Full-Text Search in SQL: Going Beyond LIKE Queries

If you're looking for smarter ways to search through your database, you're in the right place. In this article, I’ll show you how to use full-text search in SQL to go beyond basic LIKE queries and start writing more powerful, accurate, and efficient searches.

Have you ever written a SQL query using LIKE – something like WHERE name LIKE '%apple%' – and thought, "Okay, this kind of works... but isn't there something more advanced?" You're not the only one. LIKE is great for basic pattern matching, but it's not very smart. It doesn’t understand synonyms, it’s slow on big tables, and it gives you results without any sense of which ones are more relevant. It’s like trying to search a library by scanning every book one at a time.

That’s where Full-Text Search (FTS) comes in. Think of it as giving your SQL queries a major upgrade. FTS makes it possible to search for words and phrases in a way that’s faster, more flexible, and closer to how Google search works.

Instead of looking for an exact string, you can find related words, phrases, or even results ranked by how well they match your search. In this guide, we’ll go step-by-step through what Full-Text Search is, why it’s useful, and how to start using it – even if you’re new to SQL.

Why LIKE Isn't Always Enough

Let’s start with something familiar. If you’ve written any SQL at all, you’ve probably used LIKE to search for text:

SELECT * 
FROM Products 
WHERE ProductDescription LIKE '%bike%';

That query looks for the word "bike" anywhere in the product description. Simple, right? But there’s a catch – several, actually:

Here’s what makes LIKE a bit of a pain:

• Slow on big tables: SQL has to go row by row, checking each one to see if it matches. That can take forever with a large dataset.
• Only finds exact matches: If someone wrote "bicycle" instead of "bike," you’re out of luck.
• Matches inside other words: It’ll also match words that simply contain "bike" – like biker – even if that’s not what you meant.
• No ranking: You get a bunch of matches, but you don’t know which ones are the best.
  

So, LIKE is fine if you’re just getting started or working with small datasets, but it can feel like using a flashlight when what you really need is a spotlight. For a deeper understanding of the LIKE operator and its limitations, check out this article: What Do the Operators LIKE and NOT LIKE Do?.

What is Full-Text Search (FTS)?

Full-Text Search is like an upgrade for your SQL searches. It helps you find relevant results more quickly and accurately.

Imagine this: you're searching a huge product catalog, and you want to find anything related to "cycling." FTS can find "bike," "bicycle," "cycling gear," and even "mountain biking." It’s built to understand words in a smarter way.

Full-Text Search makes searching faster because it relies on special indexes rather than checking every row one by one. It’s also much more intelligent – it understands different word forms and even picks up on slight misspellings or variations.

And the best part? It doesn’t just throw back a list of results – it ranks them so the most relevant ones come first, just like a good search engine would. Think of it like giving your database a pair of reading glasses – suddenly everything becomes clearer and easier to find.

In this article, I’ll be using SQL Server to walk you through Full-Text Search examples, but don’t worry – the concepts apply to other databases too. MySQL supports full-text search through FULLTEXT indexes, and PostgreSQL comes with built-in full-text capabilities that are powerful and flexible.

Even popular cloud-hosted databases like Amazon RDS and Google Cloud SQL support full-text search depending on the database engine you choose. The syntax may vary a little, but the purpose remains the same: helping you search text smarter and faster, no matter which SQL dialect you're working with.

How to Set Up Full-Text Search in SQL Server

Let’s say you have a Products table with a column called ProductDescription. That’s the text you want to search. Here’s how to get Full-Text Search up and running.

Step 1: Check if Full-Text Search is Installed

Before anything else, let’s make sure your SQL Server has this feature installed:

SELECT SERVERPROPERTY('IsFullTextInstalled') AS IsFullTextInstalled;

If it returns 1, you’re good. If it returns 0, talk to your database admin or check your installation settings.

Step 2: Create a Full-Text Catalog

A catalog is basically a folder where your search indexes are stored.

CREATE FULLTEXT CATALOG ProductCatalog AS DEFAULT;

Think of this like making a new library shelf to hold your indexes.

Step 3: Create a Full-Text Index

Indexes are what make the search fast. Here’s how to create one:

CREATE UNIQUE INDEX UI_Products ON Products(ProductID);

Now use that unique index to create the full-text index:

CREATE FULLTEXT INDEX ON Products(ProductDescription) 
KEY INDEX UI_Products ON ProductCatalog;

Done! Now your ProductDescription column is searchable with Full-Text tools.

Writing Full-Text Search Queries

Now for the fun part – using the new tools. Let’s go over a few common examples.

1. Search for an Exact Phrase

Want to find products that mention “mountain bike” as a phrase?

SELECT * 
FROM Products 
WHERE CONTAINS(ProductDescription, '"mountain bike"');

When you surround your search terms with double quotes in a CONTAINS query, you’re telling SQL to look for that exact phrase – the words in that exact order, right next to each other. So, when you search for "mountain bike," it won’t match rows that only mention “bike” or “mountain” separately, or ones where those words are far apart in the text. It’s a way to say, “Only show me results that have this full phrase, exactly as I wrote it.”

2. Search for Related Words

Let’s say you type in “cycling equipment,” but your product descriptions don’t use those exact words. FREETEXT will still help you find close matches:

SELECT * 
FROM Products 
WHERE FREETEXT(ProductDescription, 'cycling equipment');

This approach is especially useful when you're not sure exactly how something is worded in the database. It looks at the general meaning of the words you provide and tries to find similar concepts, not just exact matches. This makes your searches feel more natural and less strict, almost like using a search engine instead of a rigid filter.

3. Rank the Results by Relevance

Want to know which results match best? Use CONTAINSTABLE for that:

SELECT 
  p.ProductID, 
  p.ProductDescription, 
  ft.RANK 
FROM CONTAINSTABLE(Products, ProductDescription, 'bike') AS ft 
JOIN Products AS p 
ON ft.[KEY] = p.ProductID 
ORDER BY ft.RANK DESC;

You’ll see a column called RANK that shows how relevant each match is. The higher the number, the better the match.

4. Search for Words That are Close Together

Want “mountain” and “bike” to appear near each other (but not necessarily side by side)?

SELECT * 
FROM Products 
WHERE CONTAINS(ProductDescription, 'NEAR((mountain, bike), 5)');

This means SQL will look for cases where the word "mountain" appears close to the word "bike" in the text – within five words, to be exact. It doesn’t matter if there are a few words in between, as long as they’re relatively near each other. This type of search is especially helpful when the exact phrasing isn’t consistent but the keywords are used in close context.

When Should You Use Full-Text Search?

Full-Text Search is the right choice when you're dealing with large amounts of unstructured text, such as product descriptions or customer reviews.

It’s especially helpful if you’re looking for more than just exact word matches – for example, when you want the database to understand related terms or variations. Plus, it gives you the ability to sort your search results by relevance, so the most useful information appears first instead of being buried in a long list.

Real-Life Examples:

• Online stores: Customers searching for items using everyday language.
• Support teams: Looking through past tickets or knowledge bases.
• Docs or blogs: Finding key topics across long text entries.

Tips for Better Performance

Full-Text Search can feel like a magic wand when you're searching through lots of text – it's fast, it's flexible, and it's way more accurate than LIKE. But like any powerful tool, it's most effective when you know how to use it properly. You still need to think about what you're searching, how often your data changes, and whether your setup matches your needs.

In short, Full-Text Search will do the heavy lifting, but you’ll still want to guide it in the right direction to get the best results.

1. Only Index What You Actually Search

When setting up Full-Text Search, it’s tempting to index every column “just in case.” But resist the urge – indexing comes with overhead, and it’s best to only apply it to columns that users will actually search. For instance, a column full of internal IDs doesn’t need a full-text index. Focus on fields like descriptions, titles, comments, or reviews, where text-based searches make sense.

2. Keep Your Indexes Updated

A full-text index is only as good as the data it represents. If your table data changes frequently – say, you regularly update product descriptions or add new records – then you need to refresh your index to reflect those changes. You can manually do this with the command:

ALTER FULLTEXT INDEX ON Products START FULL POPULATION;

Better yet, schedule regular updates to keep everything in sync without having to remember each time.

3. Use Stopwords and Synonyms

Sometimes, searches can get bogged down by overly common words. That’s where stopwords come in – they help SQL ignore filler words like “the,” “and,” or “a” that don’t add value to your search.

You can also create synonym lists so that words like “bike” and “bicycle” are treated as equivalent, giving your users better results even if they use different terms than what’s stored in the database.

Why This Matters and What You Should Do Now

Full-Text Search is a game-changer when it comes to working with large volumes of text in SQL. It transforms the way you query data by making searches faster, more flexible, and a whole lot smarter than basic string-matching methods like LIKE.

Compared to the traditional LIKE operator, it gives you so much more: smarter matching, faster searches, and the ability to rank results based on how relevant they are. It’s not just about finding words – it’s about finding the right words quickly and efficiently, even when your data is massive or your users search with unpredictable terms.

As long as you set it up correctly, keep your indexes updated, and understand when to use each query type, Full-Text Search can make your applications feel modern and responsive.

If you’re ready to take the next step, do the Advanced SQL track to build on what you’ve learned here. Or, if you're just starting your journey, explore the SQL Basics to get a solid foundation. Start applying Full-Text Search today – it’s one of those features that’s easy to learn, fun to use, and incredibly powerful once you see what it can do.