Debezium is a distributed change data capture platform that streams row-level database modifications as real-time events. By parsing database transaction logs, the system broadcasts structural and data changes to message brokers, enabling reactive processing and data integration across distributed architectures.
Principalele funcționalități ale debezium/debezium sunt: Change Data Capture, Event Streaming Infrastructure, Message Queue Connectors, Change Data Capture Streams, Asynchronous Log Streaming, Real-Time Data Integration Platforms, Data Warehouse Integrations, Database Adapters.
Alternativele open-source pentru debezium/debezium includ: redpanda-data/connect — Connect is a Kafka data integration platform and stream processing engine used to build declarative pipelines that… datalinkdc/dinky — Dinky is a real-time data platform for developing, deploying, and operating streaming applications based on Apache… zendesk/maxwell — Maxwell is a MySQL change data capture tool and binlog streaming application that converts database modifications into… linkedin/databus — Databus is a distributed change data capture system and database transaction log streamer. It extracts data… rethinkdb/rethinkdb — RethinkDB is a distributed, document-oriented database designed to store and manage JSON-formatted data across… alibaba/canal — Canal is a database replication middleware that performs change data capture by simulating a database replica. It…
Connect is a Kafka data integration platform and stream processing engine used to build declarative pipelines that move and transform messages between Kafka topics and external sources. It functions as a Kafka Connect framework and a change data capture tool, streaming real-time database modifications to synchronize data across distributed environments. The project differentiates itself through a dedicated mapping language for mutating and reshaping message payloads and the ability to execute custom processing logic within a sandboxed WebAssembly runtime. It also provides an observability pip
Dinky is a real-time data platform for developing, deploying, and operating streaming applications based on Apache Flink. It functions as a SQL streaming IDE and a real-time data pipeline orchestrator, providing a web-based environment for writing and verifying queries with integrated logic plan visualization and lineage tracking. The platform acts as a distributed cluster manager, allowing the registration, monitoring, and administration of multiple processing clusters from a centralized interface. It also serves as a change data capture integration tool, synchronizing real-time database cha
Maxwell is a MySQL change data capture tool and binlog streaming application that converts database modifications into structured JSON events. It functions as a data pipeline that reads MySQL binary logs to synchronize changes across external indices, search engines, and distributed messaging systems such as Kafka. The project provides capabilities to maintain persistent audit trails by recording a chronological history of all database modifications. It enables real-time data synchronization and event-driven architecture integration by streaming database changes to external platforms to trigg
Databus is a distributed change data capture system and database transaction log streamer. It extracts data modifications from source logs and streams them to downstream consumers to keep secondary data stores and caches consistent. The system functions as a source-agnostic data pipeline and distributed event relay. It uses a network of processes to decouple database sources from consumers, routing change streams across a network to multiple targets regardless of the original source system. The project covers real-time data synchronization and distributed pipeline monitoring. This includes t