AWS Data Pipeline

Amazon Data Pipeline: AWS Data Pipeline is a web program which will help you reliably process and move information between several AWS compute and storage solutions, and also on-premises information resources, at specified intervals. With AWS Data Pipeline, you can frequently access the data of yours in which it is kept, transform as well as process it at scale, and also on-premises information resources, at specified intervals.

With AWS Data Pipeline, you can frequently access the data of yours in which it is kept, transform as well as process it at scale, and effectively transport the end result to AWS services like Amazon S3, Amazon DynamoDB, Amazon RDS and Amazon EMR.

AWS Data Pipeline allows you to effortlessly produce complicated information processing workloads which are fault understanding, repeatable, along with very accessible. You do not need to be concerned about making sure source accessibility, managing inter-task dependencies, retrying transient failures or maybe timeouts in specific jobs, or perhaps developing a failure notification process. AWS Data Pipeline also enables you to move as well as process information which was earlier locked up in on-premises information silos.

Features of AWS Data Pipeline

Reliable



The AWS Data Pipeline infrastructure is developed for fault-tolerant execution activities. In case any failures occur in data sources or activity logic then AWS data Pipeline automatically retries the activity. If still the failures continue then sends a notification and these notification alerts can configure the situations like successful runs, delays, failures, etc.

Flexible

The AWS Data Pipeline offers features like scheduling, tracking, error handling, etc. To take actions it can be configured such as Amazon EMR jobs, execute SQL queries against databases and executes custom applications running on Amazon EC2.

Simple and Cost-effective

The AWS Data Pipeline is the drag and drops features that is easy to create a pipeline on a console. It provides a library of pipeline templates and these templates are used to create pipelines for tasks like processing log files, accessing data to Amazon S3.