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Database Domain Specialist

数据库领域专家

Quick Reference

快速参考

Enterprise Database Expertise - Comprehensive database patterns and implementations covering PostgreSQL, MongoDB, Redis, Oracle, and advanced data management for scalable modern applications.
Core Capabilities:
  • PostgreSQL: Advanced relational patterns, optimization, and scaling
  • MongoDB: Document modeling, aggregation, and NoSQL performance tuning
  • Redis: In-memory caching, real-time analytics, and distributed systems
  • Oracle: Enterprise patterns, PL/SQL, partitioning, and hierarchical queries
  • Multi-Database: Hybrid architectures and data integration patterns
  • Performance: Query optimization, indexing strategies, and scaling
  • Operations: Connection management, migrations, and monitoring
When to Use:
  • Designing database schemas and data models
  • Implementing caching strategies and performance optimization
  • Building scalable data architectures
  • Working with multi-database systems
  • Optimizing database queries and performance
企业级数据库专业能力 - 涵盖PostgreSQL、MongoDB、Redis、Oracle的全面数据库模式与实现，以及面向可扩展现代应用的高级数据管理。
核心能力：
  • PostgreSQL：高级关系型模式、优化与扩展
  • MongoDB：文档建模、聚合与NoSQL性能调优
  • Redis：内存缓存、实时分析与分布式系统
  • Oracle：企业级模式、PL/SQL、分区与分层查询
  • 多数据库：混合架构与数据集成模式
  • 性能：查询优化、索引策略与扩展
  • 运维：连接管理、迁移与监控
适用场景：
  • 设计数据库架构与数据模型
  • 实现缓存策略与性能优化
  • 构建可扩展数据架构
  • 处理多数据库系统相关工作
  • 优化数据库查询与性能

Implementation Guide

实现指南

Quick Start Workflow

快速入门流程

Database Stack Initialization:
Create a DatabaseManager instance and configure multiple database connections. Set up PostgreSQL with connection string, pool size of 20, and query logging enabled. Configure MongoDB with connection string, database name, and sharding enabled. Configure Redis with connection string, max connections of 50, and clustering enabled. Use the unified interface to query user data with profile and analytics across all database types.
Single Database Operations:
Run PostgreSQL schema migrations using the migration command with the database type and migration file path. Execute MongoDB aggregation pipelines by specifying the collection name and pipeline JSON file. Warm Redis cache by specifying key patterns and TTL values.
数据库栈初始化：
创建DatabaseManager实例并配置多个数据库连接。设置PostgreSQL的连接字符串、连接池大小为20，并启用查询日志。配置MongoDB的连接字符串、数据库名称，并启用分片。配置Redis的连接字符串、最大连接数为50，并启用集群。使用统一接口跨所有数据库类型查询包含用户资料与分析数据的用户信息。
单数据库操作：
使用迁移命令指定数据库类型与迁移文件路径，运行PostgreSQL架构迁移。通过指定集合名称与管道JSON文件执行MongoDB聚合管道。通过指定键模式与TTL值预热Redis缓存。

Core Components

核心组件

PostgreSQL Module:
  • Advanced schema design and constraints
  • Complex query optimization and indexing
  • Window functions and CTEs
  • Partitioning and materialized views
  • Connection pooling and performance tuning
MongoDB Module:
  • Document modeling and schema design
  • Aggregation pipelines for analytics
  • Indexing strategies and performance
  • Sharding and scaling patterns
  • Data consistency and validation
Redis Module:
  • Multi-layer caching strategies
  • Real-time analytics and counting
  • Distributed locking and coordination
  • Pub/sub messaging and streams
  • Advanced data structures including HyperLogLog and Geo
Oracle Module:
  • Hierarchical and recursive query patterns (CONNECT BY)
  • PL/SQL procedures, packages, and batch operations
  • Partitioning strategies (range, list, hash, composite)
  • Enterprise features and statement caching
  • LOB handling and large data processing
PostgreSQL模块：
  • 高级架构设计与约束
  • 复杂查询优化与索引
  • 窗口函数与CTE
  • 分区与物化视图
  • 连接池与性能调优
MongoDB模块：
  • 文档建模与架构设计
  • 用于分析的聚合管道
  • 索引策略与性能
  • 分片与扩展模式
  • 数据一致性与验证
Redis模块：
  • 多层缓存策略
  • 实时分析与计数
  • 分布式锁与协调
  • 发布/订阅消息与流
  • 高级数据结构（包括HyperLogLog与Geo）
Oracle模块：
  • 分层与递归查询模式（CONNECT BY）
  • PL/SQL存储过程、包与批处理操作
  • 分区策略（范围、列表、哈希、复合）
  • 企业级特性与语句缓存
  • LOB处理与大数据处理

Advanced Patterns

高级模式

Multi-Database Architecture

多数据库架构

Polyglot Persistence Pattern:
Create a DataRouter class that initializes connections to PostgreSQL, MongoDB, Redis, and Oracle. Implement get_user_profile method that retrieves structured user data from PostgreSQL or Oracle, flexible profile data from MongoDB, and real-time status from Redis, then merges all data sources. Implement update_user_data method that routes structured data updates to PostgreSQL/Oracle, profile data updates to MongoDB, and real-time data updates to Redis, followed by cache invalidation.
Data Synchronization:
Create a DataSyncManager class that synchronizes user data across databases. Implement sync_user_data method that retrieves user from PostgreSQL, creates a search document for MongoDB, upserts to the MongoDB search collection, creates cache data, and updates Redis cache with TTL.
多语言持久化模式：
创建DataRouter类，初始化与PostgreSQL、MongoDB、Redis和Oracle的连接。实现get_user_profile方法，从PostgreSQL或Oracle获取结构化用户数据，从MongoDB获取灵活的用户资料数据，从Redis获取实时状态数据，然后合并所有数据源。实现update_user_data方法，将结构化数据更新路由至PostgreSQL/Oracle，将资料数据更新路由至MongoDB，将实时数据更新路由至Redis，随后执行缓存失效操作。
数据同步：
创建DataSyncManager类，跨数据库同步用户数据。实现sync_user_data方法，从PostgreSQL获取用户数据，为MongoDB创建搜索文档，插入或更新至MongoDB搜索集合，创建缓存数据，并使用TTL更新Redis缓存。

Performance Optimization

性能优化

Query Performance Analysis:
For PostgreSQL, execute EXPLAIN ANALYZE BUFFERS on queries and use a QueryAnalyzer to generate optimization suggestions. For MongoDB, create an AggregationOptimizer to analyze and optimize aggregation pipelines. For Redis, retrieve info metrics and use a PerformanceAnalyzer to generate recommendations.
Scaling Strategies:
Configure PostgreSQL read replicas by providing replica connection URLs. Set up MongoDB sharding with shard key and number of shards. Configure Redis clustering by providing node URLs for the cluster.
查询性能分析：
对于PostgreSQL，在查询上执行EXPLAIN ANALYZE BUFFERS，并使用QueryAnalyzer生成优化建议。对于MongoDB，创建AggregationOptimizer来分析与优化聚合管道。对于Redis，获取info指标并使用PerformanceAnalyzer生成建议。
扩展策略：
通过提供副本连接URL配置PostgreSQL只读副本。设置带有分片键与分片数量的MongoDB分片。通过提供集群节点URL配置Redis集群。

Works Well With

协同工具

Complementary Skills:
  • moai-domain-backend - API integration and business logic
  • moai-foundation-core - Database migration and schema management
  • moai-workflow-project - Database project setup and configuration
  • moai-platform-supabase - Supabase database integration patterns
  • moai-platform-neon - Neon database integration patterns
  • moai-platform-firestore - Firestore database integration patterns
Technology Integration:
  • ORMs and ODMs including SQLAlchemy, Mongoose, and TypeORM
  • Connection pooling with PgBouncer and connection pools
  • Migration tools including Alembic, Flyway, and Data Pump
  • Monitoring with pg_stat_statements, MongoDB Atlas, and Oracle AWR
  • python-oracledb for Oracle connectivity and PL/SQL execution
  • Cache invalidation and synchronization
互补技能：
  • moai-domain-backend - API集成与业务逻辑
  • moai-foundation-core - 数据库迁移与架构管理
  • moai-workflow-project - 数据库项目搭建与配置
  • moai-platform-supabase - Supabase数据库集成模式
  • moai-platform-neon - Neon数据库集成模式
  • moai-platform-firestore - Firestore数据库集成模式
技术集成：
  • ORM与ODM，包括SQLAlchemy、Mongoose和TypeORM
  • 使用PgBouncer与连接池进行连接管理
  • 迁移工具，包括Alembic、Flyway和Data Pump
  • 使用pg_stat_statements、MongoDB Atlas和Oracle AWR进行监控
  • python-oracledb用于Oracle连接与PL/SQL执行
  • 缓存失效与同步

Technology Stack

技术栈

Relational Database:
  • PostgreSQL 14+ as primary database
  • MySQL 8.0+ as alternative
  • Connection pooling with PgBouncer and SQLAlchemy
NoSQL Database:
  • MongoDB 6.0+ as primary document store
  • Document modeling and validation
  • Aggregation framework
  • Sharding and replication
In-Memory Database:
  • Redis 7.0+ as primary cache
  • Redis Stack for advanced features
  • Clustering and high availability
  • Advanced data structures
Enterprise Database:
  • Oracle 19c+ / 21c+ for enterprise workloads
  • python-oracledb (successor to cx_Oracle)
  • PL/SQL procedures and packages
  • Partitioning and advanced analytics
Supporting Tools:
  • Migration tools including Alembic and Flyway
  • Monitoring with Prometheus and Grafana
  • ORMs and ODMs including SQLAlchemy and Mongoose
  • Connection management utilities
Performance Features:
  • Query optimization and analysis
  • Index management and strategies
  • Caching layers and invalidation
  • Load balancing and failover
关系型数据库：
  • PostgreSQL 14+ 作为主数据库
  • MySQL 8.0+ 作为备选
  • 使用PgBouncer与SQLAlchemy进行连接池管理
NoSQL数据库：
  • MongoDB 6.0+ 作为主文档存储
  • 文档建模与验证
  • 聚合框架
  • 分片与复制
内存数据库：
  • Redis 7.0+ 作为主缓存
  • Redis Stack 用于高级特性
  • 集群与高可用性
  • 高级数据结构
企业级数据库：
  • Oracle 19c+ / 21c+ 用于企业级工作负载
  • python-oracledb（cx_Oracle的继任者）
  • PL/SQL存储过程与包
  • 分区与高级分析
支持工具：
  • 迁移工具，包括Alembic和Flyway
  • 使用Prometheus与Grafana进行监控
  • ORM与ODM，包括SQLAlchemy和Mongoose
  • 连接管理工具
性能特性：
  • 查询优化与分析
  • 索引管理与策略
  • 缓存层与失效
  • 负载均衡与故障转移

Resources

资源

For working code examples, see examples.md.
For detailed implementation patterns and database-specific optimizations, see the modules directory.
Status: Production Ready Last Updated: 2026-01-11 Maintained by: MoAI-ADK Database Team
如需工作代码示例，请查看examples.md。
如需详细实现模式与数据库特定优化，请查看modules目录。
状态：生产就绪 最后更新：2026-01-11 维护团队：MoAI-ADK数据库团队