How do I implement cascade save in Bongo?

Implement the GetCascade method in your model struct to return an array of CascadeConfig, defining collection, query, properties, and handling old queries. Use DiffTracker for updates, as shown in the cascade configuration example. This allows automatic propagation of changes to related documents on save.

Bongo vs mgo: which should I use for a Go MongoDB project?

Choose Bongo if you need ODM features like hooks, validation, and cascade operations while retaining low-level access via mgo. Opt for mgo alone if you prioritize raw performance, simplicity, and direct control without the abstraction overhead. Bongo adds convenience but introduces complexity and potential instability.

Does Bongo support MongoDB transactions?

The README does not mention transaction support; Bongo focuses on document-level operations through mgo. For transactions, you may need to use mgo's capabilities directly or assess if Bongo's abstraction limits access to newer MongoDB features like multi-document transactions.

How to handle pagination in Bongo queries?

After a Find operation, use the Paginate method on the ResultSet to get PaginationInfo with details like TotalRecords and RecordsOnPage. This simplifies implementing paginated results, as described in the find section with Paginate(perPage, currentPage).

What are the validation hooks available in Bongo?

Bongo includes a Validate hook that returns a slice of errors for custom logic, along with other lifecycle hooks like BeforeSave and AfterSave. Implement these methods in your model struct and check errors using type assertion to ValidationError, as demonstrated in the saving models example.

Is Bongo compatible with the official Go MongoDB driver?

No, Bongo is specifically a wrapper for the mgo driver and is not designed to work with the official MongoDB Go driver. If you're using the official driver, you'll need to find an alternative ODM or adapter, as Bongo's architecture depends on mgo.

How do I track changes to fields in Bongo?

Implement the Trackable interface in your model struct with a GetDiffTracker method, then use DiffTracker to check modified fields or get all changes. Examples in the change tracking section show how to reset trackers and compare original vs. current values for auditing.

Bongo — Go ODM for MongoDB

What is Bongo?

Bongo is an Object-Document Mapper (ODM) for MongoDB, built as a wrapper around the mgo driver for Go. It provides structured document handling with Go structs, lifecycle hooks, validation, and cascade operations to simplify MongoDB interactions while maintaining access to low-level operations.

Target Audience

Go developers building applications with MongoDB who need a higher-level abstraction for data modeling, validation, and relationship management without losing direct database access.

Value Proposition

Developers choose Bongo for its robust feature set—including hooks, validation, cascade saves/deletes, and change tracking—that fills the gap for a full-featured ODM in Go, offering convention-based simplicity alongside the flexibility to drop down to raw mgo queries when needed.

Go ODM for MongoDB

Use Cases

Best For

Go applications requiring structured data modeling with MongoDB using Go structs and lifecycle hooks.
Implementing complex validation logic with structured error handling for MongoDB documents in Go.
Managing related documents with cascade save and delete operations to maintain data integrity.
Tracking field-level changes in documents for auditing or conditional logic using the built-in diff tracker.
Building Go backends that need paginated query results with easy access to underlying MongoDB queries.
Projects that want an ODM with pre-save and post-save hooks for custom business logic without sacrificing low-level control.

Not Ideal For

Projects requiring absolute API stability for production use, as Bongo's Cascade feature is explicitly marked unstable and subject to breaking changes.
Teams using the official MongoDB Go driver or newer alternatives, since Bongo is tightly coupled with the mgo driver, which may lack support for latest MongoDB features.
Applications where performance overhead must be minimized, as the ODM abstraction adds layers like change tracking and hooks that can impact speed compared to raw queries.
Scenarios needing out-of-the-box transaction support, as Bongo focuses on document-level operations without built-in handling for MongoDB multi-document transactions.

Pros & Cons

Pros

Comprehensive Lifecycle Hooks

Bongo provides BeforeSave, AfterSave, BeforeDelete, AfterDelete, AfterFind, and Validate hooks, allowing custom logic injection at key document lifecycle stages, as detailed in the hooks section of the README.

Structured Validation System

It includes an integrated validation system that returns structured ValidationError objects, making error handling and display straightforward, as shown in the saving models example with type assertion.

Built-in Change Tracking

Offers diff tracking via the Trackable interface to monitor field modifications, useful for auditing or conditional updates, with practical examples in the change tracking section.

Direct Mgo Access

Maintains full access to the underlying mgo driver, enabling developers to drop down to raw MongoDB queries when needed, as highlighted in the philosophy and usage with connection.Session.

Configurable Cascade Operations

Supports cascade save and delete for data integrity across related documents, though unstable, with detailed CascadeConfig setup examples in the README.

Cons

Unstable Cascade Feature

The cascade functionality is labeled unstable in the README and may require refactoring, posing risks for production environments where data consistency is critical.

Dependent on Legacy Mgo

Bongo is built on the mgo driver, which is older and might not integrate well with modern Go modules or support the latest MongoDB advancements, limiting future-proofing.

Complex Cascade Configuration

Setting up cascade operations involves verbose CascadeConfig structs and manual diff tracking, increasing development complexity and potential for errors, as seen in the cascade example.

Sparse Advanced Features

Lacks mention of support for newer MongoDB features like transactions or aggregation pipelines in its ODM layer, requiring fallback to raw mgo which may be cumbersome.

Frequently Asked Questions

What is Bongo?

Target Audience

Go developers building applications with MongoDB who need a higher-level abstraction for data modeling, validation, and relationship management without losing direct database access.

Value Proposition

Use Cases

Best For

Go applications requiring structured data modeling with MongoDB using Go structs and lifecycle hooks.
Implementing complex validation logic with structured error handling for MongoDB documents in Go.
Managing related documents with cascade save and delete operations to maintain data integrity.
Tracking field-level changes in documents for auditing or conditional logic using the built-in diff tracker.
Building Go backends that need paginated query results with easy access to underlying MongoDB queries.
Projects that want an ODM with pre-save and post-save hooks for custom business logic without sacrificing low-level control.

Not Ideal For

Projects requiring absolute API stability for production use, as Bongo's Cascade feature is explicitly marked unstable and subject to breaking changes.
Teams using the official MongoDB Go driver or newer alternatives, since Bongo is tightly coupled with the mgo driver, which may lack support for latest MongoDB features.
Applications where performance overhead must be minimized, as the ODM abstraction adds layers like change tracking and hooks that can impact speed compared to raw queries.
Scenarios needing out-of-the-box transaction support, as Bongo focuses on document-level operations without built-in handling for MongoDB multi-document transactions.

Pros & Cons

Pros

Comprehensive Lifecycle Hooks

Structured Validation System

Built-in Change Tracking

Offers diff tracking via the Trackable interface to monitor field modifications, useful for auditing or conditional updates, with practical examples in the change tracking section.

Direct Mgo Access

Maintains full access to the underlying mgo driver, enabling developers to drop down to raw MongoDB queries when needed, as highlighted in the philosophy and usage with connection.Session.

Configurable Cascade Operations

Supports cascade save and delete for data integrity across related documents, though unstable, with detailed CascadeConfig setup examples in the README.

Cons

Unstable Cascade Feature

The cascade functionality is labeled unstable in the README and may require refactoring, posing risks for production environments where data consistency is critical.

Dependent on Legacy Mgo

Bongo is built on the mgo driver, which is older and might not integrate well with modern Go modules or support the latest MongoDB advancements, limiting future-proofing.

Complex Cascade Configuration

Setting up cascade operations involves verbose CascadeConfig structs and manual diff tracking, increasing development complexity and potential for errors, as seen in the cascade example.

Sparse Advanced Features

Lacks mention of support for newer MongoDB features like transactions or aggregation pipelines in its ODM layer, requiring fallback to raw mgo which may be cumbersome.

Frequently Asked Questions

Bongo

What is Bongo?

Overview

Use Cases

Best For

Not Ideal For

Pros & Cons

Pros

Cons

Frequently Asked Questions

Related Projects

Found a gem we're missing?

Bongo

What is Bongo?

Overview

Use Cases

Best For

Not Ideal For

Pros & Cons

Pros

Cons

Frequently Asked Questions

Related Projects

Found a gem we're missing?