LIKE vs. SEARCH vs. CONTAINS: Understanding Text Search Operators

When working with databases or querying tools, you often need to find specific pieces of text within a dataset. This is where text search operators like LIKE, SEARCH, and CONTAINS come into play. While they all serve a similar purpose — helping you locate text — they work in different ways and are suited for specific scenarios. In this blog, we’ll break down these three operators in simple terms, so you can choose the right one for your task.

LIKE: A Basic Pattern Matching Tool:

The LIKE operator is a simple, yet powerful, tool for matching patterns in text. It’s commonly used in SQL databases. When you use LIKE, you can search for text using wildcard characters.

How It Works:

• Wildcard Characters
• % matches any sequence of characters (zero or more).
• _ matches a single character.

SEARCH: Intelligent and Powerful Text Search

The searchoperator is used in systems with advanced search functionality, like Elasticsearch or modern databases. Unlike like, it’s designed for full-text search, meaning it can analyze large blocks of text and provide intelligent results.

How It Works: search doesn’t rely on simple wildcards. Instead, it uses indexes to quickly locate matches. It also understands the structure of the text, allowing for ranking and filtering results.

CONTAINS: Checking for Exact Matches

The contains operator is straightforward. It checks whether a specific piece of text is present in a field. It’s often used in programming languages or basic database queries.

How It Works: Contains looks for an exact match of the input string.

Performance Comparison

• Fastest: (5.3s) is comparable to LIKE but typically optimized for specific use cases.
• Second Place: LIKE (5.4s), but heavily dependent on the pattern and indexing.
• Slowest: SEARCH (9.3s) due to higher computational costs for advanced

Contains is as efficient as Like in the absence of full-text indexes but generally outperforms it in systems with text indexing.

When deciding which operator to use, consider the following:

1. Dataset Characteristics: If the text fields are indexed for full-text search, Contains is usually the best choice.
2. Query Complexity: For simple patterns, like is faster and easier to implement. For more advanced queries, search is preferred despite its higher computational cost.
3. Index Availability: Both like and contains can benefit from indexing, but SEARCH often requires its own specialized index for optimal performance.

My recommendation : Contains Performs well compared to LIKE in most of the cases which i have tested. All result generated with out search optimization.

• Use like for straightforward pattern matching in well-structured datasets with proper indexing.
• Use search when performing complex text queries requiring ranking, fuzzy matching, or phrase detection.
• Use contains for exact substring searches, particularly in systems optimized for full-text indexing.