Related Products
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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.
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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.
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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.
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Platforms Supported
Windows
Mac
Linux
Cloud
On-Premises
iPhone
iPad
Android
Chromebook
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Platforms Supported
Windows
Mac
Linux
Cloud
On-Premises
iPhone
iPad
Android
Chromebook
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Platforms Supported
Windows
Mac
Linux
Cloud
On-Premises
iPhone
iPad
Android
Chromebook
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Audience
Anyone who wants to to programmatically author, schedule and monitor workflows
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Audience
Companies looking for an open source platform solution for the machine learning lifecycle
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Audience
Enterprises that need a microservices orchestration platform for running mission critical code at any scale
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Support
Phone Support
24/7 Live Support
Online
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Support
Phone Support
24/7 Live Support
Online
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Support
Phone Support
24/7 Live Support
Online
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API
Offers API
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API
Offers API
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API
Offers API
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Screenshots and Videos |
Screenshots and Videos |
Screenshots and Videos |
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Pricing
No information available.
Free Version
Free Trial
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Pricing
No information available.
Free Version
Free Trial
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Pricing
No information available.
Free Version
Free Trial
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Reviews/
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Reviews/
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Reviews/
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Training
Documentation
Webinars
Live Online
In Person
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Training
Documentation
Webinars
Live Online
In Person
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Training
Documentation
Webinars
Live Online
In Person
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Company InformationThe Apache Software Foundation
Founded: 1999
United States
airflow.apache.org
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Company InformationMLflow
Founded: 2018
United States
mlflow.org
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Company InformationTemporal
Founded: 2019
United States
temporal.io
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Categories |
Categories |
Categories |
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Integrations
Aporia
Azure Marketplace
BentoML
DataHub
Datafold
Google Cloud Managed Service for Apache Airflow
Great Expectations
IBM watsonx.data integration
Kubernetes
LiteLLM
|
Integrations
Aporia
Azure Marketplace
BentoML
DataHub
Datafold
Google Cloud Managed Service for Apache Airflow
Great Expectations
IBM watsonx.data integration
Kubernetes
LiteLLM
|
Integrations
Aporia
Azure Marketplace
BentoML
DataHub
Datafold
Google Cloud Managed Service for Apache Airflow
Great Expectations
IBM watsonx.data integration
Kubernetes
LiteLLM
|
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