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AWS Data Pipeline vs Embulk: 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; Embulk: Bulk data loader that helps data transfer between various databases. It is an open-source bulk data loader that helps data transfer between various databases, storages, file formats, and cloud services.
AWS Data Pipeline and Embulk can be primarily classified as "Data Transfer" tools.
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, Embulk provides the following key features:
- Automatic guessing of input file formats
- Parallel & distributed execution to deal with big data sets
- Transaction control to guarantee All-or-Nothing
Embulk is an open source tool with 1.33K GitHub stars and 167 GitHub forks. Here's a link to Embulk's open source repository on GitHub.
Pros of AWS Data Pipeline
- Easy to create DAG and execute it1