#java #apache_flink #cdc #change_data_capture #database #flink_cdc #flink_connectors

https://github.com/ververica/flink-cdc-connectors

#java #airflow #azkaban #dataworks #davinci #etl #flink #governance #griffin #hadoop #hive #hue #kettle #linkis #scriptis #spark #supperset #tableau #visualis #workflow #zeppelin

https://github.com/WeBankFinTech/DataSphereStudio

#scala #etl_pipeline #flink #one_stop_solution #spark #streaming #streaming_warehouse #streamx

https://github.com/streamxhub/streamx

#java #bigdata #data_synchronization #data_transfer #flink

https://github.com/DTStack/chunjun

#java #big_data #data_integration #data_lake #data_pipeline #data_synchronization #flink #high_performance #real_time

https://github.com/bytedance/bitsail

#java #batch #cdc #change_data_capture #data_integration #data_pipeline #distributed #elt #etl #flink #kafka #mysql #paimon #postgresql #real_time #schema_evolution

Flink CDC is a tool that helps you move and transform data in real-time or in batches. It makes data integration simple by using YAML files to describe how data should be moved and transformed. This tool offers features like full database synchronization, table sharding, schema evolution, and data transformation. To use it, you need to set up an Apache Flink cluster, download Flink CDC, create a YAML file to define your data sources and sinks, and then run the job. This benefits you by making it easier to manage and integrate your data efficiently across different databases.

https://github.com/apache/flink-cdc