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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 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

Apache Airflow
Apache HBase
Apache Spark
Apache Zeppelin
CData Connect
Google Cloud Bigtable
Google Cloud Datastream
Google Cloud IoT Core
Google Cloud Platform
Hadoop
Matplotlib
New Relic
NumPy
Protegrity
Python
Telmai
Yandex Cloud
Yandex DataSphere
pandas
scikit-image

Integrations Supported

Apache Airflow
Apache HBase
Apache Spark
Apache Zeppelin
CData Connect
Google Cloud Bigtable
Google Cloud Datastream
Google Cloud IoT Core
Google Cloud Platform
Hadoop
Matplotlib
New Relic
NumPy
Protegrity
Python
Telmai
Yandex Cloud
Yandex DataSphere
pandas
scikit-image

API Availability

Has API

API Availability

Has API

Pricing Information

$0.19 per hour
Free Trial Offered?
Free Version

Pricing Information

Pricing not provided.
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/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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