Find out in this report how the two Data Integration solutions compare in terms of features, pricing, service and support, easy of deployment, and ROI.
By replacing multiple legacy systems and teams with a single automated platform, organizations see significant cost savings and improved business operations.
For main recipes, there are charges, so by focusing on creating as many callable recipes as possible based on requirements, we can improve cost efficiency for the business.
In my experience, we have seen a return on investment, with results visible within a week.
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.
Whenever we faced issues with data volume, the support team helped us by suggesting solutions like breaking the data into chunks.
I reach out to the professional services team or customer success team for technical support, and they provide immediate responses.
Workato's support is robust, featuring first and second-level support.
There are scalability limitations with Workato.
Allows dynamic connection switching at runtime.
Even when clients overutilize the product, Workato allows them to continue without interruption, charging accordingly rather than limiting usage.
Once deployed, solutions do not break, making it more reliable than other solutions like Microsoft Power Automate that often disconnect.
During the initial data loads with large volumes, Workato was unable to handle the data effectively, which indicates stability issues under high loads.
To handle more than 50,000 records, I use scripting actions like Python or JavaScript to process large data in chunks.
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.
Workato struggles with scalability when handling high volumes of data, such as terabytes, requiring chunking for initial data loads.
One area for improvement is the CI/CD pipeline, which lacks a version control system similar to GitHub for easier deployment.
Currently, there's no way to set breakpoints to stop the process and debug an error as you can in other tools like webMethods.
Pricing for IBM InfoSphere DataStage is moderate and not much expensive.
Higher volume is less expensive, but in general, it is kind of pricey.
While the upfront cost is high due to task-based pricing, the cost is relatively low in terms of development because Workato provides necessary connectors for integration use cases.
Compared to other iPaaS solutions like Boomi, Workato’s pricing model charges per connection step, which increases the cost.
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.
It allows app-to-app and real-time integrations, which significantly enhance process efficiency.
It comes with pre-built connectors, eliminating the need to write APIs.
The platform's ease of use for connecting to different integrations, like Salesforce and NetSuite, is very beneficial because development isn't necessary, and everything is readily available.
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.
Named a Leader in iPaaS for Dynamic Integrations by Forrester, Workato is a modern automation and integration platform. With its enterprise-grade capabilities, you can seamlessly integrate and orchestrate workflow automation across cloud and on-premise applications, files and databases without coding.
The Workato team comes from a deep background in building integration products and will continue to expand and change the automation and integration space.
We monitor all Data Integration reviews to prevent fraudulent reviews and keep review quality high. We do not post reviews by company employees or direct competitors. We validate each review for authenticity via cross-reference with LinkedIn, and personal follow-up with the reviewer when necessary.
