Full-Text Search vs Elasticsearch: Performance Comparison

I get asked this question a lot: "Should I use MySQL full-text search or Elasticsearch?" My answer is always the same: it depends on how many records you have and how important search quality is to your product.

Let me break down the real differences.

MySQL full-text search

MySQL has had full-text search for years. You create a FULLTEXT index and use MATCH...AGAINST in your queries.

CREATE FULLTEXT INDEX idx_search ON products(name, description);

SELECT *, 
    MATCH(name, description) AGAINST('wireless headphones' IN NATURAL LANGUAGE MODE) AS score
FROM products
WHERE MATCH(name, description) AGAINST('wireless headphones' IN NATURAL LANGUAGE MODE)
ORDER BY score DESC
LIMIT 20;

In Laravel:

$products = Product::whereFullText(['name', 'description'], $query)
    ->get();

This works. For a dataset under 100,000 records, it is fast enough. Setup takes 5 minutes.

But it has real limitations. No typo tolerance — "headphons" returns nothing. Limited relevance tuning. No faceted search. Minimum word length restrictions (words shorter than 4 characters are ignored by default).

Elasticsearch

Elasticsearch is a dedicated search engine. It stores a copy of your data optimized specifically for searching.

For a dataset of 1 million records:

• MySQL full-text: 200-800ms per query
• Elasticsearch: 5-30ms per query

That is a 10-50x speed difference. But more importantly, Elasticsearch handles typos, ranks results intelligently, supports autocomplete, and enables faceted search ("show me all blue shoes under $100 with 4+ stars").

The real cost of Elasticsearch

Elasticsearch is not free in terms of complexity. You need to:

• Run and maintain an Elasticsearch cluster (or pay for a managed service)
• Keep your Elasticsearch index in sync with your database
• Handle the case where they get out of sync
• Learn the Elasticsearch query language

For a small team or a startup, this overhead might not be worth it.

My decision framework

Use MySQL full-text search if:

• Your dataset is under 100,000 records
• Search is a secondary feature, not the core of your product
• You want to keep your infrastructure simple
• Typos are not a major concern

Use Elasticsearch if:

• Your dataset is large or growing fast
• Search is a primary feature (e-commerce, job boards, content platforms)
• You need typo tolerance
• You need faceted search or autocomplete
• Your users expect Google-quality search

Start with MySQL. When users start complaining that search is not finding what they expect, that is your signal to add Elasticsearch.