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AWS Data Pipeline

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Synth

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Synth vs AWS Data Pipeline: What are the differences?

What is Synth? Realistic, synthetic test data for your app. It is the quickest way to create accurate synthetic clones of your entire data infrastructure It creates end-to-end synthetic data environments that look and behave exactly like your production data. Down to your data's content and database version..

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.

Synth and AWS Data Pipeline can be primarily classified as "Data Transfer" tools.

Some of the features offered by Synth are:

  • Powered by AI
  • Safe by design
  • Developers first

On the other hand, AWS Data Pipeline provides the following key features:

  • 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
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Pros of AWS Data Pipeline
Pros of Synth
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    Easy to create DAG and execute it
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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 Synth?

    It is the quickest way to create accurate synthetic clones of your entire data infrastructure. It creates end-to-end synthetic data environments that look and behave exactly like your production data. Down to your data's content and database version.

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

    What companies use AWS Data Pipeline?
    What companies use Synth?
      No companies found
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      What tools integrate with AWS Data Pipeline?
      What tools integrate with Synth?
      What are some alternatives to AWS Data Pipeline and Synth?
      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