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Average Ratings 0 Ratings

Total
ease
features
design
support

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Write a Review

Description

Amazon Managed Workflows for Apache Airflow (MWAA) is a service that simplifies the orchestration of Apache Airflow, allowing users to efficiently establish and manage comprehensive data pipelines in the cloud at scale. Apache Airflow itself is an open-source platform designed for the programmatic creation, scheduling, and oversight of workflows, which are sequences of various processes and tasks. By utilizing Managed Workflows, users can leverage Airflow and Python to design workflows while eliminating the need to handle the complexities of the underlying infrastructure, ensuring scalability, availability, and security. This service adapts its workflow execution capabilities automatically to align with user demands and incorporates AWS security features, facilitating swift and secure data access. Overall, MWAA empowers organizations to focus on their data processes without the burden of infrastructure management.

Description

Dagster is the cloud-native open-source orchestrator for the whole development lifecycle, with integrated lineage and observability, a declarative programming model, and best-in-class testability. It is the platform of choice data teams responsible for the development, production, and observation of data assets. With Dagster, you can focus on running tasks, or you can identify the key assets you need to create using a declarative approach. Embrace CI/CD best practices from the get-go: build reusable components, spot data quality issues, and flag bugs early.

API Access

Has API No 

API Access

Has API Yes 

Screenshots View All

Screenshots View All

Integrations

Amazon Web Services (AWS) Yes 
Apache Airflow Yes 
APERIO DataWise No 
Airbyte No 
Azure Kubernetes Service (AKS) No 
Coginiti No 
Collate No 
Dask No 
Databricks No 
Fivetran No 
Google Cloud Platform No 
Jupyter Notebook No 
Microsoft Teams No 
PagerDuty No 
Papertrail No 
PostgreSQL No 
SDF No 
Twilio No 
dbt No 
pandas No 

Integrations

Amazon Web Services (AWS) Yes 
Apache Airflow Yes 
APERIO DataWise Yes 
Airbyte Yes 
Azure Kubernetes Service (AKS) Yes 
Coginiti Yes 
Collate Yes 
Dask Yes 
Databricks Yes 
Fivetran Yes 
Google Cloud Platform Yes 
Jupyter Notebook Yes 
Microsoft Teams Yes 
PagerDuty Yes 
Papertrail Yes 
PostgreSQL Yes 
SDF Yes 
Twilio Yes 
dbt Yes 
pandas Yes 

Pricing Details

$0.49 per hour
Free Trial No 
Free Version No 

Pricing Details

$0
Pricing starts at $0.04/min for Serverless and $0.03/min for Hybrid, and tapers down from there based on usage.
Free Trial Yes 
Free Version Yes 

Deployment

Web-Based Yes 
On-Premises No 
iPhone App No 
iPad App No 
Android App No 
Windows No 
Mac No 
Linux No 
Chromebook No 

Deployment

Web-Based Yes 
On-Premises Yes 
iPhone App No 
iPad App No 
Android App No 
Windows Yes 
Mac Yes 
Linux Yes 
Chromebook No 

Customer Support

Business Hours No 
Live Rep (24/7) No 
Online Support Yes 

Customer Support

Business Hours No 
Live Rep (24/7) Yes 
Online Support Yes 

Types of Training

Training Docs Yes 
Webinars No 
Live Training (Online) No 
In Person No 

Types of Training

Training Docs Yes 
Webinars No 
Live Training (Online) No 
In Person No 

Vendor Details

Company Name

Amazon

Founded

1994

Country

United States

Website

aws.amazon.com/managed-workflows-for-apache-airflow/

Vendor Details

Company Name

Dagster Labs

Founded

2019

Country

United States

Website

dagster.io

Product Features

Product Features

Data Fabric

Data Access Management No 
Data Analytics Yes 
Data Collaboration Yes 
Data Lineage Tools Yes 
Data Networking / Connecting Yes 
Metadata Functionality Yes 
No Data Redundancy No 
Persistent Data Management No 

Data Management

Customer Data No 
Data Analysis Yes 
Data Capture No 
Data Integration Yes 
Data Migration Yes 
Data Quality Control No 
Data Security No 
Information Governance No 
Master Data Management No 
Match & Merge Yes 

ETL

Data Analysis Yes 
Data Filtering Yes 
Data Quality Control No 
Job Scheduling Yes 
Match & Merge No 
Metadata Management No 
Non-Relational Transformations No 
Version Control No 

Machine Learning

Deep Learning No 
ML Algorithm Library No 
Model Training Yes 
Natural Language Processing (NLP) No 
Predictive Modeling Yes 
Statistical / Mathematical Tools Yes 
Templates No 
Visualization No 

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Apache Airflow

The Apache Software Foundation

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