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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 DataOps DataFlow?

Apache Spark offers a comprehensive component-driven platform that streamlines the automation of Data Reconciliation testing for contemporary Data Lake and Cloud Data Migration initiatives. DataOps DataFlow serves as an innovative web-based tool designed to facilitate the automation of testing for ETL projects, Data Warehouses, and Data Migrations. You can utilize DataFlow to efficiently load data from diverse sources, perform comparisons, and transfer discrepancies either into S3 or a Database. This enables users to create and execute data flows with remarkable ease. It stands out as a premier testing solution specifically tailored for Big Data Testing. Moreover, DataOps DataFlow seamlessly integrates with a wide array of both traditional and cutting-edge data sources, encompassing RDBMS, NoSQL databases, as well as cloud-based and file-based systems, ensuring versatility in data handling.

Media

Media

Integrations Supported

APERIO DataWise
Amazon Redshift
Apache Airflow
Azure Synapse Analytics
Dataform
Datagaps DataOps Suite
Google Cloud AI Infrastructure
Google Cloud BigQuery
Google Cloud Dataflow
Google Cloud Datastore
Google Cloud Managed Service for Apache Spark
Google Cloud Platform
Google Cloud Pub/Sub
Google Cloud Storage
IBM watsonx.data integration
Microsoft Power BI
Pantomath
Python
Snowflake
Tableau

Integrations Supported

APERIO DataWise
Amazon Redshift
Apache Airflow
Azure Synapse Analytics
Dataform
Datagaps DataOps Suite
Google Cloud AI Infrastructure
Google Cloud BigQuery
Google Cloud Dataflow
Google Cloud Datastore
Google Cloud Managed Service for Apache Spark
Google Cloud Platform
Google Cloud Pub/Sub
Google Cloud Storage
IBM watsonx.data integration
Microsoft Power BI
Pantomath
Python
Snowflake
Tableau

API Availability

Has API

API Availability

Has API

Pricing Information

$0.074 per vCPU hour
Free Trial Offered?
Free Version

Pricing Information

Contact us
Free Trial Offered?
Free Version

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

Datagaps

Date Founded

2010

Company Location

United States

Company Website

www.datagaps.com/dataops-dataflow/

Categories and Features

Categories and Features

Data Management

Customer Data
Data Analysis
Data Capture
Data Integration
Data Migration
Data Quality Control
Data Security
Information Governance
Master Data Management
Match & Merge

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