

Find out what your peers are saying about Amazon Web Services (AWS), Informatica, Palantir and others in Cloud Data Integration.
I can specify savings of around 40 to 60%.
Reliable data plus less human intervention and less error result in a strong return on investment.
I am happy with the technical support from AWS.
When working with AWS GovCloud, we often did not get an answer in time because AWS seemed more focused on the commercial side.
The support for SAS in Brazil is not the best one, but the support in Sweden is really good, as they visit the company and work to solve the issues.
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.
Minor version upgrades are handled by DMS automatically.
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.
There is significant room for improvement, especially with regard to using a hybrid approach that involves both CAS and persistent storage.
SAS Data Management can be improved in terms of the learning curve.
From my experience, SAS Data Management is an expensive tool.
My main valuable features of AWS Database Migration Service include the ability to move data securely and continuously synchronize changes during the migration process, ensuring a smooth transition to the cloud.
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.
SAS Data Management stands out because of its data standardization, transformation, and verification capabilities.
The best features I appreciate about SAS Data Management tool are that it's easy to create the flows and schedule data, and the tables are not too big, making it easy to control the ETL process, including user access which is also easy to manage in SAS.
SAS Data Management's best feature is first, data reliability because SAS Data Management is a very trusted platform.

| Company Size | Count |
|---|---|
| Small Business | 8 |
| Midsize Enterprise | 9 |
| Large Enterprise | 17 |
| Company Size | Count |
|---|---|
| Small Business | 8 |
| Midsize Enterprise | 2 |
| Large Enterprise | 8 |
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.
SAS Data Management provides data integration, governance, and robust reporting tools. It connects to diverse data sources, ensuring quality management and enabling data analysis for technical and non-technical users.
SAS Data Management features flexible data flow creation, scheduling, and ETL control. It enhances data integration and metadata management with tools that support data standardization. Users benefit from its importing and exporting capabilities, connecting to multiple sources. It facilitates improved data quality management and offers a flexible language for diverse needs. Data visualization capabilities further support decision-making across industries, automating reports and data warehouses.
What are the key features of SAS Data Management?SAS Data Management helps industries like finance integrate diverse data sources for analytics and reporting. It is used for tasks such as financial reporting, credit risk analysis, and data cleansing. Through user-driven automation, it aids in aligning data warehouses and generating insightful visual outputs, making it ideal for analyzing structured data from sources like Excel and CSV files.
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