Faktory vs Flow-Like
Overview
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.
CLI (Node.js)
Manual
Detailed Comparison
Redis -> Sidekiq == Faktory -> Faktory. Faktory is a server daemon which provides a simple API to produce and consume background jobs. Jobs are a small JSON hash with a few mandatory keys. | Mission-critical automation you can audit, control and run on-prem. No black boxes. No silent failures. No data leaks. Built for teams that cannot afford uncertainty. |
| - | workflow-automation, workflows, local, privacy, agent, agent-builder, automation |
Statistics | |
GitHub Stars 6.0K | GitHub Stars - |
GitHub Forks 236 | GitHub Forks - |
Stacks 7 | Stacks 2 |
Followers 27 | Followers 1 |
Votes 3 | Votes 1 |
Pros & Cons | |
Pros
| No community feedback yet |
Integrations | |
| No integrations available | |
What are some alternatives to Faktory, Flow-Like?
Sidekiq
Sidekiq uses threads to handle many jobs at the same time in the same process. It does not require Rails but will integrate tightly with Rails 3/4 to make background processing dead simple.
Airflow
Use Airflow to author workflows as directed acyclic graphs (DAGs) of tasks. The Airflow scheduler executes your tasks on an array of workers while following the specified dependencies. Rich command lines utilities makes performing complex surgeries on DAGs a snap. The rich user interface makes it easy to visualize pipelines running in production, monitor progress and troubleshoot issues when needed.
Beanstalkd
Beanstalks's interface is generic, but was originally designed for reducing the latency of page views in high-volume web applications by running time-consuming tasks asynchronously.
GitHub Actions
It makes it easy to automate all your software workflows, now with world-class CI/CD. Build, test, and deploy your code right from GitHub. Make code reviews, branch management, and issue triaging work the way you want.
Hangfire
It is an open-source framework that helps you to create, process and manage your background jobs, i.e. operations you don't want to put in your request processing pipeline. It supports all kind of background tasks – short-running and long-running, CPU intensive and I/O intensive, one shot and recurrent.
Apache Beam
It implements batch and streaming data processing jobs that run on any execution engine. It executes pipelines on multiple execution environments.
Zenaton
Developer framework to orchestrate multiple services and APIs into your software application using logic triggered by events and time. Build ETL processes, A/B testing, real-time alerts and personalized user experiences with custom logic.
Resque
Background jobs can be any Ruby class or module that responds to perform. Your existing classes can easily be converted to background jobs or you can create new classes specifically to do work. Or, you can do both.
Luigi
It is a Python module that helps you build complex pipelines of batch jobs. It handles dependency resolution, workflow management, visualization etc. It also comes with Hadoop support built in.
Unito
Build and map powerful workflows across tools to save your team time. No coding required. Create rules to define what information flows between each of your tools, in minutes.
