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IBM

Confluent on IBM zSystems: the leading event streaming solution for your application modernization strategy

IBM zSystems customers are looking for cost-effective solutions that can power their next generation of internal and external facing applications, many of which are real-time and mission critical. With Confluent on IBM zSystems, enterprises now have the capabilities they need to modernize their mainframe applications with a resilient data streaming platform.

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Why Confluent with IBM zSystems?

The leading event streaming solution for your application modernization strategy

Drive real-time data pipelines with IBM zSystems data

Reduce reliance on batch processing on your IBM zSystems while capturing zSystems data in real-time for fast analytics and business intelligence with minimal latency. Correlate with other data flowing through Confluent to drive the needs of the digital enterprise.

Build modern, resilient streaming applications

Extend core applications on IBM zSystems with modern, distributed microservices by making the data readily available with Confluent. Accelerate development times and implement a modern event based architecture using IBM and Confluent together.

Increase the ROI of your IBM zSystems investment

Change the economics of your mainframe by optimizing costs while also increasing the return on the data. Confluent on z/OS exploits the underlining processor cores that reduce processing costs and take advantage of data being accessible in the Confluent Connector. This solution increases the value of your mainframe as a critical piece of your hybrid data architecture.

Unlocking IBM zSystems Data

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Together Confluent and IBM partner with leading enterprises

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"Enterprises building real-time applications with IBM zSystems often leverage data events as a central part of their hybrid cloud strategy. Confluent on IBM zSystems offers a unique and compelling solution for data events in their hybrid data platform to empower those enterprises."

Kyle Charlet, CTO IBM zSystems Software, Distinguished Engineer

Use Cases

Retail

Access inventory data for seamless omnichannel experiences. Identify trends, analyze transactions, and deliver personalized recommendations and offers, all in real time.

Banking

Perform fraud analytics to identify patterns and power machine learning algorithms. Capture, aggregate, and filter data from all security log resources to adhere to various regulatory requirements.

Insurance

Accelerate claim processing and deliver improved customer experience by moving claim processing from batch to real time. Detect anomalies to pre-emptively identify potentially fraudulent activities.