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  1. Stackups
  2. Utilities
  3. Task Scheduling
  4. Workflow Manager
  5. Airflow vs Tallyfy

Airflow vs Tallyfy

OverviewDecisionsComparisonAlternatives

Overview

Airflow
Airflow
Stacks1.7K
Followers2.8K
Votes128
Tallyfy
Tallyfy
Stacks6
Followers14
Votes0

Airflow vs Tallyfy: What are the differences?

Developers describe Airflow as "A platform to programmaticaly author, schedule and monitor data pipelines, by Airbnb". 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. On the other hand, Tallyfy is detailed as "Workflow software that turns your daily tasks and approvals into automated, repeatable processes". It is a workflow software and a business process workflow management tool which automates and improve your workflows.

Airflow and Tallyfy belong to "Workflow Manager" category of the tech stack.

Some of the features offered by Airflow are:

  • 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.

On the other hand, Tallyfy provides the following key features:

  • Business Rules Management
  • Collaboration
  • Process Modeling & Design

Airflow is an open source tool with 13.8K GitHub stars and 5.11K GitHub forks. Here's a link to Airflow's open source repository on GitHub.

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Advice on Airflow, Tallyfy

Anonymous
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.

294k views294k
Comments

Detailed Comparison

Airflow
Airflow
Tallyfy
Tallyfy

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.

Tallyfy is beautifully designed workflow software and a zero-flowcharts and zero-code business process workflow management tool which automates and improve your repeatable processes, approvals and even client-facing workflows.

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.
Business Rules Management; Collaboration; Process Modeling & Design; Action audit trail; Manages compliance policy of the company; Configurable workflows & processes; Maintains all company workflows, processes and procedures; Data mapping; Business Process Management; Workflow Automation; Workflow Software
Statistics
Stacks
1.7K
Stacks
6
Followers
2.8K
Followers
14
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
Google Drive
Google Drive
DocuSign
DocuSign
Gmail
Gmail
Slack
Slack
Salesforce
Salesforce
Flow
Flow
Tableau
Tableau
Zapier
Zapier
Microsoft SharePoint
Microsoft SharePoint
Power BI
Power BI

What are some alternatives to Airflow, Tallyfy?

GitHub Actions

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

Apache Beam

It implements batch and streaming data processing jobs that run on any execution engine. It executes pipelines on multiple execution environments.

Zenaton

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

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

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

Shipyard

na

Flow-Like

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

ETLR

Production-grade workflow automation. No drag-and-drop required. Build, version, and deploy your workflows with YAML.

Fermi Dev

Fermi Dev

Is the AI Operational Brain for Modern Enterprises. Connect your systems, build dynamic models, and automate business processes with intelligent agents.

Vison AI

Vison AI

Hire AI Employees that deliver Human-Quality work. Automate repetitive tasks, scale effortlessly, and focus on business growth without increasing head count.

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