🦀 event stream processing for developers to collect and transform data in motion to power responsive data intensive applications.
Python Streaming DataFrames for Kafka
This demo shows how to capture data changes from relational databases (Oracle and PostgreSQL) and stream them to Confluent Cloud, use ksqlDB for real-time stream processing, send enriched data to cloud data warehouses (Snowflake and Amazon Redshift).
This demo shows how to stream data to cloud databases with Confluent. It includes fully-managed connectors (Oracle CDC, RabbitMQ, MongoDB Atlas), ksqlDB/Flink SQL as stream processing engine.
Streaming data pipelines for real-time data warehousing. Includes fully managed connectors (PostgreSQL CDC, Snowflake).
Real-time crypto trading data pipeline using Apache Spark, Kafka, and Airflow. Containerized microservices architecture for streaming analytics.
A basic streaming data store
Built a production-grade machine learning system for real-time ride fare and ETA prediction, inspired by Uber and Lyft infrastructure. https://rajesh1804.medium.com/%EF%B8%8F-ridecastai-2-0-c68dfac54dbd
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