Implementando el Patrón CQRS con Debezium, PostgreSQL, Redis y Kafka
Aprende a implementar el patrón CQRS utilizando Debezium, PostgreSQL, Redis y Kafka para mejorar el rendimiento y la escalabilidad de tus aplicaciones Java con Spring Boot.
CDC Stream Processing with Apache Flink
Explore Apache Flink's capabilities as a data integration hub, focusing on its SQL engine for changelog processing, CDC data handling, and materialized view maintenance. Learn about data source semantics and system integrations.
Change Data Streaming Patterns with Debezium and Apache Flink
Explore change data capture with Debezium and Apache Flink for microservices. Learn outbox pattern, strangler fig pattern, and saga orchestration for reliable data exchange and long-running transactions.
Feeding ML Models with Real-Time Database Data
Explore real-time data ingestion from databases to ML models using Change Data Capture. Learn about Debezium, challenges, and future improvements with a live TensorFlow demo.
Transitioning from Debezium ElasticSearch to Postgres for Streamlined Resilience
Explore backend optimization by transitioning from Debezium ElasticSearch to Postgres. Learn about foreign data wrapper, logical replication, and database consolidation for enhanced resilience and simplified infrastructure.
Realtime Change Data Capture Streaming - End-to-End Data Engineering Project
Implement real-time Change Data Capture streaming using Docker, Postgres, Debezium, Kafka, Apache Spark, and Slack. Create an efficient data pipeline for responsive data engineering projects.
Debezium - Building Streaming Data Pipelines with Change Data Capture
Explore Debezium's features for building streaming data pipelines using popular databases as sources, with a focus on Apache Kafka integration and alternative data sinks.