AWS Data Pipeline vs. Mage

AWS Data Pipeline is a web service that helps you reliably process and move data between different AWS compute and storage services, as well as on-premises data sources, at specified intervals. With AWS Data Pipeline, you can regularly access your data where it’s stored, transform and process it at scale, and efficiently transfer the results to AWS services such as Amazon S3, Amazon RDS, Amazon DynamoDB, and Amazon EMR.

Incentivized

Mage is well-suited for probability score for uptake of every product is calculated for customers using ML/ Regression models, choosing customers for a product/ Top products for a customer, based on the requirement and Identifying popular product combinations using association rules from Market Basket Analysis (or affinity Analysis)\Bundle these products as combos.

Incentivized

• Helps you easily create complex data processing workloads
• Fault tolerant
• Highly available

Incentivized

• Ranking algorithms.
• Cloud-based tool.
• Increase user engagement.

Incentivized

• Pipeline Stuck in Pending Status
• Pipeline Component Stuck in Waiting for Runner Status
• EMR Cluster Fails With Error

Incentivized

• Acquisition Contribution.
• Business Intelligence Reporting.
• Data Destinations.

Incentivized

AWS data pipelines are easy to use over data factory for data engineers

Incentivized

Mage was the easiest in terms of ease of implementation due to its no-code functionality. However, Mage doesn't have a whole ecosystem like AWS and slightly falls behind there.

Incentivized

• Easy to use
• Data engineers are able to create the data pipelines quickly and effectively
• Scalable and Fault tolerant

Incentivized

• Business Understanding.
• Data Acquisition and Understanding.
• Data Modeling and Evaluation.

Incentivized