MongoDB Store

The MongoDB store uses Grove ORM with the mongodriver for database access. It stores each entity type in a dedicated collection and uses MongoDB indexes for efficient querying.

Usage

Standalone

import (
    "github.com/xraph/grove"
    _ "github.com/xraph/grove/drivers/mongodriver"
    mongostore "github.com/xraph/relay/store/mongo"
)

db, err := grove.Open("mongo", "mongodb://localhost:27017/relay")
if err != nil {
    log.Fatal(err)
}

s := mongostore.New(db)

if err := s.Migrate(ctx); err != nil {
    log.Fatal(err)
}

r, err := relay.New(relay.WithStore(s))

With Forge extension

When using the Forge extension with Grove, the store is auto-constructed from the DI container based on the driver type:

app.Use(extension.New(
    extension.WithGroveDatabase(""),  // uses the default grove.DB
))

Or via YAML config:

extensions:
  relay:
    grove_database: ""

The extension detects the mongo driver automatically and constructs the correct store.

Collections

The store uses five collections, all prefixed with relay_:

Migrations

Migrate() creates collections with JSON Schema validation (auto-generated from Grove model structs) and applies indexes. Key indexes include:

• Event types: unique index on name, indexes on group_name and created_at
• Endpoints: compound indexes on (tenant_id, enabled) and (tenant_id, created_at)
• Events: compound index on (tenant_id, type, created_at), sparse unique index on idempotency_key
• Deliveries: compound index on (state, next_attempt_at) for efficient dequeue, plus indexes on endpoint_id and event_id
• DLQ: compound index on (tenant_id, failed_at), index on endpoint_id

Internals

Grove Migrations

The store exports a Migrations group for use with Grove's migration orchestrator. This enables tracked, versioned migrations across all stores in your application:

import mongostore "github.com/xraph/relay/store/mongo"

// mongostore.Migrations is a migrate.Group for the relay mongo store.
// Register it with the grove migration orchestrator for coordinated migrations.

When to use

• When your infrastructure is MongoDB-centric.
• Document-oriented data models where JSON flexibility is preferred.
• Horizontal scaling via MongoDB sharding.