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AWS Data Pipeline vs Google BigQuery Data Transfer Service: What are the differences?
What is 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.
What is Google BigQuery Data Transfer Service? Automate data movement from SaaS applications to Google BigQuery on a scheduled, managed basis. BigQuery Data Transfer Service lets you focus your efforts on analyzing your data. You can setup a data transfer with a few clicks. Your analytics team can lay the foundation for a data warehouse without writing a single line of code.
AWS Data Pipeline and Google BigQuery Data Transfer Service can be primarily classified as "Data Transfer" tools.
Pros of AWS Data Pipeline
- Easy to create DAG and execute it1