Overview

Airflow

Stacks1.7K

Followers2.8K

Votes128

Kissflow

Stacks10

Followers24

Votes0

Airflow vs Kissflow: What are the differences?

Airflow vs Kissflow

Airflow and Kissflow are both workflow automation tools, but they differ in several key aspects.

1. **Workflow Type**: Airflow is primarily designed for data pipeline orchestration, allowing users to schedule and monitor complex data workflows. On the other hand, Kissflow is focused on business process management, allowing users to create, automate, and track business workflows.

2. **Customization and Extensibility**: Airflow offers a high level of customization and extensibility through its Python-based scripting abilities, which allow users to define complex workflows using code. In contrast, Kissflow offers a more user-friendly interface with pre-built templates and drag-and-drop features, making it easier for non-technical users to create workflows.

3. **Deployment and Scalability**: Airflow requires users to set up and manage their own infrastructure, making it more suitable for organizations with in-house technical expertise. Kissflow, on the other hand, is a cloud-based platform that handles deployment and scalability automatically, making it more accessible to smaller organizations or teams without dedicated IT resources.

4. **Integration with Third-Party Tools**: Airflow has strong integration capabilities with a wide range of third-party tools and services, allowing users to easily connect their workflows with other systems. While Kissflow also offers integrations, its focus is more on providing a comprehensive solution within the platform, reducing the need for external integrations.

5. **Cost Structure**: Airflow is an open-source tool with no licensing fees, but users incur costs for infrastructure management and maintenance. In contrast, Kissflow operates on a subscription-based model, with pricing tiers based on the number of users and features required, making it easier to predict and budget for costs.

6. **User Audience**: Airflow is more suited for technical users who are comfortable with scripting and working with code, making it ideal for data engineers and developers. Kissflow, on the other hand, is designed for business users and process owners who need to streamline and automate workflows without relying on technical expertise.

In Summary, Airflow and Kissflow differ in their focus on workflow types, customization levels, deployment options, integration capabilities, cost structures, and target user audiences.

Advice on Airflow, Kissflow

Anonymous

Jan 19, 2020

Needs advice

I am so confused. I need a tool that will allow me to go to about 10 different URLs to get a list of objects. Those object lists will be hundreds or thousands in length. I then need to get detailed data lists about each object. Those detailed data lists can have hundreds of elements that could be map/reduced somehow. My batch process dies sometimes halfway through which means hours of processing gone, i.e. time wasted. I need something like a directed graph that will keep results of successful data collection and allow me either pragmatically or manually to retry the failed ones some way (0 - forever) times. I want it to then process all the ones that have succeeded or been effectively ignored and load the data store with the aggregation of some couple thousand data-points. I know hitting this many endpoints is not a good practice but I can't put collectors on all the endpoints or anything like that. It is pretty much the only way to get the data.

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Comments

Detailed Comparison

Airflow	Kissflow
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.	It is a workflow tool & business process workflow management software to automate your workflow process.
Dynamic: Airflow pipelines are configuration as code (Python), allowing for dynamic pipeline generation. This allows for writting code that instantiate pipelines dynamically.;Extensible: Easily define your own operators, executors and extend the library so that it fits the level of abstraction that suits your environment.;Elegant: Airflow pipelines are lean and explicit. Parameterizing your scripts is built in the core of Airflow using powerful Jinja templating engine.;Scalable: Airflow has a modular architecture and uses a message queue to talk to orchestrate an arbitrary number of workers. Airflow is ready to scale to infinity.	Process Management; Case Management; Project Management; Collaboration; Procurement Cloud; Community Platform;
Statistics
Stacks 1.7K	Stacks 10
Followers 2.8K	Followers 24
Votes 128	Votes 0
Pros & Cons
Pros 53 Features 14 Task Dependency Management 12 Cluster of workers 12 Beautiful UI 10 Extensibility Cons 2 Observability is not great when the DAGs exceed 250 2 Open source - provides minimum or no support 2 Running it on kubernetes cluster relatively complex 1 Logical separation of DAGs is not straight forward	No community feedback yet
Integrations
No integrations available	DocuSign Microsoft Outlook Smartsheet QuickBooks Slack Google Docs Dropbox Salesmate Salesforce Sales Cloud Oracle

What are some alternatives to Airflow, Kissflow?

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