Data Engineering Realtime Data

I have created this project to demo real time reporting performance for various architectures.

Architecture

Components

• Kafka Producer - Nodejs app generating fake data
• Kafka Producer - React app that will send data from a UI to Kafka
• Kafka
• Kafka Consumer - Nodejs
• Kafka Consumer - React
• S3 - staging data between Kafka and Snowflake
• Snowflake - Snowpipe
• Analytics React App

Why kafka

Kafka acts as a broker thus decoupling your consumers and producers! This drastically reduces the number of integrations required.

Performance

• Kafka Producer -> Kafka -> Kafka Consumer -> React App
• Kafka Producer -> Kafka -> S3 -> Snowflake -> React App

Challenges

How to deal with data loss - TODO

Kafka producers will can choose different levels of data loss checks (acknowledgements aka akns 1-3).

1. producer does receives acknowledgement
2. producer checks acknowledgment from kafka parent partition
3. producer check that acknowledgment has occured from kafka parent and replicas partitions.

To implement a batch check vs stream.

Number of Kafka Partitions vs consumer

TODO