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  1. Stackups
  2. Application & Data
  3. Serverless
  4. Serverless Task Processing
  5. Azure Functions vs stdlib

Azure Functions vs stdlib

OverviewComparisonAlternatives

Overview

Azure Functions
Azure Functions
Stacks785
Followers705
Votes62
stdlib
stdlib
Stacks17
Followers12
Votes0
GitHub Stars3.7K
Forks190

Azure Functions vs stdlib: What are the differences?

Developers describe Azure Functions as "Listen and react to events across your stack". 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. On the other hand, stdlib is detailed as "The Standard Library for Functions as a Service". It is the fastest, easiest way to build infinitely scalable, self-healing APIs. Standard Library is based on Function as a Service ("serverless") architecture, initially popularized by AWS Lambda. You can use Standard Library to build modular, scalable APIs for yourself and other developers in minutes without having to manage servers, gateways, domains, write documentation, or build SDKs. Your development workflow has never been easier - focus on writing code you love, let Standard Library handle everything else.

Azure Functions and stdlib belong to "Serverless / Task Processing" category of the tech stack.

Some of the features offered by Azure Functions are:

  • Easily schedule event-driven tasks across services
  • Expose Functions as HTTP API endpoints
  • Scale Functions based on customer demand

On the other hand, stdlib provides the following key features:

  • Code online — Browser-based editor
  • Version-controlled API releases
  • Easy API sharing and access control

stdlib is an open source tool with 3.64K GitHub stars and 181 GitHub forks. Here's a link to stdlib's open source repository on GitHub.

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Detailed Comparison

Azure Functions
Azure Functions
stdlib
stdlib

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.

It is the fastest, easiest way to build infinitely scalable, self-healing APIs. Standard Library is based on Function as a Service ("serverless") architecture, initially popularized by AWS Lambda. You can use Standard Library to build modular, scalable APIs for yourself and other developers in minutes without having to manage servers, gateways, domains, write documentation, or build SDKs. Your development workflow has never been easier - focus on writing code you love, let Standard Library handle everything else.

Easily schedule event-driven tasks across services;Expose Functions as HTTP API endpoints;Scale Functions based on customer demand;Develop how you want, using a browser-based UI or existing tools;Get continuous deployment, remote debugging, and authentication out of the box
Code online — Browser-based editor;Version-controlled API releases;Easy API sharing and access control;One centralized library for all your APIs;Auto-generated documentation
Statistics
GitHub Stars
-
GitHub Stars
3.7K
GitHub Forks
-
GitHub Forks
190
Stacks
785
Stacks
17
Followers
705
Followers
12
Votes
62
Votes
0
Pros & Cons
Pros
  • 14
    Pay only when invoked
  • 11
    Great developer experience for C#
  • 9
    Multiple languages supported
  • 7
    Great debugging support
  • 5
    Can be used as lightweight https service
Cons
  • 1
    Poor support for Linux environments
  • 1
    Sporadic server & language runtime issues
  • 1
    Not suited for long-running applications
  • 1
    No persistent (writable) file system available
No community feedback yet
Integrations
Azure DevOps
Azure DevOps
Java
Java
Bitbucket
Bitbucket
Node.js
Node.js
Microsoft Azure
Microsoft Azure
GitHub
GitHub
Visual Studio Code
Visual Studio Code
JavaScript
JavaScript
Azure Cosmos DB
Azure Cosmos DB
C#
C#
Ruby
Ruby
Node.js
Node.js
Python
Python

What are some alternatives to Azure Functions, stdlib?

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.

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.

Serverless

Serverless

Build applications comprised of microservices that run in response to events, auto-scale for you, and only charge you when they run. This lowers the total cost of maintaining your apps, enabling you to build more logic, faster. The Framework uses new event-driven compute services, like AWS Lambda, Google CloudFunctions, and more.

Google Cloud Functions

Google Cloud Functions

Construct applications from bite-sized business logic billed to the nearest 100 milliseconds, only while your code is running

Knative

Knative

Knative provides a set of middleware components that are essential to build modern, source-centric, and container-based applications that can run anywhere: on premises, in the cloud, or even in a third-party data center

OpenFaaS

OpenFaaS

Serverless Functions Made Simple for Docker and Kubernetes

Nuclio

Nuclio

nuclio is portable across IoT devices, laptops, on-premises datacenters and cloud deployments, eliminating cloud lock-ins and enabling hybrid solutions.

Apache OpenWhisk

Apache OpenWhisk

OpenWhisk is an open source serverless platform. It is enterprise grade and accessible to all developers thanks to its superior programming model and tooling. It powers IBM Cloud Functions, Adobe I/O Runtime, Naver, Nimbella among others.

Cloud Functions for Firebase

Cloud Functions for Firebase

Cloud Functions for Firebase lets you create functions that are triggered by Firebase products, such as changes to data in the Realtime Database, uploads to Cloud Storage, new user sign ups via Authentication, and conversion events in Analytics.

AWS Batch

AWS Batch

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.

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