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The Top 20 Problems with Batch Processing (and How to Fix Them with Data Streaming)

Batch processing introduces delays, complexity, and data quality issues that modern businesses can no longer afford. This article outlines the most common problems with batch workflows—ranging from outdated insights to compliance risks—and illustrates each with real-world examples. It also highlights how real-time data streaming offers a more reliable, scalable, and future-proof alternative.
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The Strangler Fig Design Pattern - Migration and Replacement of Legacy IT Applications with Data Streaming using Apache Kafka
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Replacing Legacy Systems, One Step at a Time with Data Streaming: The Strangler Fig Approach

Modernizing legacy systems doesn’t have to mean a risky big-bang rewrite. This blog explores how the Strangler Fig Pattern, when combined with data streaming, enables gradual, low-risk transformation—unlocking real-time capabilities, reducing complexity, and supporting scalable, cloud-native architectures. Discover how leading organizations are using this approach to migrate at their own pace, stay compliant, and enable new business models. Plus, why Reverse ETL falls short and streaming is the future of IT modernization.
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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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Learnings from the CIO Summit: AI + Data Streaming = Key for Success
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CIO Summit: The State of AI and Why Data Streaming is Key for Success

The CIO Summit in Amsterdam provided a valuable perspective on the state of AI adoption across industries. While enthusiasm for AI remains high, organizations are grappling with the challenge of turning potential into tangible business outcomes. Key discussions centered on distinguishing hype from real value, the importance of high-quality and real-time data, and the role of automation in preparing businesses for AI integration. A recurring theme was that AI is not a standalone solution—it must be supported by a strong data foundation, clear ROI objectives, and a strategic approach. As AI continues to evolve toward more autonomous, agentic systems, data streaming will play a critical role in ensuring AI models remain relevant, context-aware, and actionable in real time.
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From Airline to Travel Ecosystem with Data Streaming using Apache Kafka at Cathay Pacific
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Cathay: From Premium Airline to Integrated Travel Ecosystem with Data Streaming

Cathay Pacific is evolving beyond aviation, rebranding as Cathay to offer a seamless travel and lifestyle ecosystem. From flights to shopping, loyalty rewards, and digital experiences, real-time data streaming with Apache Kafka is at the heart of this transformation. By replacing traditional middleware with a cloud-native Kafka platform, Cathay has unlocked real-time customer insights, seamless integrations, and smarter operations—driving innovation across the travel industry.
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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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