

Informatica Intelligent Data Management Cloud and AWS Database Migration Service both operate in the competitive data management space. IDMC appears to have the edge with its comprehensive suite of features for data management, while AWS DMS stands out for its cost-effectiveness in database migration tasks.
Features: IDMC offers robust data integration capabilities across MDM and data quality with a model-driven architecture that supports seamless governance across domains. It includes customizable workflows and flexible architecture supporting registry, consolidation, and coexisting styles, thus ensuring integration across various environments. AWS DMS, however, is recognized for its efficient database migration capabilities, enabling swift migrations with minimal downtime and user-friendly functionality.
Room for Improvement: Users of IDMC suggest enhancing preconfigured business rules and improving its reporting and data stewardship features. Additionally, its user interface could benefit from improvements and better integration with SAP. AWS DMS could improve its support for data type conversion and extend its compatibility with non-AWS services. Enhancing initial migration processes and global support integration would also be beneficial.
Ease of Deployment and Customer Service:IDMC supports deployment on on-premises, hybrid, and public clouds, offering flexibility but involves a complex setup process. In terms of customer service, IDMC is known for responsiveness, although resolution times can vary based on contracts. AWS DMS simplifies deployment with its cloud-oriented approach, although this limits on-premises capabilities. AWS provides effective customer service, but technical support consistency and responsiveness can sometimes require persistence.
Pricing and ROI: IDMC’s feature set often leads to significant ROI over time, despite its expensive and usage-based licensing models resulting in high costs. In comparison, AWS DMS is praised for its cost-effectiveness, particularly for migration-focused tasks, though it might lack in meeting comprehensive data management needs.
I can specify savings of around 40 to 60%.
Leadership prefers to utilize third-party tools, such as Snowflake, which has both storage and ELT features.
The stability and performance remain issues.
Compared to Collibra Catalog, where the value is noticeable within six months.
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.
Due to the tool's maturity limitations, solutions are not always simple and often require workarounds.
Even after going out of service support, they still reached back to me whenever I raised tickets.
We expect more responsive assistance because they have the expertise since Informatica is their tool, but I don't see enough expertise on the Informatica support side.
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.
I have used the product over multiple systems and was able to write reports for large data sets without any performance issues.
As a SaaS platform, IDMC is quite scalable and provides complete flexibility.
There are many options available, and the licensing model is quite good, supporting our needs effectively.
For DMS version upgrades, we schedule downtime during business hours so that midnight workloads are not interrupted and morning business can run smoothly.
Stability is crucial because IDMC holds business-critical data, and it needs to be available all the time for business users.
There are substantial stability issues with Informatica Cloud Data Quality on the cloud.
I find the stability to be good, with occasional restarts required every two to three months due to glitches.
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.
The tool needs to mature in terms of category-specific attributes or dynamic attributes.
The current solution requires code-writing and tweaking, while other solutions offer material-level matches.
If the development interface could be optimized to have fewer modules, it would be greatly beneficial.
It ranges from a quarter million to a couple of million a year.
Informatica Intelligent Cloud Services is affordable for my specific use cases, with the pricing being rated three or four on a scale where one is very cheap.
Regarding pricing, compared to other tools I have worked with, Informatica offers competitive pricing, which I find not high in terms of starting strategy.
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.
The platform's ability to pull in data from other platforms without the need for an additional integration tool enhances its appeal.
The connectors serve as the main functionality, making data integration processes more efficient by saving time and effort.
We could run data quality rules as part of Service Bus, which ensured the integrity of customer information before it was entered into our database.
| Product | Market Share (%) |
|---|---|
| AWS Database Migration Service | 7.8% |
| Informatica Intelligent Data Management Cloud (IDMC) | 6.7% |
| Other | 85.5% |

| Company Size | Count |
|---|---|
| Small Business | 8 |
| Midsize Enterprise | 8 |
| Large Enterprise | 17 |
| Company Size | Count |
|---|---|
| Small Business | 51 |
| Midsize Enterprise | 27 |
| Large Enterprise | 153 |
AWS Database Migration Service, also known as AWS DMS, is a cloud service that facilitates the migration of relational databases, NoSQL databases, data warehouses, and other types of data stores. The product can be used to migrate users' data into the AWS Cloud or between combinations of on-premises and cloud setups. The solution allows migration between a wide variety of sources and target endpoints; the only requirement is that one of the endpoints has to be an AWS service. AWS DMS cannot be used to migrate from an on-premises database to another on-premises database.
AWS Database Migration Service allows users to perform one-time migrations, as well as replications of ongoing changes to keep sources and targets in sync. Organizations can utilize the AWS Schema Conversion Tool to translate their database schema to a new platform and then use AWS DMS to migrate the data. The product offers cost efficiency as a part of the AWS Cloud, as well as speed to market, flexibility, and security.
The main use cases of AWS Database Migration Service include:
AWS Database Migration Service Components
AWS Database Migration Service consists of various components which function together to achieve users’ data migration. A migration on AWS DMS is structured in three levels: a replication instance, source and target endpoints, and a replication task. The components include the following actions:
AWS Database Migration Service Benefits
AWS Database Migration Service offers its users a wide range of benefits. Among them are the following:
Reviews from Real Users
Vishal S., an infrastructure lead at a computer software company, likes AWS Database Migration Service because it is easy to use and set up.
Vinod K., a data analyst at AIMLEAP, describes AWS DMS as an easy solution to save and extract data.
Informatica Intelligent Data Management Cloud (IDMC) offers seamless integration of master data management, data quality, and data integration with a cloud-native architecture supporting multiple data management styles, optimizing data governance through metadata management.
IDMC enhances data synchronization and mapping tasks, utilizing a broad range of connectors to interact efficiently with data sources. Its precise address validation via AddressDoctor and intuitive navigation bolster user empowerment, delivering agility, scalability, and security in data governance. Despite its strengths, areas like ease of use, SAP integration, and reporting could benefit from enhancements. Connectivity issues and workflow complexities are noted, needing improvements in performance, support, and licensing cost. Users demand expanded ETL capabilities, real-time processing, and broader data source support to address growing data needs.
What are the key features of IDMC?In industries such as banking, healthcare, and telecom, IDMC is implemented for data integration, cloud migration, and enhancing data quality. Its capabilities are crucial for metadata management, lineage tracking, and real-time processing, ensuring high data quality and streamlined operations.
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