Browsing Tag

open source

170 posts
Retail Media with Data Streaming using Apache Kafka and Flink
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Retail Media with Data Streaming: The Future of Personalized Advertising in Commerce

Retail media is reshaping digital advertising by using first-party data to deliver personalized, timely ads across online and in-store channels. As retailers build retail media networks, they unlock new revenue opportunities while improving ad effectiveness and customer engagement. The key to success lies in real-time data streaming, which enables instant targeting, automated bidding, and precise attribution. Technologies like Apache Kafka and Apache Flink make this possible, helping retailers like Albertsons enhance ad performance and maximize returns. This post explores how real-time streaming is driving the evolution of retail media
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Replacing OT Middleware with Data Streaming using Kafka and Flink for Cloud-Native Industrial IoT with MQTT and OPC-UA
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Modernizing OT Middleware: The Shift to Open Industrial IoT Architectures with Data Streaming

Legacy OT middleware is struggling to keep up with real-time, scalable, and cloud-native demands. As industries shift toward event-driven architectures, companies are replacing vendor-locked, polling-based systems with Apache Kafka, MQTT, and OPC-UA for seamless OT-IT integration. Kafka serves as the central event backbone, MQTT enables lightweight device communication, and OPC-UA ensures secure industrial data exchange. This approach enhances real-time processing, predictive analytics, and AI-driven automation, reducing costs and unlocking scalable, future-proof architectures.
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How Data Streaming and AI Help Telcos - Top 5 Trends from MWC 2025
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How Data Streaming and AI Help Telcos to Innovate: Top 5 Trends from MWC 2025

As the telecom and tech industries rapidly evolve, real-time data streaming is emerging as the backbone of digital transformation. For MWC 2025, McKinsey outlined five key trends defining the future: IT excellence, sustainability, 6G, generative AI, and AI-driven software development. This blog explores how data streaming powers each of these trends, enabling real-time observability, AI-driven automation, energy efficiency, ultra-low latency networks, and faster software innovation. From Dish Wireless’ cloud-native 5G network to Verizon’s edge AI deployments, leading companies are leveraging event-driven architectures to gain a competitive advantage. Whether you’re tackling network automation, sustainability challenges, or AI monetization, data streaming is the strategic enabler for 2025 and beyond. Read on to explore the latest use cases, industry insights, and how to future-proof your telecom strategy.
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Data Streaming with Apache Kafka and Flink as the Backbone for a B2B Data Marketplace
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Data Streaming as the Technical Foundation for a B2B Marketplace

A B2B data marketplace empowers businesses to exchange, monetize, and leverage real-time data through self-service platforms featuring subscription management, usage-based billing, and secure data sharing. Built on data streaming technologies like Apache Kafka and Flink, these marketplaces deliver scalable, event-driven architectures for seamless integration, real-time processing, and compliance. By exploring successful implementations like AppDirect, this post highlights how organizations can unlock new revenue streams and foster innovation with modern data marketplace solutions.
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Data Streaming with Apache Kafka and Flink in the Media Industry at Netflix Disney Plus Hotstar and Reliance JioCinema
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Data Streaming with Apache Kafka and Flink in the Media Industry: Disney+ Hotstar and JioCinema

The $8.5 billion merger of Disney+ Hotstar and Reliance’s JioCinema marks a transformative moment for India’s media industry, combining two of the most influential streaming platforms into a data streaming powerhouse. This blog explores how technologies like Apache Kafka and Flink power these platforms, enabling massive-scale content distribution, real-time analytics, and user engagement. With tools like MirrorMaker and Cluster Linking, the merger presents opportunities for seamless Kafka migrations, hybrid multi-cloud flexibility, and new innovations like multi-angle viewing and advanced personalization. The transparency of both platforms about their Kafka-based architectures highlights their technical leadership and the lessons they offer the data streaming community. The integration of their infrastructures sets the stage for redefining media streaming in India, offering exciting insights and benchmarks for organizations leveraging data streaming at scale.
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Online Model Training and Model Drift in Machine Learning with Apache Kafka and Flink
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Online Model Training and Model Drift in Machine Learning with Apache Kafka and Flink

The rise of real-time AI and machine learning is reshaping the competitive landscape. Traditional batch-trained models struggle with model drift, leading to inaccurate predictions and missed opportunities. Platforms like Apache Kafka and Apache Flink enable continuous model training and real-time inference, ensuring up-to-date, high-accuracy predictions. This blog explores TikTok’s groundbreaking AI architecture, its use of data streaming for real-time recommendations, and how businesses can leverage Kafka and Flink to modernize their ML pipelines. I also examine how data streaming complements platforms like Databricks, Snowflake, and Microsoft Fabric to create scalable, adaptive AI systems.
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Tesla Energy Platform - The Power of Data Streaming with Apache Kafka
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Tesla Energy Platform – The Power of Data Streaming with Apache Kafka

Tesla’s Virtual Power Plant (VPP) turns thousands of home batteries, solar panels, and energy storage systems into a coordinated, intelligent energy network. By leveraging Apache Kafka for event streaming and WebSockets for real-time IoT connectivity, Tesla enables instant energy redistribution, dynamic grid balancing, and automated market participation. This event-driven architecture ensures millisecond-level decision-making, allowing homeowners to optimize energy usage and utilities to stabilize power grids. Tesla’s approach highlights how real-time data streaming and intelligent automation are reshaping the future of decentralized, resilient, and sustainable energy systems.
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Top 10 Real Time Innovations in FinServ with Data Streaming using Apache Kafka and Flink
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  • 10 minute read

How Data Streaming with Apache Kafka and Flink Drives the Top 10 Innovations in FinServ

The financial industry is rapidly shifting toward real-time, intelligent, and seamlessly integrated services. From IoT payments and AI-driven banking to embedded finance and RegTech, financial institutions must process vast amounts of data instantly and securely. Data Streaming with Apache Kafka and Apache Flink provides the backbone for real-time payments, fraud detection, personalized financial insights, and compliance automation. This blog post explores the top 10 emerging financial technologies and how data streaming enables them, helping banks, fintechs, and central institutions stay ahead in the future of finance.
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Free Ebook: Data Streaming Use Cases and Industry Success Stories Featuring Apache Kafka and Flink

Real-time data is no longer optional—it’s essential. Businesses across industries use data streaming to power insights, optimize operations, and drive innovation. After 7+ years at Confluent, I’ve seen firsthand how Apache Kafka and Flink transform organizations. That’s why I wrote The Ultimate Data Streaming Guide: Concepts, Use Cases, Industry Stories—a free eBook packed with insights, real-world examples, and best practices. Download your free copy now and start your data streaming journey!
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Data Streaming with Apache Kafka and Flink vs Visual Coding with Low-Code No-Code
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Why Generative AI and Data Streaming Are Replacing Visual Coding with Low-Code / No-Code Platforms

Low-code/no-code tools have revolutionized software development and data engineering by providing visual interfaces that empower non-technical users. However, their limitations in scalability, consistency, and integration pose significant challenges in modern, real-time architectures. Generative AI is emerging as a game-changer, offering unprecedented flexibility and customization, addressing many of the pitfalls of traditional low-code/no-code platforms. Simultaneously, the data ecosystem is evolving with Apache Kafka and Flink, enabling real-time, event-driven architectures that resolve inefficiencies of fragmented, batch-driven systems. This blog explores the evolution of low-code/no-code tools, their challenges, when (not) to use visual coding, and how generative AI and data streaming are reshaping the landscape.
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