A definitive guide and implementation framework for managing database access, connection pooling, and schema migrations in Go applications.
Install & Download
1. ClawHub CLI
The fastest way to install a skill directly from the registry.
npx clawhub@latest install go-data-persistence
2. Manual Installation
Copy the skill folder to one of these locations
~/.openclaw/skills/ <project>/skills/ Priority: Workspace > Local > Bundled
3. Prompt Installation
Copy this prompt to OpenClaw to install it automatically.
Help me install go-data-persistence using Clawhub. If Clawhub is not installed, install it first (npm i -g clawhub).
Prefer to download?
Get the raw skill files in a ZIP archive.
What is Go Data Persistence Patterns?
This Go data persistence skill provides a comprehensive framework for handling database interactions with precision and performance. It bridges the gap between raw SQL control using pgx or sqlx and the high-level productivity of ORMs like Ent or GORM. By utilizing these Openclaw Skills, developers can implement robust repository patterns that decouple domain logic from database drivers, ensuring maintainable and testable codebases.
The skill emphasizes production readiness through deep dives into connection pool tuning, automated migration workflows with golang-migrate, and sophisticated transaction management at the service layer. It is designed to help teams choose the right abstraction level based on project complexity while maintaining strict security standards against SQL injection and resource leaks.
Go Data Persistence Patterns Use Cases
- Building high-performance microservices requiring fine-grained PostgreSQL control with pgx.
- Rapidly prototyping CRUD applications using the Ent code-generation framework.
- Refactoring legacy Go code to implement the Repository Pattern for better testability.
- Automating database schema evolution across CI/CD pipelines using golang-migrate.
- Implementing atomic multi-step business logic through service-layer transaction helpers.
How Go Data Persistence Patterns Works
- Database Selection: Evaluate project needs to choose between raw SQL (sqlx/pgx) for performance or ORMs (Ent/GORM) for development speed.
- Connection Management: Initialize a shared database connection pool at application startup with optimized settings for MaxOpenConns and MaxIdleConns.
- Repository Definition: Define store interfaces that utilize context-aware queries and map database-specific errors to domain-specific sentinel errors.
- Migration Execution: Apply schema changes using versioned SQL files during the application bootstrap phase to ensure database consistency.
- Transaction Orchestration: Wrap multi-store operations in service-layer transaction helpers to guarantee atomicity and consistent rollback behavior.
Go Data Persistence Patterns Setup
To integrate these patterns into your project, install the necessary drivers and migration tools:
# Install the recommended PostgreSQL driver
go get github.com/jackc/pgx/v5
# Install sqlx for enhanced database/sql features
go get github.com/jmoiron/sqlx
# Install golang-migrate CLI for schema management
brew install golang-migrate
Ensure your application calls the migration runner and initializes the connection pool exactly once at startup.
Go Data Persistence Patterns Data Schema & Taxonomy
The skill organizes data persistence through a structured taxonomy of references and implementation patterns:
| Component | File/Pattern | Responsibility |
|---|---|---|
| Migrations | /migrations/*.up.sql |
Versioned schema evolution files. |
| Models | type User struct |
Go structs with db tags for column mapping. |
| Store | PostgresUserStore |
Implementation of the data access layer. |
| References | connection-pooling.md |
In-depth guides for pool sizing and monitoring. |
| References | transactions.md |
Patterns for isolation levels and atomic units. |
Go Data Persistence Patterns Advanced Features
- Native PostgreSQL protocol support using pgx for advanced features like LISTEN/NOTIFY and COPY commands.
- Service-layer transaction injection allowing multiple repositories to participate in a single atomic unit.
- Automated schema-as-code generation with Ent integration for GraphQL and type-safe query building.
- Idempotent migration strategies with CI/CD integration gates to prevent production schema drift.
- Context propagation across all database layers to ensure query cancellation and timeout compliance.
SKILL.md
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