Apache Airflow

Apache Airflow

The Apache Software Foundation
Apache Spark

Apache Spark

Apache Software Foundation
Maestro

Maestro

MaestroDev
+

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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

Apache Spark™ is a unified analytics engine for large-scale data processing. Apache Spark achieves high performance for both batch and streaming data, using a state-of-the-art DAG scheduler, a query optimizer, and a physical execution engine. Spark offers over 80 high-level operators that make it easy to build parallel apps. And you can use it interactively from the Scala, Python, R, and SQL shells. Spark powers a stack of libraries including SQL and DataFrames, MLlib for machine learning, GraphX, and Spark Streaming. You can combine these libraries seamlessly in the same application. Spark runs on Hadoop, Apache Mesos, Kubernetes, standalone, or in the cloud. It can access diverse data sources. You can run Spark using its standalone cluster mode, on EC2, on Hadoop YARN, on Mesos, or on Kubernetes. Access data in HDFS, Alluxio, Apache Cassandra, Apache HBase, Apache Hive, and hundreds of other data sources.

About

DevOps Orchestration is the practice of composing any tasks across the SDLC and Operations functions, with any choice of tools and environments, and with the process logic centralized away from the individual tools themselves. The Maestro product includes plug-ins, pre-built tasks, and templates for continuous integration, test automation, release management, DevOps visibility, automated deployment, and continuous delivery. Whether your DevOps tools are on-premise or cloud services (or both!), Maestro effortlessly connects workflow tasks between your tools for Continuous Integration and Continuous Deployment. The workflow "CompositionTM" above shows a Git checkout, Jenkins build, Sonar code check, testing steps, and then custom notifications. Remove manual tasks from your custom release process, and create a precise, repeatable set of tasks that execute reliably, every time.

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

Organizations that want a unified analytics engine for large-scale data processing

Audience

DevOps teams looking for a complete Release Management solution

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

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

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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

Apache Software Foundation
Founded: 1999
United States
spark.apache.org

Company Information

MaestroDev
Founded: 2006
United States
maestrodev.wixsite.com/maestrodev/

Alternatives

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JAMS

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Alternatives

dbt

dbt

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Alternatives

AWS Glue

AWS Glue

Amazon
dbt

dbt

dbt Labs
Amazon MWAA

Amazon MWAA

Amazon
MLlib

MLlib

Apache Software Foundation
Clarive

Clarive

Clarive Software

Categories

Categories

Categories

Streaming Analytics Features

Data Enrichment
Data Wrangling / Data Prep
Multiple Data Source Support
Process Automation
Real-time Analysis / Reporting
Visualization Dashboards

Integrations

Amazon MWAA
Apache Hive
Apache Kudu
Ardent
DQOps
Datafold
Gemini Enterprise Agent Platform Notebooks
Great Expectations
Kubernetes
LakeSail
MLflow
Molecula
Rackspace Managed Hosting
Ray
SDF
Sifflet
Spark Streaming
Sync
Thunder Compute
Yottamine

Integrations

Amazon MWAA
Apache Hive
Apache Kudu
Ardent
DQOps
Datafold
Gemini Enterprise Agent Platform Notebooks
Great Expectations
Kubernetes
LakeSail
MLflow
Molecula
Rackspace Managed Hosting
Ray
SDF
Sifflet
Spark Streaming
Sync
Thunder Compute
Yottamine

Integrations

Amazon MWAA
Apache Hive
Apache Kudu
Ardent
DQOps
Datafold
Gemini Enterprise Agent Platform Notebooks
Great Expectations
Kubernetes
LakeSail
MLflow
Molecula
Rackspace Managed Hosting
Ray
SDF
Sifflet
Spark Streaming
Sync
Thunder Compute
Yottamine
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