions - AWS Online Tech Talks

More videos:

  • Review - AWS Step Functions: Parallelism and concurrency in Step Functions and AWS Lambda
  • Review - AWS Step Functions: Workflows for development and testing

Category Popularity

0-100% (relative to Google App Engine and AWS Step Functions)
Cloud Computing
100 100%
0% 0
Workflow Automation
0 0%
100% 100
Cloud Hosting
100 100%
0% 0
Automation
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 Step Functions

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 Step Functions Reviews

Top 8 Apache Airflow Alternatives in 2024
This service suits for many use cases, such as building ETL pipelines, orchestrating microservices, and managing high workloads. AWS Step Functions is particularly efficient when combined with other AWS solutions: Lambda for computing, Dynamo DB for storage, Athena for Analytics, SageMaker for machine learning, etc.
Source: blog.skyvia.com
10 Best Airflow Alternatives for 2024
AWS Step Functions enable the incorporation of AWS services such as Lambda, Fargate, SNS, SQS, SageMaker, and EMR into business processes, Data Pipelines, and applications. Users and enterprises can choose between 2 types of workflows: Standard (for long-running workloads) and Express (for high-volume event processing workloads), depending on their use case.
Source: hevodata.com

Social recommendations and mentions

Based on our record, AWS Step Functions should be more popular than Google App Engine. It has been mentiond 67 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 / 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 / 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 / 11 months ago
View more

AWS Step Functions mentions (67)

  • Create Stateful Serverless Workflows with AWS Step Functions and JSONata
    As an avid user of AWS Step Functions, I've been pleased by several excellent releases over the past few years, including Distributed Map, Express Workflows, Intrinsic functions, TestState, redrive, service integrations, and so many others. Those are all fantastic releases, but in my humble opinion, none of them are as big of a deal as the introduction of JSONata expressions. AWS announced this game-changing... - Source: dev.to / about 1 month ago
  • Automate Email Processing using Event Driven Architecture and Generative AI
    Because the code above enables EventBridge events on the bucket, we can then create a new EventBridge rule to trigger a StepFunction that will then process the emails as follows:. - Source: dev.to / 3 months ago
  • What is AWS Step Functions? - A Complete Guide
    AWS Step Functions is one of those game-changing services that has completely changed how I approach this problem. Today, I want to share my experience with Step Functions and how it can simplify your serverless workflows. - Source: dev.to / 5 months ago
  • Large-scale Data Processing with Step Functions : AWS Project
    The solution uses AWS Step Functions to provides end to end orchestration for processing billions of records with your simulation or transformation logic using AWS Step Functions Distributed Map and Activity features. At the start of the workflow, Step Functions will scale the number of workers to a (configurable) predefined number. It then reads in the dataset and distributes metadata about the dataset in batches... - Source: dev.to / 6 months ago
  • How to invoke a lambda function from your database
    If you need to run long-running jobs, consider using AWS Step Functions in tandem with Lambda functions. - Source: dev.to / 8 months ago
View more

What are some alternatives?

When comparing Google App Engine and AWS Step Functions, 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.

Apache Airflow - Airflow is a platform to programmaticaly author, schedule and monitor data pipelines.

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

Kestra.io - Infinitely scalable, event-driven, language-agnostic orchestration and scheduling platform to manage millions of workflows declaratively in code.

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.

Dagster - The cloud-native open source orchestrator for the whole development lifecycle, with integrated lineage and observability, a declarative programming model, and best-in-class testability.