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
This project is a streaming data integration framework that captures real-time database changes and synchronizes them with downstream systems. It operates as a distributed streaming ETL and database synchronizer, reading database logs and snapshots to propagate row-level modifications to target sinks. The system supports declarative data integration, allowing users to define source-to-sink data flows using SQL or YAML configurations. It distinguishes itself by automating schema evolution to maintain synchronization when source structures change and ensuring exactly-once delivery and processin
Realtime is a real-time data distribution and synchronization engine that enables applications to stream database changes and coordinate state between clients. It functions as a synchronization layer that monitors database write-ahead logs to provide change data capture and pushes updates to authorized clients via WebSockets. The project features a real-time presence server for tracking the online status of active users and a broadcast service for sending ephemeral messages without database persistence. It organizes communication through channel-based message routing and uses a structured JSO
RethinkDB is a distributed, document-oriented database designed to store and manage JSON-formatted data across scalable clusters. It utilizes a custom log-structured storage engine with B-Tree indexing to ensure high-performance disk I/O and data persistence. The system maintains high availability through automatic sharding and replication, employing a primary-replica voting consensus mechanism to handle node failures and ensure consistent cluster operations. A defining characteristic of the platform is its reactive changefeed engine, which allows applications to subscribe to live data update
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.
Les fonctionnalités principales de linkedin/databus sont : Change Data Capture, Source-Agnostic Data Pipelines, Distributed Data Pipelines, Change Data Capture Systems, Distributed Event Distribution, Change, Change Data Relays, Real-time Data Synchronization.
Les alternatives open-source à linkedin/databus incluent : zendesk/maxwell — Maxwell is a MySQL change data capture tool and binlog streaming application that converts database modifications into… apache/flink-cdc — This project is a streaming data integration framework that captures real-time database changes and synchronizes them… supabase/realtime — Realtime is a real-time data distribution and synchronization engine that enables applications to stream database… rethinkdb/rethinkdb — RethinkDB is a distributed, document-oriented database designed to store and manage JSON-formatted data across… datalinkdc/dinky — Dinky is a real-time data platform for developing, deploying, and operating streaming applications based on Apache… risingwavelabs/risingwave — RisingWave is a cloud-native streaming database and real-time analytics engine that uses standard SQL to process…