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Description
AWS Data Pipeline is a robust web service designed to facilitate the reliable processing and movement of data across various AWS compute and storage services, as well as from on-premises data sources, according to defined schedules. This service enables you to consistently access data in its storage location, perform large-scale transformations and processing, and seamlessly transfer the outcomes to AWS services like Amazon S3, Amazon RDS, Amazon DynamoDB, and Amazon EMR. With AWS Data Pipeline, you can effortlessly construct intricate data processing workflows that are resilient, repeatable, and highly available. You can rest assured knowing that you do not need to manage resource availability, address inter-task dependencies, handle transient failures or timeouts during individual tasks, or set up a failure notification system. Additionally, AWS Data Pipeline provides the capability to access and process data that was previously confined within on-premises data silos, expanding your data processing possibilities significantly. This service ultimately streamlines the data management process and enhances operational efficiency across your organization.
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
Integrations
Amazon DynamoDB
Amazon EC2
Amazon RDS
Amazon S3
Apache Airflow
Apache Flume
Apache Hive
Apache Spark
Apache Zeppelin
EC2 Spot
Integrations
Amazon DynamoDB
Amazon EC2
Amazon RDS
Amazon S3
Apache Airflow
Apache Flume
Apache Hive
Apache Spark
Apache Zeppelin
EC2 Spot
Pricing Details
$1 per month
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
Amazon
Founded
1994
Country
United States
Website
aws.amazon.com/datapipeline/
Vendor Details
Company Name
Yandex
Founded
1997
Country
Russia
Website
cloud.yandex.com/en/services/data-proc
Product Features
ETL
Data Analysis
Data Filtering
Data Quality Control
Job Scheduling
Match & Merge
Metadata Management
Non-Relational Transformations
Version Control