3 个仓库
Applying defined database schemas from model files to target databases.
Distinct from Database Deployment Tools: Specifically refers to deploying a schema model (YAML/SQL) rather than provisioning the server instance.
Explore 3 awesome GitHub repositories matching data & databases · Schema Model Deployment. Refine with filters or upvote what's useful.
Instantiator is a PHP library designed to create class instances without invoking their constructors. It uses the PHP Reflection API to allocate objects in memory and initialize them in a predefined state, bypassing standard constructor logic. The project functions as a data hydration tool and a testing helper. It enables the population of PHP objects from external data sources by mapping values directly to properties, regardless of whether those properties are public, protected, or private. This capability allows for the generation of objects in specific internal states for unit tests withou
Automates the application of defined database schemas to target environments.
DbGate is a universal database management tool and SQL client that provides a unified interface for querying and administering multiple SQL and NoSQL databases. It functions as a multi-database administration GUI and SQL IDE, allowing users to write and execute scripts and manage database schemas. The project distinguishes itself by acting as an API client and explorer for REST, GraphQL, and OData services, enabling users to fetch and export data from these endpoints. It also serves as a data integration tool, facilitating the movement of records between diverse databases and file formats suc
Deploys database schemas defined in YAML and SQL files to target database servers.
firebase-tools is a command-line interface and cloud resource orchestrator used to manage, test, and deploy Firebase projects. It serves as the primary tool for administering cloud resources, configuring project settings, and handling authentication from a terminal. The project includes a local cloud service emulator that allows developers to run local versions of cloud services to verify behavior before production deployment. It also implements a server based on the Model Context Protocol to expose project data and service controls to AI assistants. The tool covers a wide range of operation
Pushes validated schemas, operations, and data from a local environment to a production cloud database.