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The Data Streaming Landscape 2025

Data streaming is a new software category. It has grown from niche adoption to becoming a fundamental part of modern data architecture, leveraging open source technologies like Apache Kafka and Flink. With real-time data processing transforming industries, the ecosystem of tools, platforms, and cloud services has evolved significantly. This blog post explores the data streaming landscape of 2025, analyzing key players, trends, and market dynamics shaping this space.
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Data Streaming Trends for 2025 - Leading with Apache Kafka and Flink
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Top Trends for Data Streaming with Apache Kafka and Flink in 2025

Apache Kafka and Apache Flink are leading open-source frameworks for data streaming that serve as the foundation for cloud services, enabling organizations to unlock the potential of real-time data. Over recent years, trends have shifted from batch-based data processing to real-time analytics, scalable cloud-native architectures, and improved data governance powered by these technologies. Looking ahead to 2025, the data streaming ecosystem is set to undergo even greater changes. Here are the top trends shaping the future of data streaming for businesses.
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Data Streaming with Apache Kafka and Flink in the Cloud in Healthcare and Pharma at Cardinal Health
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Data Streaming in Healthcare and Pharma: Use Cases and Insights from Cardinal Health

This blog delves into Cardinal Health’s journey, exploring how its event-driven architecture and data streaming power use cases like supply chain optimization, and medical device and equipment management. By integrating Apache Kafka with platforms like Apigee, Dell Boomi and SAP, Cardinal Health sets a benchmark for IT modernization and innovation in the healthcare and pharma sectors.
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Dynamic Pricing with Data Streaming using Apache Kafka and Flink
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A New Era in Dynamic Pricing: Real-Time Data Streaming with Apache Kafka and Flink

In the age of digitization, the concept of pricing is no longer fixed or manual. Instead, companies increasingly use dynamic pricing — a flexible model that adjusts prices based on real-time market changes to enable real-time responsiveness, giving companies the tools they need to respond instantly to demand, competitor prices, and customer behaviors. This blog post explores the fundamentals of dynamic pricing, its link to data streaming, and real-world examples across different industries such as retail, logistics, gaming and the energy sector.
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Industrial IoT Middleware OT IT Bridge between Edge and Cloud with Apache Kafka and Flink
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Industrial IoT Middleware for Edge and Cloud OT/IT Bridge powered by Apache Kafka and Flink

As industries continue to adopt digital transformation, the convergence of Operational Technology (OT) and Information Technology (IT) has become essential. The OT/IT Bridge is a key concept in industrial automation to connect real-time operational processes with business-oriented IT systems ensuring seamless data flow and coordination. By leveraging Industrial IoT middleware and data streaming technologies like Apache Kafka and Flink, businesses can achieve a unified approach to managing both production processes and higher-level business operations to drive greater efficiency, predictive maintenance, and streamlined decision-making.
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Unified Commerce with Data Streaming using Apache Kafka and Flink at the Edge and in the Cloud
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Unified Commerce in Retail and eCommerce with Apache Kafka and Flink for Real-Time Customer 360

Delivering a seamless and personalized customer experience across all touchpoints is essential for staying competitive in today’s rapidly evolving retail and eCommerce landscape. Unified commerce integrates all sales channels and backend systems into a single platform to ensure real-time consistency in customer interactions, inventory management, and order fulfillment. This blog post explores how Apache Kafka and Flink can be pivotal in achieving real-time Customer 360 in the unified commerce ecosystem and how it differs from traditional omnichannel approaches.
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Apache Iceberg Open Table Format for Data Lake Lakehouse Streaming wtih Kafka Flink Databricks Snowflake AWS GCP Azure
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Apache Iceberg – The Open Table Format for Lakehouse AND Data Streaming

An open table format framework like Apache Iceberg is essential in the enterprise architecture to ensure reliable data management and sharing, seamless schema evolution, efficient handling of large-scale datasets and cost-efficient storage. This blog post explores market trends, adoption of table format frameworks like Iceberg, Hudi, Paimon, Delta Lake and XTable, and the product strategy of leading vendors of data platforms such as Snowflake, Databricks (Apache Spark), Confluent (Apache Kafka / Flink), Amazon Athena and Google BigQuery.
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Energy Trading with Apache Kafka and Flink at Uniper ReAlto Powerledger
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Energy Trading with Apache Kafka and Flink

Energy trading and data streaming are connected because real-time data helps traders make better decisions in the fast-moving energy markets. This data includes things like price changes, supply and demand, smart IoT meters and sensors, and weather, which help traders react quickly and plan effectively. As a result, data streaming with Apache Kafka and Apache Flink makes the market clearer, speeds up information sharing, and improves forecasting and risk management. This blog post explores the use cases and architectures for scalable and reliable real-time energy trading, including real-world deployments from Uniper, re.alto and Powerledger.
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RAG and Kafka Flink to Prevent Hallucinations in GenAI
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Real-Time GenAI with RAG using Apache Kafka and Flink to Prevent Hallucinations

How do you prevent hallucinations from large language models (LLMs) in GenAI applications? LLMs need real-time, contextualized, and trustworthy data to generate the most reliable outputs. This blog post explains how RAG and a data streaming platform with Apache Kafka and Flink make that possible. A lightboard video shows how to build a context-specific real-time RAG architecture. Also, learn how the travel agency Expedia leverages data streaming with Generative AI using conversational chatbots to improve the customer experience and reduce the cost of service agents.
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My Data Streaming Journey with Kafka and Flink - 7 Years at Confluent
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My Data Streaming Journey with Kafka & Flink: 7 Years at Confluent

Time flies… I joined Confluent seven years ago when Apache Kafka was mainly used by a few tech giants and the company had ~100 employees. This blog post explores my data streaming journey, including Kafka becoming a de facto standard for over 100,000 organizations, Confluent doing an IPO on the NASDAQ stock exchange, 5000+ customers adopting a data streaming platform, and emerging new design approaches and technologies like data mesh, GenAI, and Apache Flink. I look at the past, present and future of my personal data streaming journey. Both, from the evolution of technology trends and the journey as a Confluent employee that started in a Silicon Valley startup and is now part of a global software and cloud company.
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