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What is Google Cloud Managed Service for Apache Airflow?

Managed Service for Apache Airflow is a comprehensive workflow orchestration platform from Google Cloud that enables organizations to build, schedule, and monitor complex data pipelines with ease. Based on the open-source Apache Airflow project, it uses Python-defined DAGs to create flexible and scalable workflows. The fully managed nature of the service removes the burden of infrastructure management, allowing teams to focus on data engineering and automation tasks. It integrates seamlessly with Google Cloud services such as BigQuery, Dataflow, Managed Service for Apache Spark, Cloud Storage, and Pub/Sub, enabling end-to-end pipeline orchestration. The platform supports hybrid and multi-cloud environments, making it ideal for organizations with diverse data ecosystems. It includes advanced features like DAG versioning, scheduler-managed backfills, and improved user interfaces for better workflow management. Built-in monitoring, logging, and visualization tools help ensure reliability and simplify troubleshooting. The service also supports CI/CD pipelines, enabling automated deployment and management of workflows. Its open-source foundation ensures portability and flexibility while avoiding vendor lock-in. Security features such as IAM, VPC Service Controls, and encryption provide strong data protection. The platform is suitable for a wide range of use cases, including ETL pipelines, machine learning workflows, and business intelligence automation. It also enables event-driven and near real-time pipeline execution. Overall, Managed Service for Apache Airflow provides a robust, scalable, and user-friendly solution for orchestrating modern data workflows.

What is Google Cloud Dataflow?

A data processing solution that combines both streaming and batch functionalities in a serverless, cost-effective manner is now available. This service provides comprehensive management for data operations, facilitating smooth automation in the setup and management of necessary resources. With the ability to scale horizontally, the system can adapt worker resources in real time, boosting overall efficiency. The advancement of this technology is largely supported by the contributions of the open-source community, especially through the Apache Beam SDK, which ensures reliable processing with exactly-once guarantees. Dataflow significantly speeds up the creation of streaming data pipelines, greatly decreasing latency associated with data handling. By embracing a serverless architecture, development teams can concentrate more on coding rather than navigating the complexities involved in server cluster management, which alleviates the typical operational challenges faced in data engineering. This automatic resource management not only helps in reducing latency but also enhances resource utilization, allowing teams to maximize their operational effectiveness. In addition, the framework fosters an environment conducive to collaboration, empowering developers to create powerful applications while remaining free from the distractions of managing the underlying infrastructure. As a result, teams can achieve higher productivity and innovation in their data processing initiatives.

Media

Media

Integrations Supported

Google Cloud Platform
Pantomath
APERIO DataWise
Apache Airflow
CData Connect
Control-M
DataBuck
Google Cloud BigQuery
Google Cloud Bigtable
Google Cloud Dataflow
Google Cloud Datastore
Google Cloud Knowledge Catalog
Google Cloud Managed Service for Apache Spark
Google Cloud Storage
IBM watsonx.data integration
New Relic
Protegrity
Python
Sedai
Ternary

Integrations Supported

Google Cloud Platform
Pantomath
APERIO DataWise
Apache Airflow
CData Connect
Control-M
DataBuck
Google Cloud BigQuery
Google Cloud Bigtable
Google Cloud Dataflow
Google Cloud Datastore
Google Cloud Knowledge Catalog
Google Cloud Managed Service for Apache Spark
Google Cloud Storage
IBM watsonx.data integration
New Relic
Protegrity
Python
Sedai
Ternary

API Availability

Has API

API Availability

Has API

Pricing Information

$0.074 per vCPU hour
Free Version
Free Trial Offered?

Pricing Information

Pricing not provided
Free Version
Free Trial Offered?

Supported Platforms

SaaS
Android
iPhone
iPad
Windows
Mac
On-Prem
Chromebook
Linux

Supported Platforms

SaaS
Android
iPhone
iPad
Windows
Mac
On-Prem
Chromebook
Linux

Customer Service / Support

Standard Support
24 Hour Support
Web-Based Support

Customer Service / Support

Standard Support
24 Hour Support
Web-Based Support

Training Options

Documentation Hub
Webinars
Online Training
On-Site Training

Training Options

Documentation Hub
Webinars
Online Training
On-Site Training

Company Facts

Organization Name

Google

Date Founded

1998

Company Location

United States

Company Website

cloud.google.com/products/managed-service-for-apache-airflow

Company Facts

Organization Name

Google

Date Founded

1998

Company Location

United States

Company Website

cloud.google.com/dataflow

Categories and Features

Categories and Features

Streaming Analytics

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

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