How to Insert and Search Millions of Records in Laravel in Vehicles Table

(For Non-Native Developers, with Simple Examples)

Working with big data in Laravel can feel scary at first — especially if you are not a native English speaker like me. But once you understand the basics, it becomes manageable.

In this post, I will explain how to insert and search millions of records in Laravel — using a real-world example from one of my projects.

---

The Use Case: Vehicles Table

Let’s say you have a table called vehicles. It has millions of rows.

Each row has the following columns:

• make (like Toyota, Honda)

• model (like Corolla, Civic)

• generation (like E210, FK8)

• version (like GR, RS)

• ecu (like Bosch, Siemens)

• torch (yes or no)

Now we want to:

1. Insert thousands or millions of records

2. Search those records quickly

3. Avoid inserting duplicates

4. Make sure Laravel handles everything smoothly

---

Step 1: Do Not Insert One by One

Inserting records one at a time is very slow. If you do:

foreach ($vehicles as $vehicle) {

Vehicle::create($vehicle); // ❌ Very slow for big data

}

This is bad when you have 1 million records. Laravel will run 1 million insert queries.

---

Step 2: Use Bulk Insert or Upsert

Laravel allows you to insert many records at once.

$data = [

['make' => 'Toyota', 'model' => 'Corolla', 'generation' => 'E210', 'version' => 'GR', 'ecu' => 'Bosch', 'torch' => 'yes'],

['make' => 'Honda', 'model' => 'Civic', 'generation' => 'FK8', 'version' => 'RS', 'ecu' => 'Siemens', 'torch' => 'no'],

// more...

];

// Insert in bulk

Vehicle::insert($data);

If you want to avoid duplicates and update existing rows, use upsert():

Vehicle::upsert(

$data,

['make', 'model', 'generation', 'version', 'ecu'], // unique columns

['torch'] // columns to update if duplicate found

);

This is very fast and handles thousands of records at once.

---

Step 3: Use Indexes for Fast Search

If you want to search quickly, your table needs proper indexing.

Without indexes, Laravel will search the entire table row by row. That is very slow.

Add indexes in your migration file like this:

$table->string('make')->index();

$table->string('model')->index();

$table->string('ecu')->index();

This tells the database to prepare fast access to these columns.

---

Step 4: Search Records Efficiently

Now, when a user selects “Toyota”, “Corolla”, and “Bosch”, you can search like this:

$results = Vehicle::where('make', 'Toyota')

->where('model', 'Corolla')

->where('ecu', 'Bosch')

->get();

You can also add limit() or paginate() to avoid loading too much at once:

$results = Vehicle::where('make', 'Toyota')

->paginate(50);

This gives you 50 results per page — much faster and lighter for frontend apps.

---

Step 5: Use Chunking for Processing in Batches

If you need to process all records, use chunk() instead of get():

Vehicle::chunk(1000, function ($vehicles) {

foreach ($vehicles as $vehicle) {

// process each one

}

});

This saves memory and avoids crashing your server.

---

Final Advice for Non-Native Developers

If English is not your first language (like for many of us in Pakistan or similar countries), do not worry.

You do not need fancy words or complex patterns.

Just focus on:

• Writing clean, working code

• Understanding how Laravel handles big data

• Using the right tools (upsert, chunk, index, paginate)

• Learning step by step

I started with small Laravel projects. Today, I work with millions of records and global SaaS apps.

You can do it too. Just take it one step at a time.

---

Summary

✅ Use insert() or upsert() to handle large imports

✅ Add indexes on important columns

✅ Use paginate() or limit() for search

✅ Use chunk() to process in parts

✅ Avoid inserting records one by one

✅ Do not give up — learn slowly and improve every day

---

Thanks for reading.

Let me know if you want a version of this in Urdu, or if you want help applying it to your own Laravel project.