Apache Airflow

Apache Airflow

The Apache Software Foundation
Apache Spark

Apache Spark

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

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

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

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

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

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

Company Information

Temporal
Founded: 2019
United States
temporal.io

Alternatives

JAMS

JAMS

JAMS Software

Alternatives

dbt

dbt

dbt Labs

Alternatives

AWS Glue

AWS Glue

Amazon
dbt

dbt

dbt Labs
Amazon MWAA

Amazon MWAA

Amazon
MLlib

MLlib

Apache Software Foundation

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

Apache Iceberg
Apache PredictionIO
Ardent
Chalk
Databricks Data Intelligence Platform
Datafold
Datakin
Decube
Determined AI
HPE Ezmeral
IRI Voracity
Mage Sensitive Data Discovery
Microsoft Purview
Oracle Machine Learning
ScaleOps
Secoda
SnowcatCloud
Telmai
Unity Catalog

Integrations

Apache Iceberg
Apache PredictionIO
Ardent
Chalk
Databricks Data Intelligence Platform
Datafold
Datakin
Decube
Determined AI
HPE Ezmeral
IRI Voracity
Mage Sensitive Data Discovery
Microsoft Purview
Oracle Machine Learning
ScaleOps
Secoda
SnowcatCloud
Telmai
Unity Catalog

Integrations

Apache Iceberg
Apache PredictionIO
Ardent
Chalk
Databricks Data Intelligence Platform
Datafold
Datakin
Decube
Determined AI
HPE Ezmeral
IRI Voracity
Mage Sensitive Data Discovery
Microsoft Purview
Oracle Machine Learning
ScaleOps
Secoda
SnowcatCloud
Telmai
Unity Catalog
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