AWS Database Migration Service vs. AWS Glue

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.

Incentivized

One of AWS Glue's most notable features that aid in the creation and transformation of data is its data catalog. Support, scheduling, and the automation of the data schema recognition make it superior to its competitors aside from that. It also integrates perfectly with other AWS tools. The main restriction may be integrated with systems outside of the AWS environment. It functions flawlessly with the current AWS services but not with other goods. Another potential restriction that comes to mind is that glue operates on a spark, which means the engineer needs to be conversant in the language.

Incentivized

• It is extremely fast, easy, and self-intuitive. Though it is a suite of services, it requires pretty less time to get control over it.
• As it is a managed service, one need not take care of a lot of underlying details. The identification of data schema, code generation, customization, and orchestration of the different job components allows the developers to focus on the core business problem without worrying about infrastructure issues.
• It is a pay-as-you-go service. So, there is no need to provide any capacity in advance. So, it makes scheduling much easier.

Incentivized

• In-Stream schema registries feature people can not use this more efficiently
• in Connections feature they can add more connectors as well
• The crucial problem with AWS Glue is that it only works with AWS.

Incentivized

While easy to set up and manage monitoring for large datasets, its complexity can be a barrier for new users. Integration with AWS Ecosystem, Managed Monitoring, Dashboards and monitoring tools for AWS Glue are generally easy to set up and maintain, Automated Data Pipelines. Automates data pipeline creation, making it efficient for certain data integration

Incentivized

Amazon responds in good time once the ticket has been generated but needs to generate tickets frequent because very few sample codes are available, and it's not cover all the scenarios.

Incentivized

AWS Glue is a fully managed ETL service that automates many ETL tasks, making it easier to set AWS Glue simplifies ETL through a visual interface and automated code generation.

• 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

• We are using GLUE for our ETL purpose. it’s ease with other our AWS services makes our ROI, 100% ROI.
• One missing piece was compatibility with other data source for which we found a work around and made our data source as S3 only, so our dependencies on other data source is also reducing

Incentivized