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

Azure Functions vs Nimbella

OverviewComparisonAlternatives

Overview

Azure Functions
Azure Functions
Stacks785
Followers705
Votes62
Nimbella
Nimbella
Stacks0
Followers2
Votes0

Nimbella vs Azure Functions: What are the differences?

What is Nimbella? Simple serverless cloud for developers. It is designed specifically to address the challenges developers face in adopting a serverless computing model. There is little doubt that serverless is radically changing the way cloud applications are developed. Stop wasting time on infrastructure management for your Cloud Apps. Build & run stateful apps, frontend + backend, and stateful APIs in minutes.

What is Azure Functions? 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.

Nimbella and Azure Functions can be categorized as "Serverless / Task Processing" tools.

Some of the features offered by Nimbella are:

  • Dedicated secure deployments to your own domains with SSL
  • Stateful, stateless, Jamstack, and long-running applications
  • Structured templates to develop fast and collaborate with your team

On the other hand, Azure Functions provides the following key features:

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

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Detailed Comparison

Azure Functions
Azure Functions
Nimbella
Nimbella

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 designed specifically to address the challenges developers face in adopting a serverless computing model. There is little doubt that serverless is radically changing the way cloud applications are developed. Stop wasting time on infrastructure management for your Cloud Apps. Build & run stateful apps, frontend + backend, and stateful APIs in minutes.

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
Dedicated secure deployments to your own domains with SSL; Stateful, stateless, Jamstack, and long-running applications; Structured templates to develop fast and collaborate with your team; Conveniently access logs and statistics from the terminal or the browser; Build and run front-end and back-end applications using the tools and languages you know; Start with a generous free tier and grow with us
Statistics
Stacks
785
Stacks
0
Followers
705
Followers
2
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#
Kubernetes
Kubernetes
AWS IAM
AWS IAM
Google Cloud Platform
Google Cloud Platform

What are some alternatives to Azure Functions, Nimbella?

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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