

AWS Database Migration Service and AWS Glue both compete in the cloud data management and ETL space. AWS Database Migration Service has the upper hand for simpler migrations, while AWS Glue excels in large-scale ETL and integrated workflows.
Features: AWS Database Migration Service offers Change Data Capture for seamless data transfer, scalability, and robust security through encryption and IAM integration. AWS Glue stands out with its efficient data catalog system, integration capabilities for smooth ETL processes, and automation features that enhance ease of use and real-time backups.
Room for Improvement: AWS Database Migration Service needs better handling of large-scale data, improved error handling, and enhanced third-party integrations. AWS Glue could improve user satisfaction with better documentation, a more user-friendly interface, and reduced dependency on coding for less technical users. Both services could benefit from more responsive technical support and clearer error messaging.
Ease of Deployment and Customer Service: AWS Database Migration Service is typically deployed in the public cloud with ease of compatibility but faces mixed reviews in customer service quality. AWS Glue, while deeply integrated across cloud environments, is seen as complex with a steep learning curve for initial deployments. Users appreciate AWS's overall support, although inconsistencies in service quality have been noted.
Pricing and ROI: AWS Database Migration Service is seen as a cost-effective solution for smaller workloads, providing infrastructure savings over traditional tools. AWS Glue's pay-as-you-go model offers flexibility but can be cost-prohibitive for smaller companies. Database Migration Service offers better economy for basic migrations, while Glue provides greater value for complex, large-scale data processes.
I can specify savings of around 40 to 60%.
I advocate using Glue in such cases.
When working with AWS GovCloud, we often did not get an answer in time because AWS seemed more focused on the commercial side.
I am happy with the technical support from AWS.
Upgrades occur every four months, and new developments coincide with version updates.
For complex Glue-related problems such as job failures or permission issues, their documentation is good, but having direct access to support helps cut down troubleshooting time significantly.
Even if there was a failure, we could catch it and rerun it.
AWS's scalable nature involves a human approach, meaning it is not auto-scalable.
While scalability is good, latency exists due to our business nature.
It is beneficial to upgrade jobs, and we conduct extensive testing in development before migrating to production.
It can easily handle data from one terabyte to 100 terabytes or more, scaling nicely with larger datasets.
For DMS version upgrades, we schedule downtime during business hours so that midnight workloads are not interrupted and morning business can run smoothly.
AWS Glue is highly stable, and I would rate its stability as nine.
DMS works within AWS ecosystem, but they also have to look for third party solutions. Now Snowflake is a bigger player, or Databricks.
Sometimes, those who implement the service face problems and resolve it, but I may not even know what problems they faced.
Migrating jobs from version 3.0 to 4.0 can present compatibility issues.
With AWS, I gather data from multiple sources, clean it up, normalize it, de-duplicate it, and make it presentable.
A more user-friendly and simpler process would help speed up the deployment process.
Costing depends on resource usage, and cost optimization may involve redesigning jobs for flexibility.
AWS charges based on runtime, which can be quite pricey.
The smallest cost for a project is around €700, while the largest can reach up to €7,000 based on the scale of the usage.
AWS offers a way to build jobs that are scalable, expandable for new and current tables, and can be deployed quickly.
You can copy the database at first without impacting your current database, and then use CDC to copy incremental changes.
The scalability option is another valuable feature because AWS provides its own compute behind it, so I can scale up and scale down at any given point.
For ETL, I feel the performance is excellent. If I create jobs in a standard way, the performance is great, and maintenance is also seamless.
AWS Glue's most valuable features include its transformation capabilities, which provide data quality and shape for processing in ML or AI models.
AWS Glue has reduced efforts by 60%, which is the main benefit.
| Product | Mindshare (%) |
|---|---|
| AWS Glue | 7.6% |
| AWS Database Migration Service | 6.4% |
| Other | 86.0% |
| Company Size | Count |
|---|---|
| Small Business | 8 |
| Midsize Enterprise | 8 |
| Large Enterprise | 17 |
| Company Size | Count |
|---|---|
| Small Business | 11 |
| Midsize Enterprise | 6 |
| Large Enterprise | 32 |
AWS Database Migration Service facilitates database transfers with its automation, scalability, and cost-efficiency. Supporting real-time synchronization and schema transformations, it integrates with ETL tools and offers robust security, simplifying administration while focusing on data logic.
Highly effective for migrating databases like Oracle, SQL, and PostgreSQL from on-premises to cloud environments, AWS Database Migration Service supports live replication and Change Data Capture. It aids in seamless database replication and transformation, ensuring real-time data synchronization and secure AWS data storage. Users benefit from efficient workflows, reducing complex technical tasks during large data migrations. While praised for simplifying administration, areas for improvement include integration capabilities and pricing competitiveness. Enhanced handling of large-scale migrations, network bandwidth management, and third-party ecosystem support further augment its potential.
What are the key features of AWS Database Migration Service?In terms of industry-specific implementations, AWS Database Migration Service is widely used for industries requiring reliable and efficient data solutions such as finance, healthcare, and technology. It supports companies in maintaining real-time updates and securing sensitive information during cloud transitions, making it a key asset in streamlining database management and facilitating business transformation.
AWS Glue is a serverless data integration service offering seamless integration with AWS services like S3, Redshift, and Athena. Known for its flexibility with data formats and automation of ETL tasks, AWS Glue enhances data management and transformation.
AWS Glue facilitates seamless data extraction, transformation, and loading for businesses, integrating with key AWS services, allowing efficient data pipeline automation. It's valued for a user-friendly GUI, scalability, and cost-effectiveness, supporting PySpark for complex datasets and includes a robust data catalog, real-time backup capabilities, and code generation. Despite its strengths, improvements are needed in documentation, training, and broader programming language support. Users face challenges with its complex interface and integration with non-AWS products, driving demand for enhancements in its usability and performance.
What are AWS Glue's most important features?Businesses leverage AWS Glue in industries for ETL processes, data integration, and transformation. It is used to optimize data lakes or warehouses integration, enhancing data cataloging and real-time integration. Its serverless feature enables efficient data processing in sectors like finance and healthcare, where handling complex data-intensive tasks is crucial.
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