Apache Airflow

Apache Airflow

The Apache Software Foundation
+

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About

Airflow is a platform created by the community to programmatically author, schedule and monitor workflows. Airflow has a modular architecture and uses a message queue to orchestrate an arbitrary number of workers. Airflow is ready to scale to infinity. Airflow pipelines are defined in Python, allowing for dynamic pipeline generation. This allows for writing code that instantiates pipelines dynamically. Easily define your own operators and extend libraries to fit the level of abstraction that suits your environment. Airflow pipelines are lean and explicit. Parametrization is built into its core using the powerful Jinja templating engine. No more command-line or XML black-magic! Use standard Python features to create your workflows, including date time formats for scheduling and loops to dynamically generate tasks. This allows you to maintain full flexibility when building your workflows.

About

MLflow is an open source platform to manage the ML lifecycle, including experimentation, reproducibility, deployment, and a central model registry. MLflow currently offers four components. Record and query experiments: code, data, config, and results. Package data science code in a format to reproduce runs on any platform. Deploy machine learning models in diverse serving environments. Store, annotate, discover, and manage models in a central repository. The MLflow Tracking component is an API and UI for logging parameters, code versions, metrics, and output files when running your machine learning code and for later visualizing the results. MLflow Tracking lets you log and query experiments using Python, REST, R API, and Java API APIs. An MLflow Project is a format for packaging data science code in a reusable and reproducible way, based primarily on conventions. In addition, the Projects component includes an API and command-line tools for running projects.

About

Temporal is the open source microservices orchestration platform for running mission critical code at any scale. It guarantees workflow completion of any size and complexity, has built-in support for exponential activity retries, and simplifies defining workflow compensation logic with native Saga pattern support. You can define retries, rollbacks, cleanup, and even human intervention steps in the case of failure. Workflows are defined in general-purpose programming languages that bring the ultimate flexibility for defining workflows of any complexity, especially when compared to markup-based DSLs. Temporal provides full visibility into end-to-end workflows that can span multiple services. It makes complex microservices orchestration manageable by providing a high level of insight into each workflow's state. Contrast this with ad-hoc orchestration based on queues where gaining visibility of your workflows is virtually impossible.

Platforms Supported

Windows
Mac
Linux
Cloud
On-Premises
iPhone
iPad
Android
Chromebook

Platforms Supported

Windows
Mac
Linux
Cloud
On-Premises
iPhone
iPad
Android
Chromebook

Platforms Supported

Windows
Mac
Linux
Cloud
On-Premises
iPhone
iPad
Android
Chromebook

Audience

Anyone who wants to to programmatically author, schedule and monitor workflows

Audience

Companies looking for an open source platform solution for the machine learning lifecycle

Audience

Enterprises that need a microservices orchestration platform for running mission critical code at any scale

Support

Phone Support
24/7 Live Support
Online

Support

Phone Support
24/7 Live Support
Online

Support

Phone Support
24/7 Live Support
Online

API

Offers API

API

Offers API

API

Offers API

Screenshots and Videos

Screenshots and Videos

Screenshots and Videos

Pricing

No information available.
Free Version
Free Trial

Pricing

No information available.
Free Version
Free Trial

Pricing

No information available.
Free Version
Free Trial

Reviews/Ratings

Overall 0.0 / 5
ease 0.0 / 5
features 0.0 / 5
design 0.0 / 5
support 0.0 / 5

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Reviews/Ratings

Overall 0.0 / 5
ease 0.0 / 5
features 0.0 / 5
design 0.0 / 5
support 0.0 / 5

This software hasn't been reviewed yet. Be the first to provide a review:

Review this Software

Reviews/Ratings

Overall 0.0 / 5
ease 0.0 / 5
features 0.0 / 5
design 0.0 / 5
support 0.0 / 5

This software hasn't been reviewed yet. Be the first to provide a review:

Review this Software

Training

Documentation
Webinars
Live Online
In Person

Training

Documentation
Webinars
Live Online
In Person

Training

Documentation
Webinars
Live Online
In Person

Company Information

The Apache Software Foundation
Founded: 1999
United States
airflow.apache.org

Company Information

MLflow
Founded: 2018
United States
mlflow.org

Company Information

Temporal
Founded: 2019
United States
temporal.io

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Categories

Categories

Categories

Integrations

Aporia
Azure Marketplace
BentoML
DataHub
Datafold
Google Cloud Managed Service for Apache Airflow
Great Expectations
IBM watsonx.data integration
Kubernetes
LiteLLM
Metaphor
Oxla
Pantomath
Ragas
SDF
UbiOps
lakeFS
neptune.ai
rudol

Integrations

Aporia
Azure Marketplace
BentoML
DataHub
Datafold
Google Cloud Managed Service for Apache Airflow
Great Expectations
IBM watsonx.data integration
Kubernetes
LiteLLM
Metaphor
Oxla
Pantomath
Ragas
SDF
UbiOps
lakeFS
neptune.ai
rudol

Integrations

Aporia
Azure Marketplace
BentoML
DataHub
Datafold
Google Cloud Managed Service for Apache Airflow
Great Expectations
IBM watsonx.data integration
Kubernetes
LiteLLM
Metaphor
Oxla
Pantomath
Ragas
SDF
UbiOps
lakeFS
neptune.ai
rudol
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