MongoDB Transactions in Laravel

This tutorial was written by Farhan Chowdhury.

Laravel is one of the most widely adopted PHP frameworks. Developers love it for its elegant syntax, expressive ORM, and batteries-included experience. MongoDB, on the other hand, has become a go-to choice for flexible, schema-less storage that scales effortlessly. Together, they form a powerful stack that combines Laravel’s productivity with MongoDB’s agility in handling modern application data.

When building production-grade applications, one thing becomes non-negotiable: data integrity. Whether you are managing financial transactions, maintaining inventory counts, or recording orders, your data must remain accurate and consistent even when multiple operations occur simultaneously. That’s where transactions come in.

Traditionally, MongoDB was seen as a non-transactional database. It offered speed and flexibility but lacked the multi-document atomic guarantees that developers rely on in SQL systems. That changed with MongoDB 4.0, which introduced multi-document ACID transactions. Now, developers can enjoy both schema flexibility and transactional safety when operations require consistency across multiple documents or collections.

In this article, we’ll explore how MongoDB transactions work and how you can leverage them within a Laravel application. We’ll begin with the fundamentals of transactions, examine MongoDB’s implementation of ACID properties, and then move into Laravel-specific examples. You’ll see how transactions fit naturally into common use cases like order management or payment processing. We’ll also cover best practices, common pitfalls, and when it makes more sense to rely on MongoDB’s document model instead of wrapping everything in a transaction.

By the end, you’ll have a clear understanding of how to implement and optimize MongoDB transactions in Laravel to build applications that are fast, flexible, and reliable.

Understanding transactions in databases

A transaction in database systems represents a unit of work, a set of operations that must either all succeed or all fail together. Transactions provide a safety boundary that prevents incomplete or inconsistent changes from entering the database.

To formalize this behavior, databases rely on the ACID properties:

• Atomicity: Treats all operations in a transaction as one indivisible unit. If one operation fails, the entire transaction is rolled back. For instance, in a fund transfer, if money is deducted from one account but not credited to another, atomicity prevents the database from committing partial changes.

• Consistency: Ensures that the database moves from one valid state to another. Once a transaction completes, all constraints, indexes, and rules remain satisfied. For example, if a rule says that an account balance cannot go negative, consistency ensures this holds true after every transaction.

• Isolation: Prevents concurrent transactions from interfering with each other. Imagine two customers checking out items from the same inventory at the same time. Isolation ensures the final stock count reflects both operations correctly.

• Durability: Guarantees that once a transaction is committed, its results persist even in the face of crashes or restarts. If a payment succeeds, durability ensures that the record remains intact after a reboot.

In relational databases such as MySQL or PostgreSQL, ACID transactions are standard. MongoDB initially guaranteed atomicity only at the single-document level. Each document update was safe, but cross-document consistency had to be managed by the application. As workloads became more complex, MongoDB evolved to include multi-document transactions while maintaining its flexible document model.

Transactions are particularly crucial in business applications.

Consider a banking system where transferring funds requires deducting from one account and adding to another. Without transactions, one side of the operation could complete while the other fails.

In e-commerce, confirming an order may involve updating stock, creating an order record, and charging the customer. Transactions ensure all these steps succeed or none of them do.

In short, transactions are the backbone of trust in applications where accuracy, reliability, and fairness are essential. Next, we’ll look at how MongoDB implements these guarantees and how Laravel can make use of them.

MongoDB’s transaction model

When MongoDB was first released, it offered atomicity at the document level. This meant that any single document update was guaranteed to be all or nothing. The design worked well for many workloads, especially where embedding related data in a single document eliminated the need for multi-record transactions.

As MongoDB adoption grew in enterprise environments, developers needed stronger consistency guarantees across multiple collections. This led to the introduction of multi-document ACID transactions in MongoDB 4.0.

Evolution of MongoDB transactions

• Pre-4.0: Only single-document operations were atomic. Developers had to design schemas carefully, often embedding related data in one document to avoid inconsistencies.
• MongoDB 4.0: Introduced multi-document transactions for replica sets.
• MongoDB 4.2 and later: Expanded support to sharded clusters, making transactions viable even in horizontally scaled environments.

This shift brought MongoDB closer to the transactional guarantees of relational systems while keeping its document-oriented flexibility intact.

How transactions work

In MongoDB, transactions use a session object to group operations. You start a transaction, execute operations across multiple collections, and then either commit or abort it. Behind the scenes, MongoDB coordinates changes to ensure that ACID guarantees hold true.

Here’s how to perform a transactional workflow in Laravel (PHP) using MongoDB’s session-based transactions:

use Illuminate\Support\Facades\DB;

DB::connection('mongodb')->transaction(function ($session) {
    // 1) Create an order
    DB::connection('mongodb')->collection('orders')->insert([
        'item' => 'Laptop',
        'qty'  => 1,
        'created_at' => now(),
    ], ['session' => $session]);

    // 2) Decrease inventory stock
    DB::connection('mongodb')->collection('inventory')
        ->where('sku', 'LAP123')
        ->decrement('stock', 1, [], ['session' => $session]);
});

The $session object used in the code above plays a pivotal role in the transaction process. It serves as a shared context that links all operations within a transaction, allowing MongoDB to recognize and coordinate them as a single atomic sequence.

By explicitly passing $session into each query, you ensure that MongoDB treats those operations as part of one logical transaction. Without this, the database would execute each statement independently, losing the atomicity that transactions are meant to guarantee.

The DB::connection('mongodb')->transaction() helper opens a session and ensures that all enclosed operations run atomically. If any statement throws an error, the transaction is rolled back. Otherwise, it commits successfully.

Limitations and considerations

While transactions are powerful, they also come with some shortcomings.

Performance overhead: Transactions add coordination costs because the database must manage locks, synchronize writes, and track session state across multiple documents. Long or complex transactions can slow down the system.

Timeouts: Transactions have a maximum lifetime of 60 seconds by default. If a transaction involves slow queries, large batch writes, or network latency, it may exceed this limit and be aborted automatically.

Not all operations are allowed: Certain operations cannot run inside a transaction. Examples include creating or dropping indexes, running DDL commands, or any operation that requires global locks. These actions must be handled outside the transactional context.

Increased resource usage: Each transaction consumes additional memory for locks, oplog entries, and in-progress snapshots. The more operations a transaction includes, the higher the demand on system resources, which can affect performance.

Transactions vs. embedded documents

In MongoDB, data modeling usually gives you two options: embedding related documents inside a parent document or storing them in separate collections and linking them with references.

Embedding often removes the need for transactions altogether, since updates to a single document are always atomic. For example, you might store an order and all of its line items inside one JSON document. Updating the order, adding a new item, or marking it as paid can all happen atomically without requiring a multi-document transaction.

By contrast, when related information naturally belongs in different collections, such as orders, payments, and inventory, transactions are used to maintain consistency across them. The choice depends on your data structure and how you query it. Embedding favors locality and simplicity, while referencing and transactions favor separation of concerns and data consistency across collections.

MongoDB’s flexible schema allows developers to avoid transactions in many cases by embedding related data. For example, instead of using a transaction to link an order to its line items, you could embed the line items directly inside the order document. Transactions should be reserved for situations where relationships span multiple collections and must remain consistent.

With this understanding of MongoDB’s transaction model, we’re now ready to look at how to set up Laravel to take advantage of these capabilities.

Setting up Laravel with MongoDB for transactions

Now that we’ve explored MongoDB’s transaction model and when to use it, the next step is preparing a Laravel project to work with these capabilities. Transactions won’t function unless the environment is configured correctly, so let’s make sure the foundation is in place before diving into real examples.

Multi-document transactions in MongoDB require a replica set (or a sharded cluster). If you’re using MongoDB Atlas, this comes built-in. For local development, you’ll need to run MongoDB as a replica set (for example, via Docker using a --replSet argument or docker-compose configuration).

Step 1: Install the package

Install the official Laravel MongoDB package via Composer. As of now, the recommended version is ^5.5, which ensures compatibility with Laravel 11 and PHP 8.3.

composer require mongodb/laravel-mongodb:^5.5

Step 2: Configure environment variables

Open your .env file and define your MongoDB connection credentials. If you’re using MongoDB Atlas, you can copy the connection string directly from your cluster dashboard:

DB_CONNECTION=mongodb
MONGODB_URI="mongodb+srv://<username>:<password>@cluster0.mongodb.net"
MONGODB_DATABASE=laravel_mongo_tx_demo

Note: The +srv format is used by MongoDB Atlas. For a local setup, your URI might look like mongodb://127.0.0.1:27017/?replicaSet=rs0.

Step 3: Update config/database.php

Insert the MongoDB connection details into Laravel’s database configuration so the framework can route database calls through the MongoDB Driver:

// config/database.php
return [
    'connections' => [
        'mongodb' => [
            'driver'   => 'mongodb',
            'dsn'      => env('MONGODB_URI'),
            'database' => env('MONGODB_DATABASE'),
        ],
    ],
];

Step 4: Create a MongoDB model

Models work similarly to Eloquent models in SQL databases but extend a different base class. For example:

use MongoDB\Laravel\Eloquent\Model;

class HealthCheck extends Model
{
    protected $connection = 'mongodb';
    protected $collection = 'health_checks';
    protected $fillable = ['ok'];
}

Step 5: Run a quick test

You can confirm that the connection works either using Laravel Tinker or a simple closure route.

Option A: Laravel Tinker

php artisan tinker

HealthCheck::create(['ok' => true]);
HealthCheck::all();

Option B: Closure route

// routes/web.php
Route::get('/test-mongo', function () {
    HealthCheck::create(['ok' => true]);
    return HealthCheck::all();
});

If you can view the inserted document either through Laravel or MongoDB Compass, your setup is complete and ready for transactional operations.

Performing transactions in Laravel

With setup complete, we can now see how transactions actually work inside a Laravel project. MongoDB provides multi‑document ACID transactions by grouping operations into a client session. The Laravel MongoDB package exposes this underlying client so you can explicitly start sessions, run transactional logic, and commit or abort as necessary.

The mental model

Before jumping into code, it helps to understand the basic flow of how a transaction operates conceptually in MongoDB when used through Laravel:

• Start a client session.
• Execute all reads/writes inside a withTransaction callback.
• The driver commits if the callback succeeds or aborts if your code throws.
• Pass the session to each operation so they participate in the same transaction.

Minimal example: Debit/credit transfer

Consider a transfer between two user wallets. Both the debit and credit must succeed or fail together.

use Illuminate\Support\Facades\DB;
use MongoDB\BSON\ObjectId;
use MongoDB\Driver\ReadConcern;
use MongoDB\Driver\ReadPreference;
use MongoDB\Driver\WriteConcern;

function transfer(string $from, string $to, int $amount): void
{
    $conn   = DB::connection('mongodb');
    $client = $conn->getMongoClient();
    $db     = $conn->getMongoDB();

    $session = $client->startSession([
        'defaultTransactionOptions' => [
            'readConcern'     => new ReadConcern(ReadConcern::LOCAL),
            'writeConcern'    => new WriteConcern(WriteConcern::MAJORITY),
            'readPreference'  => new ReadPreference(ReadPreference::PRIMARY),
        ],
    ]);

    $session->withTransaction(function () use ($db, $session, $from, $to, $amount) {
        $users = $db->selectCollection('users');

        // Ensure sender has enough balance
        $fromDoc = $users->findOne([
            '_id' => new ObjectId($from),
            'balance' => ['$gte' => $amount],
        ], ['session' => $session]);

        if (!$fromDoc) {
            throw new RuntimeException('Insufficient funds.');
        }

        // Debit and credit in one transaction
        $users->updateOne(
            ['_id' => new ObjectId($from)],
            ['$inc' => ['balance' => -$amount]],
            ['session' => $session]
        );

        $users->updateOne(
            ['_id' => new ObjectId($to)],
            ['$inc' => ['balance' => $amount]],
            ['session' => $session]
        );

        // Optional audit log
        $db->selectCollection('transfers')->insertOne([
            'from'    => new ObjectId($from),
            'to'      => new ObjectId($to),
            'amount'  => $amount,
            'created_at' => now(),
        ], ['session' => $session]);
    });
}

This approach is explicit and mirrors MongoDB’s official PHP examples. The critical piece is passing ['session' => $session] to each operation.

Mixing Eloquent with transactions

You can still use Laravel’s expressive query builder and Eloquent models inside a transaction while keeping sessions explicit:

use MongoDB\Laravel\Eloquent\Model;

class User extends Model {
    protected $connection = 'mongodb';
    protected $collection = 'users';
    protected $fillable   = ['name','balance'];
}

function addStoreCredit(string $userId, int $amount): void
{
    $conn   = DB::connection('mongodb');
    $client = $conn->getMongoClient();
    $db     = $conn->getMongoDB();

    $session = $client->startSession();

    $session->withTransaction(function () use ($session, $db, $userId, $amount) {
        $db->selectCollection('users')->updateOne(
            ['_id' => new ObjectId($userId)],
            ['$inc' => ['balance' => $amount]],
            ['session' => $session]
        );

        $fresh = User::where('_id', new ObjectId($userId))->first();
        // Do something with $fresh
    });
}

This hybrid approach lets you enjoy Eloquent’s ergonomics without losing transactional guarantees.

Error handling and retries

• Throwing an exception inside the callback aborts and rolls back the transaction automatically.
• In distributed environments, you may encounter transient errors (for example, primary elections). These often come with the label TransientTransactionError. Wrap your transaction logic with a retry mechanism if necessary.

try {
    transfer($from, $to, $amount);
} catch (Throwable $e) {
    report($e);
    throw $e; // or retry based on error type
}

Quick test in Tinker

Let’s verify our implementation in a practical way by running a quick experiment inside Laravel Tinker. This will help confirm that the session-based transaction behaves exactly as expected.

DB::connection('mongodb')->getMongoDB()->selectCollection('users')->insertMany([
  ['_id' => new MongoDB\BSON\ObjectId($a = (string) new MongoDB\BSON\ObjectId), 'name' => 'Alice', 'balance' => 500],
  ['_id' => new MongoDB\BSON\ObjectId($b = (string) new MongoDB\BSON\ObjectId), 'name' => 'Bob',   'balance' => 100],
]);

transfer($a, $b, 150);

If Alice’s balance decreases by 150 and Bob’s increases by 150, the transaction succeeded. Commenting out one update and rerunning shows that balances remain unchanged—evidence of rollback.

Performance considerations

Transactions consume extra resources. Keep them short and efficient; avoid long user waits inside a transaction, minimize the number of operations, and don’t stream large results. MongoDB also enforces a maximum transaction duration. For complex workflows, consider breaking them up or relying on MongoDB’s natural single‑document atomicity and embedded documents when appropriate.

With these patterns in hand, you can confidently design transactional workflows such as payments, order fulfillment, and audits directly in Laravel while retaining MongoDB’s flexibility.

Advanced use cases and real-world scenarios

Once you’re comfortable with basic transactions, it’s time to look at how they fit into real-world workflows. Transactions aren’t limited to banking systems; they can help enforce consistency anywhere multiple collections depend on each other. In this section, we’ll go through practical examples of using MongoDB transactions in Laravel projects and what to watch out for when applying them in production.

E‑commerce order workflow

One of the most common use cases for multi‑document transactions is e‑commerce. When a customer places an order, several operations must succeed together:

• Deduct stock from the inventory.
• Create a new order document.
• Update the user’s balance or reward points.

If any of these steps fail, the entire operation should roll back to prevent inconsistent states, such as missing stock without an actual order. Here’s how you can implement this flow:

DB::connection('mongodb')->transaction(function ($session) use ($userId, $productId, $quantity) {
    $db       = DB::connection('mongodb')->getMongoDB();
    $products = $db->selectCollection('products');
    $orders   = $db->selectCollection('orders');
    $users    = $db->selectCollection('users');

    // Read the product within the same session (transactional snapshot)
    $product = $products->findOne(
        ['_id' => new ObjectId($productId)],
        ['projection' => ['price' => 1, 'stock' => 1], 'session' => $session]
    );

    if (! $product || ($product['stock'] ?? 0) < $quantity) {
        throw new RuntimeException('Insufficient stock.');
    }

    $total = ($product['price'] ?? 0) * $quantity;

    // Deduct stock
    $products->updateOne(
        ['_id' => new ObjectId($productId)],
        ['$inc' => ['stock' => -$quantity]],
        ['session' => $session]
    );

    // Create order
    $orders->insertOne([
        'user_id'    => new ObjectId($userId),
        'product_id' => new ObjectId($productId),
        'quantity'   => $quantity,
        'total'      => $total,
        'status'     => 'confirmed',
        'created_at' => now(),
    ], ['session' => $session]);

    // Update user balance
    $users->updateOne(
        ['_id' => new ObjectId($userId)],
        ['$inc' => ['balance' => -$total]],
        ['session' => $session]
    );
});

This example ensures all three operations either commit together or not at all. If the balance update or order creation fails, MongoDB automatically rolls back the stock deduction. It’s a clean way to enforce consistency across collections that represent separate business entities.

User registration with related collections

Another great use case is onboarding. When a new user registers, you might want to create multiple related documents in a single atomic operation:

• A users document containing credentials and profile details
• A profiles document with extended information
• An audit_logs document to record the registration event

You can wrap all of these inserts inside one transaction:

DB::connection('mongodb')->transaction(function ($session) use ($data) {
    $db = DB::connection('mongodb')->getMongoDB();

    $users    = $db->selectCollection('users');
    $profiles = $db->selectCollection('profiles');
    $audits   = $db->selectCollection('audit_logs');

    $userInsert = $users->insertOne(
        $data['user'],
        ['session' => $session]
    );

    $userId = $userInsert->getInsertedId();

    $profiles->insertOne([
        'user_id' => $userId,
        'bio'     => $data['profile']['bio'] ?? '',
        'avatar'  => $data['profile']['avatar'] ?? null,
    ], ['session' => $session]);

    $audits->insertOne([
        'action'    => 'user_registered',
        'user_id'   => $userId,
        'timestamp' => now(),
    ], ['session' => $session]);
});

This transaction guarantees that no orphaned profiles or audit logs exist without their corresponding user record. It’s especially valuable in systems where registration triggers multiple downstream actions or analytics events.

Payment processing systems

Payment systems are another classic example where atomic operations are critical. Consider a digital wallet app where a user sends funds to another user. You need to ensure both debit and credit happen together:

DB::connection('mongodb')->transaction(function ($session) use ($from, $to, $amount) {
    Wallet::where('user_id', $from)->decrement('balance', $amount, [], $session);
    Wallet::where('user_id', $to)->increment('balance', $amount, [], $session);

    Transaction::create([
        'from' => $from,
        'to' => $to,
        'amount' => $amount,
        'timestamp' => now(),
    ], $session);
});

If either balance update fails, the transaction is rolled back automatically. This ensures the sender and receiver accounts never drift out of sync.

Balancing performance and safety

While transactions offer strong consistency guarantees, they also introduce overhead. Each transaction holds locks and requires coordination between replica set members. Here are a few ways to keep them efficient:

• Keep transactions short‑lived and focused. Don’t run heavy queries inside them.
• Only include the collections necessary for the operation.
• Avoid user‑facing delays; perform long‑running calculations before entering a transaction.

When you design your data model thoughtfully, using embedding where appropriate and transactions only when necessary, you get the best of MongoDB’s flexibility without sacrificing data integrity.

When to use transactions vs. embedded documents

In MongoDB, there’s more than one way to structure data. You can either embed related information inside a single document or separate it into multiple collections connected by references. Both strategies can maintain consistency, but each carries its own trade-offs in complexity and performance. Knowing when to use transactions versus embedded documents is one of the key skills in designing efficient MongoDB applications.

One of MongoDB’s greatest strengths lies in its flexible schema design. Developers can model data in different ways depending on the needs of the application. However, that flexibility can also lead to confusion when deciding whether to use multi-document transactions or embedded documents. Both approaches ensure data consistency, but they differ significantly in how they impact performance, scalability, and complexity.

Embedded documents: The natural fit for most use cases

In MongoDB, a single document can represent a complete entity along with its related data. This design is often referred to as embedding. Instead of splitting related data into multiple collections, you store them together in a single document.

For example, consider an order that contains several line items. In a relational database, you’d typically have two tables, orders and order_items, linked by a foreign key. In MongoDB, this can be modeled as one document with an array of items:

{
  "_id": ObjectId("652ef9a..."),
  "customer_id": ObjectId("652ef1b..."),
  "total": 120.50,
  "items": [
    { "product": "Laptop", "quantity": 1, "price": 1000 },
    { "product": "Mouse", "quantity": 2, "price": 20 }
  ],
  "status": "processing"
}

In this case, the order and its items are tightly coupled. They’ll almost always be read and updated together. Storing them in the same document allows you to perform atomic updates without needing transactions at all. MongoDB guarantees atomicity at the single-document level, no matter how deeply nested the structure is.

Advantages of embedding:

• Atomic updates without needing transactions
• Faster reads since all related data lives in the same document
• Simplified schema with no need for joins or cross-collection lookups

When to embed:

• The related data is always accessed together.
• The document size remains well under the 16 MB BSON limit.
• The data doesn’t change frequently or independently.

When transactions become necessary

Transactions shine when multiple collections or documents need to stay consistent with one another. For example, imagine an order document in one collection and a payment document in another. These two entities are related, but they don’t belong in the same document because their lifecycles and update patterns differ. You might need to insert a payment record and simultaneously update the order’s status:

DB::connection('mongodb')->transaction(function ($session) {
    Order::where('_id', $orderId)
        ->update(['status' => 'paid'], [], $session);

    Payment::create([
        'order_id' => $orderId,
        'amount' => 120.50,
        'method' => 'credit_card',
        'timestamp' => now()
    ], $session);
});

In this scenario, if one operation fails, such as the payment record not being created, the entire transaction rolls back, ensuring your database doesn’t end up in a half-updated state.

Advantages of transactions:

• Maintain consistency across multiple collections
• Handle complex workflows involving multiple entities
• Essential for financial, inventory, and auditing systems where every change must balance across documents

When to use transactions:

• You’re updating multiple documents that must remain in sync.
• The data resides in separate collections for valid modeling reasons.
• The application needs ACID guarantees beyond a single document.

Choosing the right approach

A good rule of thumb is to start with embedding and only introduce transactions when necessary. Embedding simplifies your data model and offers excellent performance for most workloads. However, as your application grows, certain workflows will demand the stronger consistency guarantees that only transactions provide.

Scenario	Recommended Approach
Order with line items	Use embedding to store all order details, including items, quantities, and prices, in a single document. This allows quick access to complete order data and ensures atomic updates during checkout.
User profile and settings	Embed user preferences, notification settings, and small configuration data within the same user document for faster reads and simpler updates. This keeps all user-related information localized.
Order and payment data	Use transactions when payment records and order updates occur in separate collections. This ensures that the order status is only marked as paid when the payment record has been successfully written.
Multi-step financial operations	Implement transactions to handle linked operations, such as crediting one account while debiting another. Transactions help maintain accurate balances and prevent partial updates.
Logs and audit trails	Store logs and audit records in a separate collection to avoid document bloat. Use transactions only if these records must remain synchronized with state changes in other collections, such as during financial reconciliation.

Ultimately, choosing between transactions and embedding is about finding balance. Use embedding for locality and simplicity, and use transactions for cross-collection consistency. With thoughtful modeling, you can take advantage of both to build performant, reliable MongoDB applications within Laravel.

Best practices for transactions in Laravel + MongoDB

When working with transactions in Laravel and MongoDB, efficiency and reliability depend on how well you structure, execute, and monitor your operations. While the mongodb/laravel-mongodb package simplifies much of the process, following a few disciplined practices ensures your transactions remain performant and predictable.

1. Keep transactions short-lived

Every transaction in MongoDB holds locks on the documents it touches. The longer a transaction runs, the more likely it is to block other operations and increase contention. Design your logic so that a transaction performs only the minimal set of operations necessary. For example, deduct an amount, update inventory, confirm an order, and then commit immediately. Avoid mixing unrelated writes within the same session.

In Laravel, this means keeping your transaction closure concise:

DB::connection('mongodb')->transaction(function ($session) {
    $order = Order::create(['status' => 'pending'], [], $session);
    Inventory::where('item_id', $order->item_id)->decrement('stock', 1, [], $session);
    Payment::create(['order_id' => $order->_id, 'status' => 'initiated'], [], $session);
});

2. Use indexes inside transactions

Transactions can become slower if queries within them scan large collections. Ensure that fields used in where and update filters are properly indexed. For example, if you often query by order_id or user_id inside a transaction, create indexes on those fields:

Schema::connection('mongodb')->table('orders', function ($collection) {
    $collection->index('user_id');
});

This simple optimization can make a noticeable difference when dealing with production workloads.

3. Avoid unnecessary collections

Each additional collection involved in a transaction adds coordination overhead. MongoDB must maintain consistency across all of them, which can lead to performance drops. Whenever possible, restructure your data so that related entities live within the same collection or as embedded documents, particularly for one-to-one or tightly coupled relationships.

For instance, if you only store user profile details, consider embedding them within the user document instead of spreading them across multiple collections.

4. Handle errors and retries gracefully

MongoDB may abort a transaction due to transient errors like network interruptions, primary failovers, or write conflicts. Laravel’s transaction() method will automatically roll back on unhandled exceptions, but it’s good practice to handle retries explicitly for critical paths:

$attempts = 0;
$maxAttempts = 3;

do {
    try {
        DB::connection('mongodb')->transaction(function ($session) {
            // transactional operations
        });
        break; // success
    } catch (\Throwable $e) {
        $attempts++;
        if ($attempts >= $maxAttempts) {
            throw $e;
        }
        sleep(1); // backoff before retry
    }
} while (true);

This approach ensures resilience without overwhelming the system with repeated retries.

5. Log failures for debugging

When a transaction fails, it’s essential to know why. Always log contextual details such as the collection name, document IDs, and exception messages. This information helps during post-incident reviews and guides future optimizations:

Log::error('Transaction failed', [
    'collection' => 'orders',
    'error' => $e->getMessage(),
]);

Pairing these logs with MongoDB’s explain() command or performance metrics from Atlas can reveal inefficiencies in your queries.

6. Test transaction logic thoroughly

Unit and feature tests should verify both success and failure scenarios. For instance, ensure that rollbacks occur correctly when one operation fails and that no partial data remains. Using Laravel’s in-memory or isolated test database setup helps validate transactional consistency:

public function test_order_rollback_on_payment_failure()
{
    $this->expectException(PaymentException::class);

    DB::connection('mongodb')->transaction(function ($session) {
        Order::create(['status' => 'pending'], [], $session);
        throw new PaymentException('Payment gateway unavailable');
    });

    $this->assertCount(0, Order::all());
}

By following these best practices—short, well-indexed transactions with clear error handling, structured logging, and proper testing—you can take full advantage of MongoDB’s ACID guarantees while maintaining performance. Laravel’s expressive API makes these techniques straightforward to implement and easy to maintain.

Common pitfalls and how to avoid them

Even though MongoDB’s transaction support is robust and Laravel provides a clean abstraction around it, developers often run into subtle mistakes that cause unexpected rollbacks, partial writes, or degraded performance. Understanding these pitfalls early can help you build more reliable and efficient transactional systems.

1. Forgetting to pass the $session

One of the most common issues when using transactions in Laravel with MongoDB is forgetting to pass the $session object to every query inside the transaction callback. Each operation that should be part of the transaction must share the same session. If you omit it for even one query, that operation will execute outside the transaction, defeating the purpose of atomicity.

Example mistake:

DB::connection('mongodb')->transaction(function ($session) {
    // This update is inside the transaction
    User::where('_id', $from)->decrement('balance', 100, [], $session);

    // This one will run outside the transaction if $session is not passed
    User::where('_id', $to)->increment('balance', 100);
});

Fix: Always include $session explicitly in every read and write inside the transaction.

2. Mixing inconsistent reads and writes

MongoDB maintains transaction-level consistency, but mixing different isolation levels or using reads that bypass the transaction session can cause anomalies. For instance, reading a document outside the session and then updating it inside can result in stale data being used.

Best practice: Perform all reads and writes within the same transaction session. If you must read data before starting the transaction, validate or re-fetch it within the transaction to ensure it hasn’t changed.

3. Handling large documents or collections

MongoDB transactions aren’t designed for huge documents or large batch updates. Large payloads increase memory usage and slow down commits, especially when multiple documents are locked. This can trigger rollbacks or lock contention.

Best practice: Keep documents reasonably sized (well below the 16 MB limit) and avoid multi-document transactions for operations involving thousands of records. Instead, consider breaking the logic into smaller, idempotent batches or using MongoDB’s bulk write operations where atomicity isn’t critical.

4. Letting transactions run too long

Transactions that take too long to complete can block other operations and cause performance bottlenecks. MongoDB automatically aborts transactions that exceed a configured lifetime (by default, 60 seconds). Long-running transactions also hold locks longer, impacting concurrency.

Best practice: Keep transactions short and focused—perform only essential reads and writes, and avoid heavy computations or network calls inside the transaction callback. If you need to process large datasets, process them in chunks outside the transactional context.

5. Ignoring exception handling and retries

Transactions can abort due to transient errors such as network timeouts, primary stepdowns, or write conflicts. Failing to catch these exceptions and retry the transaction can lead to data inconsistency or lost writes.

Best practice: Wrap transactions in a retry loop to handle transient failures. For example:

$maxRetries = 3;
$attempt = 0;

do {
    try {
        DB::connection('mongodb')->transaction(function ($session) {
            // Transaction logic here
        });
        break;
    } catch (\MongoDB\Driver\Exception\RuntimeException $e) {
        if (++$attempt >= $maxRetries) {
            throw $e;
        }
    }
} while (true);

6. Debugging without proper logging

When transactions silently fail or roll back, developers often have little insight into what went wrong. Laravel’s exception handling may not always show MongoDB-specific errors unless explicitly logged.

Best practice: Add structured logs or events inside your transaction callbacks. Log failures, retries, and abort causes using Laravel’s logging system. You can also use MongoDB’s db.currentOp() or profiler to monitor transaction behavior in development environments.

By keeping these pitfalls in mind and adopting disciplined session usage, proper error handling, and efficient transaction design, you can ensure MongoDB transactions in Laravel stay consistent, performant, and maintainable.

Conclusion

MongoDB transactions bring a level of consistency and reliability that was once exclusive to traditional SQL databases. Through this article, we explored what transactions are, how MongoDB implements them, and how Laravel integrates these capabilities into a familiar, expressive API.

From the fundamentals of ACID properties to advanced real-world use cases, you now have the tools to safely coordinate multi-document operations and maintain data integrity across collections.

While MongoDB’s flexibility encourages creative data modeling, transactions shouldn’t be treated as a default solution. They’re powerful when used intentionally—for example, in scenarios that demand strict atomicity or cross-collection consistency—but unnecessary for single-document updates or embedded document designs.

The key takeaway is to balance consistency with performance and design your schema in a way that leverages MongoDB’s strengths while respecting its constraints. If used judiciously, transactions can make your Laravel applications more robust without sacrificing the agility MongoDB is known for.

Next steps

Now that you’ve seen how transactions work in MongoDB and how easily Laravel can manage them, try incorporating them into your own applications.

Experiment with different transactional workflows, measure their performance, and review how they fit into your overall data model.

For deeper dives, check out the official MongoDB documentation and the Laravel MongoDB package guide.

You can also take this further by exploring advanced MongoDB Atlas features such as triggers, serverless instances, and automated performance monitoring.

Each of these complements the transactional model and helps build scalable, reliable, and modern Laravel applications backed by MongoDB.