Dell PowerScale Storage Adopted by Japan Research Institute for Affiliated Credit Card Company's Data Service Platform, Accelerating Modernization

Story Highlights

- Migration of data processing previously done on mainframes to an open data service platform. - Achieved stable handling of transactions increasing at approximately 20% annually. - Facilitated easy utilization of core data stored on the data service platform. - Enabled loose coupling between core systems and peripheral systems.

May 13, 2026:

Dell Technologies K.K. announced today that Japan Research Institute (Headquarters: Shinagawa-ku, Tokyo; President and Representative Director: Jun Uchikawa; hereinafter, JRI), the IT core company of SMBC Group, has adopted "Dell PowerScale" storage for the data service platform of its affiliated credit card company. As a result, this data service platform has been modernized from a mainframe to an open system, significantly improving stable handling of rapidly increasing payment transactions and enhancing data utilization capabilities across the entire organization.

Background of Adoption:

The affiliated credit card company faced an urgent need to offload high-load processes, including data processing, to an open data service platform to alleviate the burden on its mainframe. This was due to a surge in small-amount payments accompanying the spread of cashless payments in recent years, leading to a transaction volume increase of approximately 20% annually. The increasing processing load on the existing mainframe was also posing a potential risk to the stable operation of the entire core system.

Reasons for Adoption:

Based on its track record of utilizing Dell Technologies' unstructured storage (the predecessor of "PowerScale") as a data analysis platform, JRI adopted the scale-out storage "PowerScale" as the foundation's storage, ensuring high performance, reliability, and flexible scalability. The main reasons for adoption are as follows:

- Multi-protocol support: Compatible with a wide range of protocols such as NFS, HDFS, SMB, and S3, allowing data to be written directly from the mainframe via NFS and seamlessly processed on a Hadoop/Apache Spark-based platform. - Flexible scalability: As scale-out storage, performance and capacity can be expanded without stopping the system. - Mixed-generation model operation: Different generations of models can be mixed within a single cluster, achieving automatic balancing simply by adding nodes.

Effects of Introduction:

- Reduced mainframe load and realized stable operation: Even on days when tens of terabytes of data are generated overnight and a large volume of transactions are concentrated, the mainframe now operates stably without delay, securing performance equivalent to or better than before. - Simplified data linkage architecture and strengthened collaboration among developers: By utilizing "PowerScale" as a shared file server for mainframe and open systems, secure data transfer is possible without modifying existing processes or controls. This has also facilitated smoother communication between mainframe and Spark application developers. - Promotion of data utilization through loose coupling of core and peripheral systems: Decoupling the mainframe and the data service platform has eliminated concerns about the load on or impact to the mainframe, making it easier to utilize data in peripheral systems. - Establishment of a flexible DX foundation for future cloud integration: By preparing to leverage cloud storage protocols, an extensible and flexible foundation has been established that allows for more flexible data utilization across various cloud services and applications in the future. This lays the groundwork for continuous digital transformation within the group.

Comment:

Naoki Kobayashi, Director, Data Engineering Department, Data and Information Systems Division, Japan Research Institute, stated: "By building a new data service platform, we have achieved stable operation without being affected by the mainframe's transaction processing load, which was a long-standing issue, and have expanded the freedom of data utilization. This is a significant achievement. We believe this will greatly accelerate future modernization initiatives. Through this project, we have achieved loose coupling between the mainframe and the data service platform, and we expect that data utilization in peripheral systems will become even more flexible going forward. The multi-protocol support of 'PowerScale' was key to realizing this mechanism. We intend to leverage this feature to take on new challenges such as cloud integration in the future."

Dell Technologies Managing Executive Officer, Solutions