igor vs GORM for PostgreSQL projects?

Igor offers similar syntax but is PostgreSQL-specific with optimizations like prepared statements and LISTEN/NOTIFY. However, it lacks GORM's ORM features such as associations and callbacks, making it lighter but less feature-complete for complex relationships.

How to use transactions with igor?

Use the Begin, Commit, and Rollback methods on the Database type. Igor supports full transaction management, but you must handle errors manually, and methods return errors instead of chaining like GORM.

Can igor handle database migrations?

No, igor does not support DDL operations natively. You must use the Raw or Exec methods to run SQL commands for schema changes, requiring external tools or manual migration scripts.

How to work with JSONB data in igor?

Define model fields with the igor.JSON type, which behaves like a map[string]interface{}. Igor handles serialization automatically, and you can use it with PostgreSQL's JSON/JSONB types as shown in the examples.

What are the performance trade-offs of igor?

Igor prioritizes performance with prepared statements and PostgreSQL optimizations, but the lack of associations means you'll need manual JOINs, which can increase query complexity and reduce developer convenience.

How to listen for notifications in PostgreSQL using igor?

Use the Listen method with a channel name and callback function. Igor handles the PostgreSQL LISTEN command asynchronously, and you can send notifications with Notify, as detailed in the LISTEN/NOTIFY support section.

Is igor suitable for microservices?

Yes, due to its lightweight nature and PostgreSQL focus, but the lack of multi-database support and ORM features might require additional work if integrating with other systems or handling complex data models.

Open-Awesome

igor

Apache-2.0Go

A PostgreSQL abstraction layer for Go with GORM-like syntax, focusing on security and performance.

GitHub

128 stars5 forks0 contributors

What is igor?

Igor is a Go library that serves as an abstraction layer for PostgreSQL, providing a GORM-like syntax for database operations. It enables developers to perform CRUD operations in a secure, fast, and intuitive manner, leveraging PostgreSQL's advanced features like JSONB support and prepared statements. The library focuses on simplifying data access while maintaining high performance and security standards.

Target Audience

Go developers working with PostgreSQL who need a lightweight, secure abstraction layer for database operations without the complexity of a full ORM. It is ideal for projects where performance and SQL injection prevention are critical.

Value Proposition

Developers choose Igor for its balance of GORM compatibility and PostgreSQL-specific optimizations, offering prepared statements by default for security, native support for PostgreSQL types, and efficient CRUD operations without the overhead of associations or DDL management.

Overview

igor is an abstraction layer for PostgreSQL with a gorm like syntax.

Use Cases

Best For

Building Go applications that require secure database access with prepared statements
Migrating from GORM to a PostgreSQL-specific abstraction layer
Implementing event-driven architectures using PostgreSQL LISTEN/NOTIFY
Working with PostgreSQL JSONB and array types in Go
Performing CRUD operations with automatic handling of default values
Developing high-performance database layers without full ORM features

Not Ideal For

Applications requiring complex data relationships with associations between tables
Teams that depend on ORM features like soft delete or automatic callbacks
Projects needing built-in database schema migration tools
Developers who prefer flexible method chaining order as in GORM

Pros & Cons

Pros

Built-in Security

Uses prepared statements by default for all queries, preventing SQL injection and improving performance, as emphasized in the README's security focus.

PostgreSQL Native Features

Supports PostgreSQL-specific types like JSONB and arrays natively, and integrates LISTEN/NOTIFY for event-driven workflows, leveraging database optimizations.

GORM-Like Syntax

Maintains syntax compatibility with GORM, easing migration for existing projects, though with noted differences in method order and model requirements.

Efficient Value Handling

Exploits PostgreSQL's RETURNING clause to automatically update model fields with database-generated values, ensuring data consistency after inserts and updates.

Cons

Missing ORM Features

Lacks support for associations, callbacks, and soft delete, which are standard in full ORMs and necessary for complex data modeling, as admitted in the README.

Rigid Method Order

Requires calling Model before Select, unlike GORM, which can cause errors if not followed and complicates code refactoring, as highlighted in the Differences section.

Error Handling via Panic

Some methods, such as Where without conditions or Delete with empty models, panic instead of returning errors, making error management less robust in production.

PostgreSQL Lock-in

Designed exclusively for PostgreSQL, so it cannot be used with other databases, limiting flexibility for projects that might need multi-database support.

Frequently Asked Questions

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