StackShareStackShare
Follow on
StackShare

Discover and share technology stacks from companies around the world.

Follow on

© 2025 StackShare. All rights reserved.

Product

  • Stacks
  • Tools
  • Feed

Company

  • About
  • Contact

Legal

  • Privacy Policy
  • Terms of Service
  1. Stackups
  2. Application & Data
  3. Serverless
  4. Serverless Task Processing
  5. OpenFaaS vs TriggerMesh

OpenFaaS vs TriggerMesh

OverviewComparisonAlternatives

Overview

OpenFaaS
OpenFaaS
Stacks54
Followers234
Votes17
GitHub Stars26.0K
Forks2.0K
TriggerMesh
TriggerMesh
Stacks2
Followers6
Votes0

OpenFaaS vs TriggerMesh: What are the differences?

## Introduction
This Markdown code provides a comparison between OpenFaaS and TriggerMesh in terms of key differences.

1. **Architecture**: OpenFaaS is designed as an open-source serverless framework, allowing for easy deployment of functions, while TriggerMesh is a serverless management platform providing integrations with various cloud providers and orchestrators.
2. **Multi-cloud Support**: OpenFaaS primarily focuses on on-premises and cloud agnostic deployments, whereas TriggerMesh offers seamless support for multiple cloud providers such as AWS, Azure, Google Cloud, and on-premises Kubernetes clusters.
3. **Workflow Automation**: OpenFaaS empowers developers to easily deploy and manage functions with minimal configuration, whereas TriggerMesh enables complex workflows by allowing users to automate the process of connecting event sources and functions through a graphical user interface.
4. **Integration Capabilities**: OpenFaaS provides a simple and straightforward integration process through its CLI tool, while TriggerMesh offers advanced integration capabilities such as event streaming, transformation, and routing using connectors.
5. **Monitoring and Management**: OpenFaaS offers basic monitoring and management capabilities through Prometheus and Grafana, while TriggerMesh provides more comprehensive monitoring tools and dashboards for users to gain insights into their serverless applications.
6. **Scalability and Performance**: OpenFaaS is highly scalable and efficient for small to medium workloads, while TriggerMesh is optimized for more demanding and high-performance serverless applications.

In Summary, the key differences between OpenFaaS and TriggerMesh lie in their architecture, multi-cloud support, workflow automation, integration capabilities, monitoring and management tools, as well as scalability and performance for varying serverless workload requirements.

Share your Stack

Help developers discover the tools you use. Get visibility for your team's tech choices and contribute to the community's knowledge.

View Docs
CLI (Node.js)
or
Manual

Detailed Comparison

OpenFaaS
OpenFaaS
TriggerMesh
TriggerMesh

Serverless Functions Made Simple for Docker and Kubernetes

It provides tools that enable developers to deploy and manage their functions-as-a-service (FaaS) and provide full-lifecycle management of your cloud-native and microservices from a single central console on all of your clouds and on-premise.

-
Easily connect SaaS, cloud, and on-premises applications with serverless and cloud-native architectures; Bring your legacy applications to the cloud and leverage your existing IT investment;Improve developer productivity and provide consistency by integrating all services through a single standard platform
Statistics
GitHub Stars
26.0K
GitHub Stars
-
GitHub Forks
2.0K
GitHub Forks
-
Stacks
54
Stacks
2
Followers
234
Followers
6
Votes
17
Votes
0
Pros & Cons
Pros
  • 5
    Open source
  • 4
    Ease
  • 3
    Autoscaling
  • 2
    Documentation
  • 2
    Community
No community feedback yet
Integrations
Kubernetes
Kubernetes
Docker
Docker
No integrations available

What are some alternatives to OpenFaaS, TriggerMesh?

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.

Azure Functions

Azure Functions

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.

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

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.

Related Comparisons

Bootstrap
Materialize

Bootstrap vs Materialize

Laravel
Django

Django vs Laravel vs Node.js

Bootstrap
Foundation

Bootstrap vs Foundation vs Material UI

Node.js
Spring Boot

Node.js vs Spring-Boot

Liquibase
Flyway

Flyway vs Liquibase