5 Repos
Utilities for monitoring and reacting to data modifications within database tables.
Distinguishing note: None of the candidates matched; this focuses on database-level event observation.
Explore 5 awesome GitHub repositories matching data & databases · Database Change Listeners. Refine with filters or upvote what's useful.
This project is an AI agent orchestration platform that provides a visual environment for building, testing, and deploying complex automation workflows. It functions as a low-code development interface where users can chain discrete functional blocks into dependency-aware pipelines to integrate artificial intelligence with external data and services. The platform supports the creation of intelligent conversational agents, automated business processes, and multi-service API orchestrations within a unified workspace. The platform distinguishes itself through its event-driven integration engine,
Workflow Platform observes specific database tables for row insertions or updates, optionally filtering by column changes and mapping row data for downstream processing.
This project is a Node.js client for PostgreSQL databases, providing a protocol parser to translate raw binary streams into JavaScript objects. It serves as a driver for executing queries, managing data, and integrating Node.js applications with PostgreSQL backends. The library includes a connection pool manager to reduce network overhead by caching reusable connections and a result streamer that uses cursors to retrieve large datasets incrementally. It also functions as an event listener for subscribing to asynchronous server-side notifications to trigger real-time application events. Broad
Monitors and reacts to data modifications and events triggered within the database.
Realm Java is a NoSQL mobile object database and reactive database engine. It provides a persistent local data store that saves native objects directly to disk, replacing traditional SQL storage and object-relational mapping layers. The system functions as a real-time data synchronizer, coordinating local database changes with a cloud backend across multiple devices. It integrates a reactive engine that uses change listeners and asynchronous event streams to automatically update user interfaces when underlying data changes. The project covers object-oriented data modeling, CRUD operations, a
Provides utilities for monitoring and reacting to data modifications via real-time change listeners.
Hazelcast is a distributed data platform that combines an in-memory data grid with a stream processing engine to support real-time analytics and event-driven applications. It functions as a partitioned, distributed key-value store that replicates data across cluster nodes to provide low-latency access and high availability. The platform also serves as a distributed SQL query engine, allowing users to execute standard SQL statements against both in-memory datasets and external data sources. What distinguishes Hazelcast is its use of a distributed consensus subsystem to maintain strongly consis
Triggers custom actions in response to additions, updates, or removals of entries within distributed data structures.
This project is a Model Context Protocol server and AI agent database connector. It provides a standardized communication layer that allows language models to interact with relational data stores, read database schemas, and manage PostgreSQL database resources. The implementation acts as a serverless host for the Model Context Protocol, deploying on distributed edge functions to connect AI assistants to a project. This enables AI agents to perform database administration, execute SQL queries, and handle schema migrations through an AI-compatible interface. The system covers broader capabilit
Provides utilities for monitoring and reacting to data modifications within database tables.