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.
AWS Data Pipeline is a tool in the Data Transfer category of a tech stack.
Who uses AWS Data Pipeline?
29 companies reportedly use AWS Data Pipeline in their tech stacks, including Coursera, Wealthsimple, and Dek-D.
64 developers on StackShare have stated that they use AWS Data Pipeline.
AWS Data Pipeline Integrations
Pros of AWS Data Pipeline
Easy to create DAG and execute it
AWS Data Pipeline's 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
- Periodic replication of on-premise JDBC database tables into RDS
AWS Data Pipeline Alternatives & Comparisons
What are some alternatives to AWS Data Pipeline?
See all alternatives
A fully managed extract, transform, and load (ETL) service that makes it easy for customers to prepare and load their data for analytics.
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.
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.
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.