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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 AWS Data Pipeline?

AWS Data Pipeline is a cloud service designed to facilitate the dependable transfer and processing of data between various AWS computing and storage platforms, as well as on-premises data sources, following established schedules. By leveraging AWS Data Pipeline, users gain consistent access to their stored information, enabling them to conduct extensive transformations and processing while effortlessly transferring results to AWS services such as Amazon S3, Amazon RDS, Amazon DynamoDB, and Amazon EMR. This service greatly simplifies the setup of complex data processing tasks that are resilient, repeatable, and highly dependable. Users benefit from the assurance that they do not have to worry about managing resource availability, inter-task dependencies, transient failures, or timeouts, nor do they need to implement a system for failure notifications. Additionally, AWS Data Pipeline allows users to efficiently transfer and process data that was previously locked away in on-premises data silos, which significantly boosts overall data accessibility and utility. By enhancing the workflow, this service not only makes data handling more efficient but also encourages better decision-making through improved data visibility. The result is a more streamlined and effective approach to managing data in the cloud.

Media

Media

Integrations Supported

AWS App Mesh
Amazon DynamoDB
Amazon EMR
Amazon RDS
Amazon S3
Apache Flume
Apache HBase
Apache Hive
Apache Spark
Apache Zeppelin
EC2 Spot
Functionize
Hadoop
NumPy
Python
SquaredUp
TensorFlow
Yandex DataSphere
pandas
scikit-image

Integrations Supported

AWS App Mesh
Amazon DynamoDB
Amazon EMR
Amazon RDS
Amazon S3
Apache Flume
Apache HBase
Apache Hive
Apache Spark
Apache Zeppelin
EC2 Spot
Functionize
Hadoop
NumPy
Python
SquaredUp
TensorFlow
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

$1 per month
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

Amazon

Date Founded

1994

Company Location

United States

Company Website

aws.amazon.com/datapipeline/

Categories and Features

Categories and Features

ETL

Data Analysis
Data Filtering
Data Quality Control
Job Scheduling
Match & Merge
Metadata Management
Non-Relational Transformations
Version Control

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