Browsing Tag

Apache

50 posts
My Data Streaming Journey with Kafka and Flink - 7 Years at Confluent
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  • 11 minute read

My Data Streaming Journey with Kafka & Flink: 7 Years at Confluent

Time flies… I joined Confluent seven years ago when Apache Kafka was mainly used by a few tech giants and the company had ~100 employees. This blog post explores my data streaming journey, including Kafka becoming a de facto standard for over 100,000 organizations, Confluent doing an IPO on the NASDAQ stock exchange, 5000+ customers adopting a data streaming platform, and emerging new design approaches and technologies like data mesh, GenAI, and Apache Flink. I look at the past, present and future of my personal data streaming journey. Both, from the evolution of technology trends and the journey as a Confluent employee that started in a Silicon Valley startup and is now part of a global software and cloud company.
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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 vs Redpanda Comparison
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  • 18 minute read

When to choose Redpanda instead of Apache Kafka?

Data streaming emerged as a new software category. It complements traditional middleware, data warehouse, and data lakes. Apache Kafka became the de facto standard. New players enter the market because of Kafka’s success. One of those is Redpanda, a lightweight Kafka-compatible C++ implementation. This blog post explores the differences between Apache Kafka and Redpanda, when to choose which framework, and how the Kafka ecosystem, licensing, and community adoption impact a proper evaluation.
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Apache Camel vs Apache Kafka Comparison
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  • 13 minute read

When to use Apache Camel vs. Apache Kafka?

Should I use Apache Camel or Apache Kafka for my next integration project? The question is very valid and comes up regularly. This blog post explores both open-source frameworks and explains the difference between application integration and event streaming. The comparison discusses when to use Kafka or Camel, when to combine them, when not to use them at all. A decision tree shows how you can quickly qualify out one for the other.
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  • 5 minute read

Panel Discussion about Kafka, Edge, Networking and 5G in Oil and Gas and Mining Industry

The oil & gas and mining industries require edge computing for low latency and zero trust use cases. Most IT architectures are hybrid with big data analytics in the cloud and safety-critical data processing in disconnected and often air-gapped environments. This blog post shares a panel discussion that explores the challenges, use cases, and hardware/software/network technologies to reduce cost and innovate. A key focus is on the open-source framework Apache Kafka, the de facto standard for processing data in motion at the edge and in the cloud.
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De Facto Standard API - Amazon S3 for Object Storage and Apache Kafka for Event Streaming
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  • 13 minute read

Kafka API is the De Facto Standard API for Event Streaming like Amazon S3 for Object Storage

Real-time beats slow data in most use cases across industries. The rise of event-driven architectures and data in motion powered by Apache Kafka enables enterprises to build real-time infrastructure and applications. This blog post explores why the Kafka API became the de facto standard API for event streaming like Amazon S3 for object storage, and the tradeoffs of these standards and corresponding frameworks, products, and cloud services.
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