mongodb/mongoid

Features

• MongoDB Integrations - Integrates Ruby application objects with MongoDB as the primary storage backend.
• Object-to-Document Mappings - Provides the core mapping layer that translates Ruby application objects into MongoDB document formats for persistence.
• Collection Querying - Provides capabilities for fetching specific records from MongoDB collections using filters and query objects.
• Database Connection Configurations - Provides configuration mechanisms for establishing database connections using environment files and runtime variables.
• Database Connectivity - Establishes and configures the network connectivity between the application and remote MongoDB deployments.
• Document CRUD Operations - Provides standard CRUD operations for the full lifecycle management of individual documents within collections.
• Model Lifecycle Hooks - Implements mechanisms to trigger custom logic during database model events like document creation and updates.
• ODM Frameworks - Provides a dedicated ODM framework for mapping Ruby objects to NoSQL documents.
• MongoDB Database Drivers - Provides a client library and driver for executing CRUD operations and aggregation pipelines against MongoDB.
• MongoDB Schema Modeling - Allows the definition of application-level fields and validation rules on top of flexible, schema-less MongoDB documents.
• NoSQL Data Modeling - Facilitates NoSQL data modeling by defining flexible document schemas and hierarchical relationships.
• Object-Document Mappers - Acts as the primary object-document mapper that translates Ruby objects to MongoDB document structures.
• Lifecycle Callbacks - Provides event-driven hooks that execute custom logic during document creation, update, and deletion lifecycles.
• Database Connectivity Drivers - Includes the necessary drivers and interfaces to establish secure network connectivity between Ruby applications and MongoDB servers.
• Database Index Management - Provides tools for creating and managing database indexes to optimize query performance.
• Database Query Optimizations - Implements database query optimizations through the configuration of indexes and aggregation pipelines.
• Full Text Search - Indexes and retrieves documents using keyword matches and patterns via full-text search.
• High-Performance Data Infrastructures - Provides high-performance data retrieval using vector search and full-text indexing for large-scale datasets.
• Read Replica Routing Preferences - Configures read and write preferences to distribute data operations across MongoDB replica sets for better cluster traffic management.
• Aggregation Pipelines - Implements server-side aggregation pipelines to group, filter, and transform MongoDB documents into computed summaries.
• Vector Search - Retrieves documents based on mathematical similarity in high-dimensional vector spaces.
• Data Encryption - Provides mechanisms to secure sensitive information through encryption during processing and storage.
• Encryption Key Management - Generates and manages unique encryption keys stored in secure vaults to protect specific document fields.
• Field Level Encryption - Encrypts individual data fields at the source to ensure only authorized clients can decrypt specific values.
• Secure Storage - Secures sensitive information using client-side field encryption and encrypted network connections.
• SSL/TLS Connection Security - Configures encrypted communication between the application and MongoDB using SSL/TLS.
• Database Mapping - ODM framework for interfacing with MongoDB.
• Language Drivers - ODM framework for Ruby applications.

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