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jeff.klukas.net | ||
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www.morling.dev
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| | | | | Postgres logical replication, while powerful for capturing real-time data changes, presents challenges with TOAST columns, whose values can be absent from data change events in specific situations. This post discusses how Debezium addresses this through its built-in reselect post processor, then explores more robust solutions leveraging Apache Flink's capabilities for stateful stream processing, including Flink SQL and the brand-new process table functions (PTFs) in Flink 2.1. | |
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newsroom.aboutrobinhood.com
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| | | | | Robinhood's mission is to democratize finance for all. Continuous data analysis and data driven decision making at different levels within | |
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debezium.io
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| | | | | Debezium is an open source distributed platform for change data capture. Start it up, point it at your databases, and your apps can start responding to all of the inserts, updates, and deletes that other apps commit to your databases. Debezium is durable and fast, so your apps can respond quickly and never miss an event, even when things go wrong. | |
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archive.qconsf.com
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| | | Debezium (noun | de·be·zi·um | /d?:?b?:zi??m/) - Secret Sauce for Change Data Capture Apache Kafka is a highly popular option for asynchronous event propagation between microservices. Things get challenging though when adding a services database to the picture: How can you avoid inconsistencies between Kafka and the database? Enter change data capture (CDC) and Debezium. By | ||
