Building a Real-Time Data Streaming Pipeline using Apache Kafka, Flink and Postgres

🚀 Building a Real-Time Data Streaming Pipeline with Apache Kafka, Flink, and Postgres 🚀

In this comprehensive tutorial, join us on a journey to create a robust real-time data streaming pipeline from scratch! We'll dive deep into the world of Apache Kafka for efficient event ingestion, Apache Flink for powerful stream processing, and Postgres for storing and analyzing real-time insights.

🔧 What You'll Learn:

Setting up Apache Kafka for event streaming.
Building Apache Flink jobs for real-time data processing.
Integrating Flink with Kafka for seamless data flow.
Designing a schema and connecting Postgres as a data sink.
Optimizing the pipeline for scalability and performance.

🌐 Why Real-Time Data Streaming Matters:
Real-time data processing is a game-changer for industries seeking instant insights from their data. Whether you're in finance, e-commerce, or IoT, understanding how to architect a robust streaming pipeline is a valuable skill in today's data-driven world.

🎓 Who Should Watch:

Data Engineers
Software Developers
Data Scientists
Anyone interested in real-time data processing

⏰ Timestamps:

00:00 - Architecture of the pipeline
04:00 - Setting up folder structure
05:51 - Setting up Postgres
08:43 - Setting up Kafka Producer
30:50 - Setting up Flink Consumer
01:15:29 - End to End testing

🚧 Prerequisites:

Basic understanding of Kafka, Flink, and Postgres concepts.
Java and SQL knowledge is a plus.
🚨 Note:
This tutorial assumes a working knowledge of Apache Kafka, Apache Flink, and Postgres basics. If you're new to these technologies, check out our beginner-friendly guides linked in the description.

👩‍💻 Code and Resources:
https://github.com/Kavit900/data-stre...

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#ApacheKafka #ApacheFlink #Postgres #RealTimeData #DataStreaming #datapipeline

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