

Informatica IDMC and Azure Data Factory are two leading platforms in the data management field. Each product has its strengths, though IDMC appears to have an edge with its comprehensive features and flexibility, while Azure Data Factory offers more accessible pricing and ease of use for small to medium businesses.
Features: IDMC includes seamless integration of MDM, data quality, and integration modules. It also features a repository of data models and offers high-performance data cleansing and validation capabilities. Azure Data Factory shines in data transformation, easy ETL pipeline creation, and connectivity with multiple data sources.
Room for Improvement: IDMC could improve its user interface and integrate more preconfigured business rules. Attention is also needed for reporting features and global address validation issues. Azure Data Factory needs enhancements in scheduling, Azure Machine Learning integration, and better real-time processing capabilities.
Ease of Deployment and Customer Service: IDMC supports on-premises, hybrid, and cloud environments, with solid customer service that could be slow for non-critical issues. Azure Data Factory integrates easily with other Azure services and generally offers satisfactory customer service, with faster cloud deployment compared to hybrid setups.
Pricing and ROI: IDMC is seen as a premium solution with higher licensing costs, justified by its comprehensive features. Azure Data Factory offers a competitive pay-as-you-go pricing structure, appealing to smaller businesses. It is suited for scalable cloud deployments with lower initial costs.
Our stakeholders and clients have expressed satisfaction with Azure Data Factory's efficiency and cost-effectiveness.
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.
The technical support from Microsoft is rated an eight out of ten.
The technical support is responsive and helpful
The technical support for Azure Data Factory is generally acceptable.
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.
Azure Data Factory is highly scalable.
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.
The solution has a high level of stability, roughly a nine out of ten.
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.
Incorporating more dedicated API sources to specific services like HubSpot CRM or Salesforce would be beneficial.
Sometimes, the compute fails to process data if there is a heavy load suddenly, and it doesn't scale up automatically.
There is a problem with the integration with third-party solutions, particularly with SAP.
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.
The pricing is cost-effective.
It is considered cost-effective.
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.
It connects to different sources out-of-the-box, making integration much easier.
The platform excels in handling major datasets, particularly when working with Power BI for reporting purposes.
Regarding the integration feature in Azure Data Factory, the integration part is excellent; we have major source connectors, so we can integrate the data from different data sources and also perform basic transformation while transforming, which is a great feature in Azure Data Factory.
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 (%) |
|---|---|
| Informatica Intelligent Data Management Cloud (IDMC) | 3.9% |
| Azure Data Factory | 3.7% |
| Other | 92.4% |


| Company Size | Count |
|---|---|
| Small Business | 31 |
| Midsize Enterprise | 19 |
| Large Enterprise | 57 |
| Company Size | Count |
|---|---|
| Small Business | 51 |
| Midsize Enterprise | 27 |
| Large Enterprise | 153 |
Azure Data Factory efficiently manages and integrates data from various sources, enabling seamless movement and transformation across platforms. Its valuable features include seamless integration with Azure services, handling large data volumes, flexible transformation, user-friendly interface, extensive connectors, and scalability. Users have experienced improved team performance, workflow simplification, enhanced collaboration, streamlined processes, and boosted productivity.
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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