User friendly, reliable as it retries in case of any failure. Review collected by and hosted on G2.com.
Space consuming, difficult to setup and lags on slow in internet. Review collected by and hosted on G2.com.
Simplicity compared to software like SQL Review collected by and hosted on G2.com.
Integration with something other than AWS could be stronger. Review collected by and hosted on G2.com.
The only thing I can appreciate is once it is setup then it is fine. Review collected by and hosted on G2.com.
It really should be redesigned as a json blob is a terrible way to organize SQL jobs. Why can't things be scheduled like a calendar or meeting request? Review collected by and hosted on G2.com.
AWS Data Pipeline makes it very easy to get started and move data between various sources. If you're already using AWS services such as S3 or Redshift, Data Pipeline heavily reduces the lines of code / applications required to move data between AWS data sources.
You can simply run data pipeline on a schedule, specify where you want to move data between, and tell it to run processing in a series of steps if you need to filter your data. It is a good and simple way to do basic data movement.
Pipeline retries, gives you errors, and has a dashboard that shows you all of the jobs that are in queue. Review collected by and hosted on G2.com.
Data Pipeline can be a black box at times. Error messages are not good, and it is difficult to understand what exactly failed since it is an amazon service. The scheduler doesn't give timely notifications at times, so it is hard to determine the true state of the data pipeline Review collected by and hosted on G2.com.
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