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ease
features
design
support

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Description

The Apache Hadoop software library serves as a framework for the distributed processing of extensive data sets across computer clusters, utilizing straightforward programming models. It is built to scale from individual servers to thousands of machines, each providing local computation and storage capabilities. Instead of depending on hardware for high availability, the library is engineered to identify and manage failures within the application layer, ensuring that a highly available service can run on a cluster of machines that may be susceptible to disruptions. Numerous companies and organizations leverage Hadoop for both research initiatives and production environments. Users are invited to join the Hadoop PoweredBy wiki page to showcase their usage. The latest version, Apache Hadoop 3.3.4, introduces several notable improvements compared to the earlier major release, hadoop-3.2, enhancing its overall performance and functionality. This continuous evolution of Hadoop reflects the growing need for efficient data processing solutions in today's data-driven landscape.

Description

You determine the cluster size, node specifications, and a range of services, while Yandex Data Proc effortlessly sets up and configures Spark, Hadoop clusters, and additional components. Collaboration is enhanced through the use of Zeppelin notebooks and various web applications via a user interface proxy. You maintain complete control over your cluster with root access for every virtual machine. Moreover, you can install your own software and libraries on active clusters without needing to restart them. Yandex Data Proc employs instance groups to automatically adjust computing resources of compute subclusters in response to CPU usage metrics. Additionally, Data Proc facilitates the creation of managed Hive clusters, which helps minimize the risk of failures and data loss due to metadata issues. This service streamlines the process of constructing ETL pipelines and developing models, as well as managing other iterative operations. Furthermore, the Data Proc operator is natively integrated into Apache Airflow, allowing for seamless orchestration of data workflows. This means that users can leverage the full potential of their data processing capabilities with minimal overhead and maximum efficiency.

API Access

Has API

API Access

Has API

Screenshots View All

Screenshots View All

Integrations

Apache Spark
Apache Zeppelin
Apache Hudi
Apache Mahout
Apache Phoenix
Baidu Palo
BigBI
CYRES
Composable DataOps Platform
Deep.BI
Hostmaster
Netdata
Occubee
Oracle Big Data SQL Cloud Service
Oracle Big Data Service
Pavilion HyperOS
Peekdata
SnapLogic
lakeFS
witboost

Integrations

Apache Spark
Apache Zeppelin
Apache Hudi
Apache Mahout
Apache Phoenix
Baidu Palo
BigBI
CYRES
Composable DataOps Platform
Deep.BI
Hostmaster
Netdata
Occubee
Oracle Big Data SQL Cloud Service
Oracle Big Data Service
Pavilion HyperOS
Peekdata
SnapLogic
lakeFS
witboost

Pricing Details

No price information available.
Free Trial
Free Version

Pricing Details

$0.19 per hour
Free Trial
Free Version

Deployment

Web-Based
On-Premises
iPhone App
iPad App
Android App
Windows
Mac
Linux
Chromebook

Deployment

Web-Based
On-Premises
iPhone App
iPad App
Android App
Windows
Mac
Linux
Chromebook

Customer Support

Business Hours
Live Rep (24/7)
Online Support

Customer Support

Business Hours
Live Rep (24/7)
Online Support

Types of Training

Training Docs
Webinars
Live Training (Online)
In Person

Types of Training

Training Docs
Webinars
Live Training (Online)
In Person

Vendor Details

Company Name

Apache Software Foundation

Founded

1999

Country

United States

Website

hadoop.apache.org

Vendor Details

Company Name

Yandex

Founded

1997

Country

Russia

Website

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

Product Features

Big Data

Collaboration
Data Blends
Data Cleansing
Data Mining
Data Visualization
Data Warehousing
High Volume Processing
No-Code Sandbox
Predictive Analytics
Templates

Product Features

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