Ctfreak vs Amazon Managed Workflows for Apache Airflow
Overview
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Detailed Comparison
It is a managed orchestration service for Apache Airflow1 that makes it easier to set up and operate end-to-end data pipelines in the cloud at scale. With Managed Workflows, you can use Airflow and Python to create workflows without having to manage the underlying infrastructure for scalability, availability, and security. Managed Workflows automatically scales its workflow execution capacity to meet your needs, and is integrated with AWS security services to help provide you with fast and secure access to data. | It is a system service that allows you through a mobile-friendly interface to create, schedule, and execute several types of task like Shell scripts, SQL scripts, Ansible playbooks, SQL reports, Outgoing webhooks, and Workflows. |
Deploy Airflow rapidly at scale; Run Airflow with built-in security; Reduce operational costs; Use a pre-existing plugin or use your own | Distributed shell script;
Task chaining;
Concurrency;
Mobile-friendly UI;
Easy setup;
Incoming webhooks;
Low memory footprint;
Embedded storage engine;
Free, Startup and Pro edition
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Statistics | |
Stacks 21 | Stacks 2 |
Followers 13 | Followers 2 |
Votes 0 | Votes 0 |
Integrations | |
What are some alternatives to Amazon Managed Workflows for Apache Airflow, CTFreak?
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.
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.
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.
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.
Shipyard
na
Flow-Like
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.
ETLR
Production-grade workflow automation. No drag-and-drop required. Build, version, and deploy your workflows with YAML.
Vison AI
Hire AI Employees that deliver Human-Quality work. Automate repetitive tasks, scale effortlessly, and focus on business growth without increasing head count.
