AWS Data Pipeline vs Google BigQuery Data Transfer Service

AWS Data Pipeline
AWS Data Pipeline

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Google BigQuery Data Transfer Service
Google BigQuery Data Transfer Service

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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.

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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 Google BigQuery Data Transfer Service?

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.

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          What are some alternatives to AWS Data Pipeline and Google BigQuery Data Transfer Service?
          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.
          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.
          FlyData
          FlyData for Amazon Redshift allows you to transfer your data easily and securely to Amazon Redshift. Getting your data onto Amazon Redshift and keeping it up-to-date can be a real hassle. With FlyData for Amazon Redshift, you can automatically upload and migrate your data to Amazon Redshift, after only a few simple steps.
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