AWS Data Pipeline vs. AWS Database Migration Service

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.

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As stated previously, AWS Database Migration Service excels when replicating very specific data elements between environments. AWS Database Migration Service handles replication tasks to load equipment assets or customer job sites from production to QA databases very well. Full load replication - e.g., we need an exact copy of the production database in another region - works well. But when we need to load the QA database with the latest production data - it does work as well. AWS Database Migration Service comes up short because we do not want to wipe the QA database completely and make an exact copy. We want to keep what's already in the QA database and add production data so that we can QA with that level of volume. And at least with our database design, we end up having to do a lot of manual data manipulation and de-duplication.

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

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

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Independently Invited by TrustRadius

A de minimis incentive was given to thank the reviewer for their time. The incentive was not used to bias or drive a particular response, nor was the incentive contingent on a positive endorsement. More Info

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

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

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Independently Invited by TrustRadius

A de minimis incentive was given to thank the reviewer for their time. The incentive was not used to bias or drive a particular response, nor was the incentive contingent on a positive endorsement. More Info

• Set it and forget it for maintaining data consistency - moderate cost, zero to minimal maintenance
• High touch production data loads into QA - negative ROI engineering time investment far exceeded our predictions

Incentivized

Independently Invited by TrustRadius

A de minimis incentive was given to thank the reviewer for their time. The incentive was not used to bias or drive a particular response, nor was the incentive contingent on a positive endorsement. More Info