AWS Data Pipeline vs AWS Import/Export

Need advice about which tool to choose?Ask the StackShare community!

AWS Data Pipeline

95
398
+ 1
1
AWS Import/Export

5
31
+ 1
0
Add tool

AWS Data Pipeline vs AWS Import/Export: What are the differences?

AWS Data Pipeline: Process and move data between different AWS compute and storage services. AWS Data Pipeline is a web service that provides a simple management system for data-driven workflows. Using AWS Data Pipeline, you define a pipeline composed of the “data sources” that contain your data, the “activities” or business logic such as EMR jobs or SQL queries, and the “schedule” on which your business logic executes. For example, you could define a job that, every hour, runs an Amazon Elastic MapReduce (Amazon EMR)–based analysis on that hour’s Amazon Simple Storage Service (Amazon S3) log data, loads the results into a relational database for future lookup, and then automatically sends you a daily summary email; AWS Import/Export: Transfer your data directly onto and off of storage devices using Amazon’s internal network and bypassing the Internet. Import/Export supports importing and exporting data into and out of Amazon S3 buckets. For significant data sets, AWS Import/Export is often faster than Internet transfer and more cost effective than upgrading your connectivity.

AWS Data Pipeline and AWS Import/Export belong to "Data Transfer" category of the tech stack.

Some of the features offered by AWS Data Pipeline are:

  • You can find (and use) a variety of popular AWS Data Pipeline tasks in the AWS Management Console’s template section.
  • Hourly analysis of Amazon S3‐based log data
  • Daily replication of AmazonDynamoDB data to Amazon S3

On the other hand, AWS Import/Export provides the following key features:

  • Data Migration – If you have data you need to upload into the AWS cloud for the first time, AWS Import/Export is often much faster than transferring that data via the Internet.
  • Content Distribution – Send data to your customers on portable storage devices.
  • Direct Data Interchange – If you regularly receive content on portable storage devices from your business associates, you can have them send it directly to AWS for import into Amazon S3 or Amazon EBS.
Manage your open source components, licenses, and vulnerabilities
Learn More
Pros of AWS Data Pipeline
Pros of AWS Import/Export
  • 1
    Easy to create DAG and execute it
    Be the first to leave a pro

    Sign up to add or upvote prosMake informed product decisions

    What is AWS Data Pipeline?

    AWS Data Pipeline is a web service that provides a simple management system for data-driven workflows. Using AWS Data Pipeline, you define a pipeline composed of the “data sources” that contain your data, the “activities” or business logic such as EMR jobs or SQL queries, and the “schedule” on which your business logic executes. For example, you could define a job that, every hour, runs an Amazon Elastic MapReduce (Amazon EMR)–based analysis on that hour’s Amazon Simple Storage Service (Amazon S3) log data, loads the results into a relational database for future lookup, and then automatically sends you a daily summary email.

    What is AWS Import/Export?

    Import/Export supports importing and exporting data into and out of Amazon S3 buckets. For significant data sets, AWS Import/Export is often faster than Internet transfer and more cost effective than upgrading your connectivity.

    Need advice about which tool to choose?Ask the StackShare community!

    What companies use AWS Data Pipeline?
    What companies use AWS Import/Export?
    Manage your open source components, licenses, and vulnerabilities
    Learn More

    Sign up to get full access to all the companiesMake informed product decisions

    What tools integrate with AWS Data Pipeline?
    What tools integrate with AWS Import/Export?
    What are some alternatives to AWS Data Pipeline and AWS Import/Export?
    AWS Glue
    A fully managed extract, transform, and load (ETL) service that makes it easy for customers to prepare and load their data for analytics.
    Airflow
    Use Airflow to author workflows as directed acyclic graphs (DAGs) of tasks. The Airflow scheduler executes your tasks on an array of workers while following the specified dependencies. Rich command lines utilities makes performing complex surgeries on DAGs a snap. The rich user interface makes it easy to visualize pipelines running in production, monitor progress and troubleshoot issues when needed.
    AWS Step Functions
    AWS Step Functions makes it easy to coordinate the components of distributed applications and microservices using visual workflows. Building applications from individual components that each perform a discrete function lets you scale and change applications quickly.
    Apache NiFi
    An easy to use, powerful, and reliable system to process and distribute data. It supports powerful and scalable directed graphs of data routing, transformation, and system mediation logic.
    AWS Batch
    It enables developers, scientists, and engineers to easily and efficiently run hundreds of thousands of batch computing jobs on AWS. It dynamically provisions the optimal quantity and type of compute resources (e.g., CPU or memory optimized instances) based on the volume and specific resource requirements of the batch jobs submitted.
    See all alternatives