Find out what your peers are saying about Microsoft, Informatica, Talend and others in Data Integration.
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 tool has made us tremendously more efficient and saved us a significant amount of money.
Using SSIS has proven cost-effective as there are no additional fees outside the SQL Server license, and it significantly enhances data management efficiency.
We also have the flexibility to submit a feature request to be included as part of the wishlist, potentially becoming a product feature in subsequent releases.
IBM tech support has allocated dedicated resources, making it satisfactory.
Due to the tool's maturity limitations, solutions are not always simple and often require workarounds.
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.
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 first line of support needs to be more knowledgeable.
As a SaaS platform, IDMC is quite scalable and provides complete flexibility.
I find Informatica Intelligent Data Management Cloud (IDMC) to be a sustainable and scalable solution.
Stability is crucial because IDMC holds business-critical data, and it needs to be available all the time for business users.
It processes large volumes of data quickly.
I wonder if it supports other areas, such as cloud environments with open source support, or EdgeShift.
The solution needs improvement in connectivity with big data technologies such as Spark.
The tool needs to mature in terms of category-specific attributes or dynamic attributes.
I also want to see integration with other Informatica products, such as IICS, to leverage the metadata from EDC.
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.
Within the South African context, if you are getting your enterprise agreement from First Technology, they don't provide support.
SSIS has a difficult learning curve when dealing with complex transformations.
The logging capabilities could be improved, particularly for error logging.
Pricing for IBM InfoSphere DataStage is moderate and not much expensive.
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.
Utilizing SSIS involves no extra charges beyond the SQL Server license.
It was included in our licensing for SQL server, and our licensing for SQL server was extremely cheap, making it a very good price point for us.
It is straightforward from a design and development perspective, and also for deployment.
As we are a financial organization, security is our main concern, so we prefer enterprise tools.
The platform's ability to pull in data from other platforms without the need for an additional integration tool enhances its appeal.
Informatica Intelligent Data Management Cloud (IDMC) can connect to pretty much any application, including Oracle Analytics and Power BI, and it works quite seamlessly.
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.
I would rate it at a 10 as it is highly reliable; we have never had any problems with it.
One of the best aspects of SSIS is that it is built into Microsoft SQL Server, so there are no additional costs involved.
SSAS is included in the base installation of SQL Server.
| Product | Market Share (%) |
|---|---|
| SSIS | 5.9% |
| Informatica Intelligent Data Management Cloud (IDMC) | 3.6% |
| IBM InfoSphere DataStage | 3.7% |
| Other | 86.8% |
| Company Size | Count |
|---|---|
| Small Business | 23 |
| Midsize Enterprise | 4 |
| Large Enterprise | 25 |
| Company Size | Count |
|---|---|
| Small Business | 42 |
| Midsize Enterprise | 24 |
| Large Enterprise | 134 |
| Company Size | Count |
|---|---|
| Small Business | 26 |
| Midsize Enterprise | 19 |
| Large Enterprise | 57 |
IBM InfoSphere DataStage is a high-quality data integration tool that aims to design, develop, and run jobs that move and transform data for organizations of different sizes. The product works by integrating data across multiple systems through a high-performance parallel framework. It supports extended metadata management, enterprise connectivity, and integration of all types of data.
The solution is the data integration component of IBM InfoSphere Information Server, providing a graphical framework for moving data from source systems to target systems. IBM InfoSphere DataStage can deliver data to data warehouses, data marts, operational data sources, and other enterprise applications. The tool works with various types of patterns - extract, transform and load (ETL), and extract, load, and transform (ELT). The scalability of the platform is achieved by using parallel processing and enterprise connectivity.
The solution has various versions, catering to different types of companies, which include the Server Edition, the Enterprise Edition, and the MVS Edition. Depending on which version a company has bought, different goals can be achieved. They include the following:
IBM InfoSphere DataStage can be deployed in various ways, including:
IBM InfoSphere DataStage Features
The tool has various features through which users can integrate and utilize their data effectively. The components of IBM InfoSphere DataStage include:
IBM InfoSphere DataStage Benefits
This solution offers many benefits for the companies that utilize it for data integration. Some of these benefits include:
Reviews from Real Users
A data/solution architect at a computer software company says the product is robust, easy to use, has a simple error logging mechanism, and works very well for huge volumes of data.
Tirthankar Roy Chowdhury, team leader at Tata Consultancy Services, feels the tool is user-friendly with a lot of functionalities, and doesn't require much coding because of its drag-and-drop features.
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.
SSIS is a versatile tool for data integration tasks like ETL processes, data migration, and real-time data processing. Users appreciate its ease of use, data transformation tools, scheduling capabilities, and extensive connectivity options. It enhances productivity and efficiency within organizations by streamlining data-related processes and improving data quality and consistency.
