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What is Yandex Data Proc?

You decide on the cluster size, node specifications, and various services, while Yandex Data Proc takes care of the setup and configuration of Spark and Hadoop clusters, along with other necessary components. The use of Zeppelin notebooks alongside a user interface proxy enhances collaboration through different web applications. You retain full control of your cluster with root access granted to each virtual machine. Additionally, you can install custom software and libraries on active clusters without requiring a restart. Yandex Data Proc utilizes instance groups to dynamically scale the computing resources of compute subclusters based on CPU usage metrics. The platform also supports the creation of managed Hive clusters, which significantly reduces the risk of failures and data loss that may arise from metadata complications. This service simplifies the construction of ETL pipelines and the development of models, in addition to facilitating the management of various iterative tasks. Moreover, the Data Proc operator is seamlessly integrated into Apache Airflow, which enhances the orchestration of data workflows. Thus, users are empowered to utilize their data processing capabilities to the fullest, ensuring minimal overhead and maximum operational efficiency. Furthermore, the entire system is designed to adapt to the evolving needs of users, making it a versatile choice for data management.

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.

Media

Media

Integrations Supported

Apache Airflow
Python
APERIO DataWise
Apache Flume
Apache HBase
Apache Hive
Apache Spark
Apache Zeppelin
Dataform
Google Cloud BigQuery
Google Cloud Managed Service for Apache Spark
Google Cloud Platform
Google Cloud Pub/Sub
Google Cloud Storage
Hadoop
IBM watsonx.data integration
Matplotlib
Pantomath
pandas
scikit-image

Integrations Supported

Apache Airflow
Python
APERIO DataWise
Apache Flume
Apache HBase
Apache Hive
Apache Spark
Apache Zeppelin
Dataform
Google Cloud BigQuery
Google Cloud Managed Service for Apache Spark
Google Cloud Platform
Google Cloud Pub/Sub
Google Cloud Storage
Hadoop
IBM watsonx.data integration
Matplotlib
Pantomath
pandas
scikit-image

API Availability

Has API

API Availability

Has API

Pricing Information

$0.19 per hour
Free Trial Offered?
Free Version

Pricing Information

$0.074 per vCPU hour
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

Yandex

Date Founded

1997

Company Location

Russia

Company Website

cloud.yandex.com/en/services/data-proc

Company Facts

Organization Name

Google

Date Founded

1998

Company Location

United States

Company Website

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

Categories and Features

Categories and Features

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