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Services that capture and broadcast state changes from primary databases to secondary storage or analytical targets.
Distinguishing note: Focuses on the middleware layer that manages the replication flow, rather than the database engine itself.
Explore 3 awesome GitHub repositories matching data & databases · Database Replication Middleware. Refine with filters or upvote what's useful.
Canal is a database replication middleware that performs change data capture by simulating a database replica. It monitors transaction logs to stream incremental data modifications to downstream systems in real time, acting as an event streaming infrastructure that transforms low-level binary logs into structured, consumable message streams. The project distinguishes itself through a high-throughput architecture that utilizes concurrent multi-threaded parsing and stateful log position tracking to ensure reliable data delivery. It employs a pluggable sink architecture that decouples data extra
Acts as a replication client to capture and broadcast state changes from primary databases to secondary targets.
Electric is a Postgres data synchronization engine and replication proxy designed to enable local-first software. It replicates data from Postgres databases to client-side stores in real time using logical replication, allowing applications to maintain a local embedded database for offline access and low-latency updates. The system distinguishes itself by using shapes to filter and authorize specific subsets of database rows and columns before streaming them to clients or edge workers. It further supports multi-user collaboration by integrating a conflict-free replicated data type framework t
Configures how database tables publish for replication using automated or manual privilege control modes.
This project is a change data capture system and synchronization layer that moves data from MySQL databases into Elasticsearch indices. It functions as a relational-to-document mapper, transforming database tables into searchable documents to enable real-time data integration and full-text search. The synchronizer differentiates itself by supporting relational data denormalization, which transforms one-to-many database joins into parent-child document structures. It also allows for partitioned table aggregation, using regular expression patterns to group multiple database tables into a single
Acts as a synchronization layer that captures database state changes and broadcasts them to an external search index.