Informatica IDMC and AWS Step Functions compete in the enterprise data management and orchestration space. Informatica IDMC seems to have the upper hand due to its comprehensive data management, integration capabilities, and extensive feature set.
Features: Informatica IDMC provides seamless integration for data quality and master data management, supporting multiple domains with flexible architecture. Its modules cater to registry and consolidation styles, offering a comprehensive central data management solution. AWS Step Functions excels in providing robust orchestration capabilities, integrating seamlessly with AWS services and offering a user-friendly interface for task management.
Room for Improvement: Informatica IDMC requires enhancements in data stewardship and the user interface. Connectivity issues and complex configuration processes are also noted by users. AWS Step Functions could improve by offering more data transformation features and better integration with third-party solutions. Pricing flexibility and reducing dependency on the AWS ecosystem are also desired improvements.
Ease of Deployment and Customer Service: Informatica IDMC offers versatile deployment options including On-premises, Hybrid, and Private Cloud. However, deployment complexity and regional variance in customer service responsiveness are concerns. AWS Step Functions focuses on Public Cloud deployment, offering simplicity that users appreciate, though its technical support sometimes lacks the immediacy seen in IDMC's service.
Pricing and ROI: Informatica IDMC is considered expensive but delivers significant ROI through enhanced data management and quality. Its flexible pricing, though high, justifies its extensive features. AWS Step Functions adopts a consumption-based pricing model, often deemed cost-effective for AWS service users. Its scalability provides an attractive ROI, yet it may lack the feature depth offered by IDMC.
We see return on investment from this solution in terms of time; time reduction or cost benefits is what we are getting very good results from.
The speed of reply and the content of their responses usually solve the problems that arise.
I use enterprise support, which is excellent, providing responses within fifteen minutes.
If they are unsure how to resolve an issue, they keep customers informed, providing updates about progress and ensuring communication with the product team to deliver accurate responses.
The response time is pretty good because we have someone in-house, who is an expert from Informatica, in our team who can help us with any sort of queries usually.
I would rate it as nine out of ten for Informatica PowerCenter kind of products or the Informatica integration products.
Starting separate Step Functions for each request, making it highly scalable.
There isn't much need for scalability when creating orchestration in AWS Step Functions, which explains the rating of six.
I find Informatica Intelligent Data Management Cloud (IDMC) to be a sustainable and scalable solution.
As a SaaS platform, IDMC is quite scalable and provides complete flexibility.
If one zone fails, others handle the demand, ensuring high availability.
I never faced any faults or issues due to its stability with AWS, making it very reliable with no downtime and 100% reliability.
Stability is crucial because IDMC holds business-critical data, and it needs to be available all the time for business users.
It would benefit from more integration with different applications or services.
The observability concept in Informatica Intelligent Data Management Cloud (IDMC) needs improvement as the capabilities are not up to the mark compared to the industry.
One of my clients has a requirement; they want to integrate metadata into the process, which means, for example, if I just want to implement a new field into my database, that field needs to be reflected throughout, let's say, 200 mappings. This highlights the need for a data-driven approach.
I also want to see integration with other Informatica products, such as IICS, to leverage the metadata from EDC.
Pricing for Step Functions is very cheap.
The cost is average, provided it is configured correctly.
It ranges from a quarter million to a couple of million a year.
The licenses are too expensive compared to before, which is why customers are now preferring other data metadata management tools like OneTrust, Collibra, and Azure Purview.
I think the costs are reasonable for the kinds of features that Informatica Intelligent Data Management Cloud (IDMC) has.
Step Functions provide seamless integration with AWS services, which enhances the speed of application development.
It was particularly valuable for its integration capabilities, allowing for execution of scripts and data migration.
AWS Step Functions offers advanced workflows that save time and enhance efficiency by reducing delays and ensuring consistent orchestration among various services.
In on-premise, we call it EDC for metadata management, while in cloud-based technologies, it is known as the Metadata Command Center, which serves the same purpose as EDC concerning CDGC.
Informatica Intelligent Data Management Cloud (IDMC) can connect to pretty much any application, including Oracle Analytics and Power BI, and it works quite seamlessly.
The platform's ability to pull in data from other platforms without the need for an additional integration tool enhances its appeal.
| Product | Market Share (%) |
|---|---|
| AWS Step Functions | 2.1% |
| Informatica Intelligent Data Management Cloud (IDMC) | 1.4% |
| Other | 96.5% |
| Company Size | Count |
|---|---|
| Small Business | 7 |
| Midsize Enterprise | 2 |
| Large Enterprise | 5 |
| Company Size | Count |
|---|---|
| Small Business | 42 |
| Midsize Enterprise | 24 |
| Large Enterprise | 134 |
AWS Step Functions integrate seamlessly with other AWS services to offer efficient pipeline and workflow management. Its intuitive design allows for streamlined orchestration, easily handling complex tasks.
AWS Step Functions provide robust orchestration and automation capabilities, simplifying the creation of workflows with graphical and JSON-based designs. It excels in managing tasks through advanced parallelization and error handling features. Automatic scaling further enhances performance, ensuring reliability in varied environments. However, improvements are needed in IDE integration, larger data handling, and fault tolerance. Users find value in its capacity for microservice orchestration and data integration, although dependency on the Amazon ecosystem and limited third-party integrations pose challenges.
What are the key features of AWS Step Functions?In industries managing data pipelines, AWS Step Functions orchestrate workflows, execute parallel ETL jobs, and integrate various AWS services, enabling smoother operations and efficient data migration. Companies benefit from streamlined processes and robust handling of interdependent tasks.
Informatica Intelligent Data Management Cloud (IDMC) integrates data quality, governance, and integration with flexible architecture. It supports multiple domains and a data models repository, delivering AI-enhanced data management across cloud-native platforms.
IDMC provides seamless integration and governance capabilities that support diverse data environments. Its comprehensive suite includes customizable workflows, data profiling, and metadata management. AI features, a data marketplace, and performance scalability enhance data management. While its interface poses challenges, its robust matching and cloud-native integration facilities are essential for complex data ecosystems. Users employ IDMC for connecting systems, ensuring data quality, and supporting data compliance but seek better pre-built rules, services, and improved connectivity, especially with platforms like Salesforce. Licensing, cost, and added AI functionalities are areas for potential refinement.
What are the key features of IDMC?IDMC is implemented across industries for data integration, metadata management, and governance. Organizations use it to connect systems, migrate data to cloud environments, and maintain data quality. They manage master data and automate business processes, facilitating data lineage and ensuring compliance with privacy regulations.
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