Browsing Tag

Cloud

147 posts
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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Data Streaming with Apache Kafka and Flink in the Cloud in Healthcare and Pharma at Cardinal Health
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  • 7 minute read

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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Intelligent Traffic System for Tolling with Dynamic Pricing and Enforcement with Apache Kafka
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  • 9 minute read

IoT and Data Streaming with Kafka for a Tolling Traffic System with Dynamic Pricing

In the rapidly evolving landscape of intelligent traffic systems, innovative software provides real-time processing capabilities, dynamic pricing and new customer experiences, particularly in the domains of tolling, payments and safety inspection. This blog post delves into success stories from Quarterhill and DKV Mobility providing traffic and payment systems for tolls. Data streaming powered by Apache Kafka has been pivotal in the journey towards building intelligent traffic systems in the cloud.
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Serverless Data Streaming on Azure Cloud with Apache Kafka Event Hubs Confluent Cloud for OneLake and Microsoft Fabric
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  • 9 minute read

When to Choose Apache Kafka vs. Azure Event Hubs vs. Confluent Cloud for a Microsoft Fabric Lakehouse

Choosing between Apache Kafka, Azure Event Hubs, and Confluent Cloud for data streaming is critical when building a Microsoft Fabric Lakehouse. Each option caters to different needs, and this blog post will guide you in selecting the right data streaming solution for your use case.
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Microsoft Fabric and OneLake Azure Lakehouse vs Databricks and Snowflake Cloud
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  • 8 minute read

What is Microsoft Fabric for Azure Cloud (Beyond the Buzz) and how it Competes with Snowflake and Databricks

If you ask your favorite large language model, Microsoft Fabric appears to be the ultimate solution for any data challenge you can imagine. That’s also the impression many people get from Microsoft’s sales teams. But is it really the silver bullet it’s made out to be? This article takes a closer look exploring the glossy marketing and sales definition of the platform and then deconstructing it from a more practical perspective. Learn what Microsoft Fabric is truly built for, and how it fits into the wider data landscape, especially in comparison to other major players in the data analytics market like Databricks and Snowflake.
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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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Apache Kafka Deployment Options - Serverless vs Self-Managed vs BYOC Bring Your Own Cloud
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  • 9 minute read

Deployment Options for Apache Kafka: Self-Managed, Fully-Managed / Serverless and BYOC (Bring Your Own Cloud)

BYOC (Bring Your Own Cloud) is an emerging deployment model for organizations looking to maintain greater control over their cloud environments. Unlike traditional SaaS models, BYOC allows businesses to host applications within their own VPCs to provide enhanced data privacy, security, and compliance. This approach leverages existing cloud infrastructure. It offers more flexibility for custom configurations, particularly for companies with stringent security needs. In the data streaming sector around Apache Kafka, BYOC is changing how platforms are deployed. Organizations get more control and adaptability for various use cases. But it is clearly NOT the right choice for everyone!
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