AWS Data Pipeline vs Google BigQuery Data Transfer Service

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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 tools integrate with AWS Data Pipeline?
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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.
        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.
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