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Apache Flink

35 posts
SaaS vs PaaS Cloud Service for Data Streaming with Apache Kafka and Flink
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  • 6 minute read

Fully Managed (SaaS) vs. Partially Managed (PaaS) Cloud Services for Data Streaming with Kafka and Flink

The cloud revolution has reshaped how businesses deploy and manage data streaming with solutions like Apache Kafka and Flink. Distinctions between SaaS and PaaS models significantly impact scalability, cost, and operational complexity. Bring Your Own Cloud (BYOC) expands the options, giving businesses greater flexibility in cloud deployment. Misconceptions around terms like “serverless” highlight the need for deeper analysis to avoid marketing pitfalls. This blog explores deployment options, enabling informed decisions tailored to your data streaming needs.
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Apache Flink - Overkill for Simple Stateless Stream Processing
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  • 8 minute read

Apache Flink: Overkill for Simple, Stateless Stream Processing and ETL?

Discover when Apache Flink is the right tool for your stream processing needs. Explore its role in stateful and stateless processing, the advantages of serverless Flink SaaS solutions like Confluent Cloud, and how it supports advanced analytics and real-time data integration together with Apache Kafka. Dive into the trade-offs, deployment options, and strategies for leveraging Flink effectively across cloud, on-premise, and edge environments, and when to use Kafka Streams or Single Message Transforms (SMT) within Kafka Connect for ETL instead of Flink.
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Stateless and Stateful Stream Processing with Kafka Streams and Apache Flink
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  • 8 minute read

Stateless vs. Stateful Stream Processing with Kafka Streams and Apache Flink

The rise of stream processing has changed how we handle and act on data. While traditional databases, data lakes, and warehouses are effective for many batch-based use cases, they fall short in scenarios demanding low latency, scalability, and real-time decision-making. This post explores the key concepts of stateless and stateful stream processing, using Kafka Streams and Apache Flink as examples.
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Data Streaming with Apache Kafka and Flink in Healthcare and Manufacturing at Siemens Healthineers
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  • 6 minute read

How Siemens Healthineers Leverages Data Streaming with Apache Kafka and Flink in Manufacturing and Healthcare

Siemens Healthineers, a global leader in medical technology, delivers solutions that improve patient outcomes and empower healthcare professionals. A significant aspect of their technological prowess lies in their use of data streaming to unlock real-time insights and optimize processes. This blog post delves into how Siemens Healthineers uses data streaming with Apache Kafka and Flink, their cloud-focused technology stack, and the use cases that drive tangible business value, such as real-time logistics, robotics, SAP ERP integration, AI/ML, and more.
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The Data Streaming Landcape 2025 with Kafka Flink Confluent Amazon MSK Cloudera Event Hubs and Other Platforms
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  • 21 minute read

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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  • 18 minute read

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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Dynamic Pricing with Data Streaming using Apache Kafka and Flink
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  • 9 minute read

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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Real-Time AI ML Model Inference Predictive AI and Generative AI with Data Streaming using Apache Kafka and Flink
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  • 14 minute read

Real-Time Model Inference with Apache Kafka and Flink for Predictive AI and GenAI

Artificial Intelligence (AI) and Machine Learning (ML) are transforming business operations by enabling systems to learn from data and make intelligent decisions for predictive and generative AI use cases. Two essential components of AI/ML are model training and inference. This blog post explores how data streaming with Apache Kafka and Flink enhances the performance and reliability of model predictions. Whether for real-time fraud detection, smart customer service applications or predictive maintenance, understanding the value of data streaming for model inference is crucial for leveraging AI/ML effectively.
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Industrial IoT Middleware OT IT Bridge between Edge and Cloud with Apache Kafka and Flink
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  • 11 minute read

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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  • 8 minute read

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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