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Data Streaming

96 posts
The Rise of Kappa Architecture in the Age of Agentic AI with Data Streaming using Apache Kafka and Flink
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  • 9 minute read

The Rise of Kappa Architecture in the Era of Agentic AI and Data Streaming

The shift from Lambda to Kappa architecture reflects the growing demand for unified, real-time data pipelines that serve both analytical and operational needs. With the rise of Agentic AI and streaming-first systems, Kappa—powered by Apache Kafka and Apache Flink—delivers low-latency, event-driven infrastructure that supports modern applications, from scalable data products to autonomous AI agents. Open table formats and Shift Left principles further establish Kappa as the foundation for consistent, governed, and future-ready data platforms.
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Real-Time FinOps with Data Streaming using Apache Kafka and Flink
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  • 6 minute read

FinOps in Real Time: How Data Streaming Transforms Cloud Cost Management

FinOps bridges the gap between finance and engineering to control cloud spend in real time. However, many organizations still rely on delayed, batch-driven data pipelines that limit visibility and slow down decisions. This blog explores how Apache Kafka and Apache Flink enable real-time, governed FinOps by streaming cloud usage data as it happens. It covers the challenges of data governance, compliance, and cross-functional accountability—and how streaming architecture addresses them. Real-world examples from Bitvavo and SumUp show how financial services companies scale securely, build cost-aware teams, and improve agility using event-driven platforms.
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Open RAN and Data Streaming with Apache Kafka and Flink in Telecom Industry for Network Analytics and Observability
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  • 8 minute read

Open RAN and Data Streaming: How the Telecom Industry Modernizes Network Infrastructure with Apache Kafka and Flink

Open RAN is transforming telecom by decoupling hardware and software to unlock flexibility, innovation, and cost savings. But to fully realize its potential, telcos need real-time data streaming for observability, automation, and AI. This post shows how Apache Kafka, Apache Flink, and a diskless data streaming platform like Confluent WarpStream help telco operators scale RAN data processing securely and cost-effectively.
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FinTech Alpian using Data Streaming and Agentic AI with Apache Kafka in Switzerland Regulated Market
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  • 6 minute read

Agentic AI and RAG in Regulated FinTech with Apache Kafka at Alpian Bank

Regulated FinTech is transforming financial services by combining compliance with innovation. This post explores how real-time data streaming with Apache Kafka and Flink enables modern architecture, personalization, and AI integration—while maintaining strict governance. Alpian, a fully licensed Swiss digital bank, showcases how Agentic AI, RAG, and domain-driven design work together in a compliant, cloud-only environment.
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Real Time AI for Mobile Gaming and eSports at MPL with Data Streaming using Apache Kafka and Flink
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  • 6 minute read

How MPL Uses Data Streaming to Lead in Mobile Gaming and eSports

Mobile Premier League (MPL) is a leading mobile eSports skill-based gaming platform with over 90 million users. To meet the demands of real-time personalization, fraud detection, and user engagement, MPL transitioned from traditional batch processing to a modern data streaming architecture powered by Apache Kafka, Apache Flink, and Confluent Cloud. This blog explores the architectural shift, key use cases, including real-time Machine Learning inference and feature orchestration, and the business outcomes achieved, such as increased trust, lower operational costs, and improved player retention. The MPL success story highlights the value of a data streaming platform in building responsive, intelligent, and secure gaming platforms.
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Mainframe Modernization and Integration with Data Streaming using Apache Kafka IBM MQ IIDR CDC Precisely Qlik
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  • 14 minute read

Mainframe Integration with Data Streaming: Architecture, Business Value, Real-World Success

The mainframe is evolving—not fading. With cloud-native features, AI acceleration, and quantum-safe encryption, platforms like IBM z16 and z17 remain central to critical industries. But modern demands require real-time data access and system agility. Apache Kafka and Flink make this possible by streaming data bi-directionally between DB2, IMS, and MQ and cloud analytics platforms. This enables event-driven architectures without disrupting core systems. This post outlines proven strategies—offloading, integration, and replacement—and includes real-world examples across industries. The result: lower costs, faster innovation, and smarter use of legacy systems.
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How Penske Logistics Transforms Fleet Intelligence with Kafka and AI
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  • 7 minute read

How Penske Logistics Transforms Fleet Intelligence with Data Streaming and AI

Real-time visibility has become essential in logistics. As supply chains grow more complex, providers must shift from delayed, batch-based systems to event-driven architectures. Data Streaming technologies like Apache Kafka and Apache Flink enable this shift by allowing continuous processing of data from telematics, inventory systems, and customer interactions. Penske Logistics is leading the way—using Confluent’s platform to stream and process 190 million IoT messages daily. This powers predictive maintenance, faster roadside assistance, and higher fleet uptime. The result: smarter operations, improved service, and a scalable foundation for the future of logistics.
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Data Streaming with Confluent Meets SAP and Databricks for Agentic AI at Sapphire in Madrid
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  • 6 minute read

Data Streaming Meets the SAP Ecosystem and Databricks – Insights from SAP Sapphire Madrid

SAP Sapphire 2025 in Madrid brought together global SAP users, partners, and technology leaders to showcase the future of enterprise data strategy. Key themes included SAP’s Business Data Cloud (BDC) vision, Joule for Agentic AI, and the deepening SAP-Databricks partnership. A major topic throughout the event was the increasing need for real-time integration across SAP and non-SAP systems—highlighting the critical role of event-driven architectures and data streaming platforms like Confluent. This blog shares insights on how data streaming enhances SAP ecosystems, supports AI initiatives, and enables industry-specific use cases across transactional and analytical domains.
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Data Streaming Lake Warehouse and Lakehouse with Confluent Databricks Snowflake using Iceberg and Tableflow Delta Lake
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  • 12 minute read

Databricks and Confluent Leading Data and AI Architectures – What About Snowflake, BigQuery, and Friends?

Confluent, Databricks, and Snowflake are trusted by thousands of enterprises to power critical workloads—each with a distinct focus: real-time streaming, large-scale analytics, and governed data sharing. Many customers use them in combination to build flexible, intelligent data architectures. This blog highlights how Erste Bank uses Confluent and Databricks to enable generative AI in customer service, while Siemens combines Confluent and Snowflake to optimize manufacturing and healthcare with a shift-left approach. Together, these examples show how a streaming-first foundation drives speed, scalability, and innovation across industries.
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Shift Left Architecture with Confluent Data Streaming and Databricks Lakehouse Medallion
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  • 9 minute read

Shift Left Architecture for AI and Analytics with Confluent and Databricks

Confluent and Databricks enable a modern data architecture that unifies real-time streaming and lakehouse analytics. By combining shift-left principles with the structured layers of the Medallion Architecture, teams can improve data quality, reduce pipeline complexity, and accelerate insights for both operational and analytical workloads. Technologies like Apache Kafka, Flink, and Delta Lake form the backbone of scalable, AI-ready pipelines across cloud and hybrid environments.
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