Browsing Tag

Stream Processing

54 posts
Apache Flink - Overkill for Simple Stateless Stream Processing
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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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GenAI Demo with Kafka, Flink, LangChain and OpenAI
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GenAI Demo with Kafka, Flink, LangChain and OpenAI

Generative AI (GenAI) enables automation and innovation across industries. This blog post explores a simple but powerful architecture and demo for the combination of Python, and LangChain with OpenAI LLM, Apache Kafka for event streaming and data integration, and Apache Flink for stream processing. The use case shows how data streaming and GenAI help to correlate data from Salesforce CRM, searching for lead information in public datasets like Google and LinkedIn, and recommending ice-breaker conversations for sales reps.
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Tiered Storage for Apache Kafka - Use Cases Architecture Benefits.png
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  • 11 minute read

Why Tiered Storage for Apache Kafka is a BIG THING…

Apache Kafka added Tiered Storage to separate compute and storage. The capability enables more scalable, reliable and cost-efficient enterprise architectures. This blog post explores the architecture, use cases, benefits, and a case study for storing Petabytes of data in the Kafka commit log. The end discusses why Tiered Storage does NOT replace other databases and how Apache Iceberg might change future Kafka architectures even more.
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Top 5 Trends for Data Streaming with Kafka and Flink in 2024

Do you wonder about my predicted TOP 5 data streaming trends with Apache Kafka and Flink in 2024 to set data in motion? Discover new technology trends and best practices for event-driven architectures, including data sharing, data contracts, serverless stream processing, multi-cloud architectures, and GenAI.
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Real-Time Advertising Platform with Apache Kafka and Flink
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How to Build a Real-Time Advertising Platform with Apache Kafka and Flink

An advertising platform requires real-time capabilities to provide dynamic targeting, ad personalization, ad fraud detection, budget allocation, and event-driven marketing. This blog post explores how data streaming with Apache Kafka and Apache Flink enables context-specific advertising at any scale. Real-world success stories from Pinterest, Uber, Unity, buzzwil, and TV-Insight show different solutions and architectures for serving ads in marketing campaigns, embedded into mobile apps, and as SaaS software products.
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Python Kafka Quix Streams and Flink for Open Source Stream Processing
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  • 12 minute read

Quix Streams – Stream Processing with Kafka and Python

Over 100,000 organizations use Apache Kafka for data streaming. However, there is a problem: The broad ecosystem lacks a mature client framework and managed cloud service for Python data engineers. Quix Streams is a new technology on the market trying to close this gap. This blog post discusses this Python library, its place in the Kafka ecosystem, and when to use it instead of Apache Flink or other Python- or SQL-based substitutes.
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Apache Kafka and Apache Flink for Open Source and Cloud-native Data Streaming
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  • 12 minute read

Apache Kafka (including Kafka Streams) + Apache Flink = Match Made in Heaven

Apache Kafka and Apache Flink are increasingly joining forces to build innovative real-time stream processing applications. This blog post explores the benefits of combining both open-source frameworks, shows unique differentiators of Flink versus Kafka, and discusses when to use a Kafka-native streaming engine like Kafka Streams instead of Flink.
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Fraud Detection and Prevention with Apache Kafka KSQL Apache Flink
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Fraud Detection with Apache Kafka, KSQL and Apache Flink

Fraud detection becomes increasingly challenging in a digital world across all industries. Real-time data processing with Apache Kafka became the de facto standard to correlate and prevent fraud continuously before it happens. This blog post explores case studies for fraud prevention from companies such as Paypal, Capital One, ING Bank, Grab, and Kakao Games that leverage stream processing technologies like Kafka Streams, KSQL, and Apache Flink.
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Apache Kafka for Government and Citizen Services in the Public Sector
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Apache Kafka in the Public Sector – Part 3: Government and Citizen Services

The public sector includes many different areas. Some groups leverage cutting-edge technology, like military leverage. Others like the public administration are years or even decades behind. This blog series explores both edges to show how data in motion powered by Apache Kafka adds value for innovative new applications and modernizing legacy IT infrastructures. This is part 3: Use cases and architectures for Government and Citizen Services.
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