Modern web applications are no longer judged only by features. They are judged by speed, search accuracy, and user experience.

If your Laravel application has:

• Multiple filters (country, state, city, specialization)
• Text search (single or multiple keywords)
• Sorting (latest, rating, relevance, etc.)
• Growing data
• Many concurrent users

Then traditional MySQL-only search is not enough.

This tutorial explains, in simple and practical terms:

• Why MySQL struggles at scale
• Why Laravel Scout exists
• What Typesense and Meilisearch are
• Which one to choose
• Whether they are free
• Whether they work with PHP 8.2 and Laravel 10+
• How to use them on a basic server (no Docker, no Horizon, no queues)
• The best backend + frontend search strategy
• A future-proof architecture that will not break under load

This is written for real projects, not demos.

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Why MySQL-Only Search Becomes a Problem

At the beginning, MySQL feels fine:

• LIKE %keyword%
• WHERE country_id = ?
• ORDER BY created_at DESC

But as data grows, problems start appearing:

1. LIKE queries are slow
2. Multiple filters + joins are expensive
3. Sorting + filtering together kills indexes
4. Search UX becomes laggy
5. Concurrency causes DB load spikes

MySQL is excellent for transactions and consistency,
but it is not a search engine.

This is where search indexing comes in.

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What Laravel Scout Actually Is (Important to Understand)

Laravel Scout is not a search engine.

Laravel Scout is:

• A bridge between Laravel models and search engines
• A standard API for indexing and searching data
• A way to keep your Laravel code clean and future-proof

Scout lets you:

• Map a model → search index
• Swap search engines later
• Keep your app logic independent from the engine

Scout supports:

• Database (basic)
• Meilisearch
• Typesense
• Other engines

Scout itself is free and stable.

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What Typesense and Meilisearch Really Are

Typesense

Typesense is:

• A fast, open-source search engine
• Built specifically for filtering, faceting, and sorting
• Optimized for low-latency, high-concurrency search
• Designed to power search-driven UIs

Key strengths:

• Excellent multi-filter performance
• Strong sorting support
• Predictable relevance
• Very fast response times

Meilisearch

Meilisearch is:

• A developer-friendly open-source search engine
• Focused on ease of use
• Very fast to set up
• Great default search behavior

Key strengths:

• Simple setup
• Good relevance out of the box
• Friendly for small teams and MVPs

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Are They Free?

Yes — both are free if self-hosted.

What “free” really means

• No license cost
• No per-request cost
• No user limit

You only pay for:

• Your server (VPS / VM)

Paid only if:

• You choose a managed cloud service

For a basic server:

• You can run them yourself
• Completely free software-wise

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PHP 8.2 and Laravel 10+ Compatibility

This setup is fully compatible with:

• PHP 8.2
• Laravel 10
• Laravel 11 and newer

Why?

• Laravel Scout supports PHP 8+
• Typesense and Meilisearch communicate over HTTP
• No PHP extension dependency
• No version lock-in

You are safe long-term.

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“Is This Production Ready?”

Yes. This stack is production-proven.

What production-ready means here:

• Stable APIs
• Predictable behavior
• Can handle thousands of concurrent users
• Actively maintained
• Used in real businesses

The only difference between a beginner and a mature setup is how you deploy it, not the technology itself.

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Using This on a Basic Server (No Docker, No Queues, No Horizon)

This is a very important point, and the answer is practical.

Without Docker

No problem.

• Both engines run as a single binary/service
• Can be started via system service
• Laravel connects via HTTP

Without Queues

Still works.

• Indexing happens synchronously
• Create/update actions take slightly longer
• Search queries remain fast

This is acceptable for early-stage and medium traffic.

Without Horizon

Not required.

• Horizon is monitoring, not a requirement
• Later you can use Supervisor + queue worker

Conclusion:
You can start today on a basic server.

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Typesense vs Meilisearch — Honest Comparison

Choose Typesense if:

• Filters are core to your UX
• You have many combinations (country + city + specialization)
• Sorting matters a lot
• You want predictable performance as data grows

Choose Meilisearch if:

• You want the easiest setup
• Your filters are simpler
• You want quick results with minimal tuning
• You are early-stage

My recommendation for your use case

Because you emphasized:

• Filtering
• Sorting
• Performance
• Long-term stability

Typesense is the better fit.

Meilisearch is excellent, but Typesense aligns more closely with your requirements.

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Backend Search Strategy (Very Important)

You asked:

Should I load all data once or call backend every time?

Correct answer:

Always search on the backend.

Why loading everything is bad:

• Slow initial page load
• High memory usage in browser
• Impossible at scale
• Bad mobile experience

Correct modern approach:

• Backend handles search
• Frontend sends parameters
• Results are paginated
• Requests are debounced

This is how all scalable systems work.

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How to Make Backend Search Feel Instant

Even with backend calls, UX can feel instant if you:

1. Debounce input
   • Wait 300–500ms after typing
2. Cancel old requests
   • Only latest query matters
3. Keep old results visible
   • Replace when new results arrive
4. Paginate
   • Never fetch everything
5. Cache popular queries
   • Short TTL (30–60 seconds)

This works beautifully with both Typesense and Meilisearch.

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Recommended Architecture (Microservices Friendly)

Step 1: Create a Search Read Model

Instead of joining multiple tables at runtime:

• Flatten your data
• One document = one searchable entity

Example fields:

• id
• name
• country_id
• state_id
• city_id
• specialization_ids
• rating
• created_at
• searchable_text

Step 2: Index This Model

• Laravel Scout maps model → index
• No joins during search
• Search engine does the heavy lifting

Step 3: Search API

One clean endpoint:

• q (text)
• filters
• sort
• page
• per_page

Frontend does not care how it’s implemented.

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Why This Will Not Break with 1000s of Users

Because:

• Search traffic does not hit MySQL
• Filters are pre-indexed
• Sorting is pre-computed
• MySQL is reserved for writes
• Search engine is optimized for reads

This separation is the key to scalability.

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Final Recommendation (Clear and Honest)

For your situation:

• PHP 8.2
• Laravel 10+
• Microservices
• Heavy filtering
• Basic server today
• Long-term growth planned

Best choice:

Laravel Scout + Typesense

Safe alternative:

Laravel Scout + Meilisearch

Both are:

• Free (self-hosted)
• Production-ready
• Scalable
• Compatible with your stack

Typesense simply aligns better with your filter-driven UX and future scale.