SQLite vs. MS Access: Resolving Character Range Pattern Matching in LIKE Queries

Understanding SQLite’s Pattern Matching Limitations for Character Ranges

Issue Overview: Incompatibility of Character Range Syntax in LIKE Queries

The core challenge arises when migrating SQL queries from Microsoft Access 97 to SQLite3, specifically involving pattern matching with character ranges. In MS Access, the LIKE operator supports bracket notation ([a-e], [abcde], [^xz]) to define ranges of characters to match or exclude. For example:

• WHERE f LIKE '%[a-e]%' matches any text containing characters between a and e.
• WHERE f LIKE '%[^xz]%' excludes entries containing x or z.

In SQLite, however, the LIKE operator does not recognize bracket syntax for character ranges. Instead, SQLite’s LIKE only supports two wildcards:

1. % (matches zero or more characters).
2. _ (matches exactly one character).

When executing the same MS Access-style LIKE queries in SQLite, the bracket expressions are treated as literal characters. For instance, LIKE '%[a-e]%' will search for the exact substring [a-e] in column f, not for characters within the a to e range. This discrepancy leads to queries returning no results, even when data exists that should logically match the intended pattern.

The user’s application must support both SQLite and MS Access 97 databases, necessitating a unified approach to handle pattern-matching syntax across these systems. The goal is to replicate MS Access’s behavior in SQLite while maintaining compatibility with legacy Access databases.

Possible Causes: Divergent Pattern Matching Implementations

Three primary factors contribute to the mismatch in query results between MS Access and SQLite:

1. Syntax Differences Between LIKE Implementations
   MS Access extends the ANSI SQL LIKE operator with non-standard syntax for character ranges ([a-e]) and exclusions ([^xz]). SQLite adheres strictly to standard LIKE behavior, which lacks these extensions. Consequently, bracket expressions in SQLite are interpreted literally rather than as range specifiers.

2. Case Sensitivity and Collation
   MS Access defaults to case-insensitive comparisons for LIKE queries, whereas SQLite’s LIKE is case-insensitive only for ASCII characters when using the default BINARY collation. This difference can further complicate cross-database compatibility if the application does not explicitly handle case sensitivity.

3. Misuse of GLOB as a Substitute
   SQLite’s GLOB operator supports Unix-style pattern matching, including bracket ranges ([a-e]) and negation ([^xz]). However, GLOB uses * and ? as wildcards (instead of % and _) and is case-sensitive by default. Attempting to use GLOB as a drop-in replacement for LIKE without adjusting wildcards or collation will fail.

Troubleshooting Steps, Solutions & Fixes

1. Replacing LIKE with GLOB for Character Range Matching

SQLite’s GLOB operator supports bracket syntax for character ranges and exclusions, making it the closest equivalent to MS Access’s LIKE behavior. However, adjustments are required:

• Wildcard Conversion
  Replace % with * and _ with ? in patterns.
  Example:

  -- MS Access
  SELECT * FROM t WHERE f LIKE '%[a-e]%';
  
  -- SQLite equivalent with GLOB
  SELECT * FROM t WHERE f GLOB '*[a-e]*';
  

• Case Sensitivity Handling
  GLOB is case-sensitive. To replicate MS Access’s case-insensitive matching, apply the COLLATE NOCASE clause:

  SELECT * FROM t WHERE f GLOB '*[a-e]*' COLLATE NOCASE;
  

• Negation Syntax
  Use ^ instead of ! or [^] for exclusion:

  -- Exclude 'x' and 'z'
  SELECT * FROM t WHERE f GLOB '*[^xz]*';
  

2. Implementing Cross-Database Pattern Matching

To maintain compatibility between SQLite and MS Access, the application must dynamically generate queries based on the active database. This involves:

• Database Detection
  Identify the database type at runtime (e.g., via connection properties or metadata).

• Pattern Translation
  Convert bracket ranges and wildcards between LIKE and GLOB syntax. For example:

  def translate_pattern(pattern, db_type):
      if db_type == 'sqlite':
          return pattern.replace('%', '*').replace('_', '?')
      elif db_type == 'access':
          return pattern.replace('*', '%').replace('?', '_')
      return pattern
  

• Unified Case Handling
  Force case-insensitive comparisons in SQLite using COLLATE NOCASE:

  SELECT * FROM t WHERE f LIKE '%abc%' COLLATE NOCASE; -- SQLite
  

3. Advanced Alternatives: Regular Expressions and User-Defined Functions

For complex pattern-matching requirements, consider these approaches:

• SQLite’s REGEXP Operator
  Enable the REGEXP extension (requires compiling SQLite with -DSQLITE_ENABLE_REGEXP) and use POSIX-style regular expressions:

  SELECT * FROM t WHERE f REGEXP '[a-e]'; -- Matches any 'a'-'e'
  

• Custom Collations or Functions
  Create a user-defined function (UDF) to handle MS Access-style pattern matching:

  sqlite3_create_function(db, "access_like", 2, SQLITE_UTF8, NULL, &access_like_udf, NULL, NULL);
  

  SELECT * FROM t WHERE access_like(f, '%[a-e]%'); -- Custom implementation
  

• Hybrid Query Generation
  Use application logic to decompose bracket ranges into multiple LIKE clauses:

  SELECT * FROM t WHERE 
      f LIKE '%a%' OR 
      f LIKE '%b%' OR 
      f LIKE '%c%' OR 
      f LIKE '%d%' OR 
      f LIKE '%e%';
  

Summary of Key Adjustments

By systematically addressing syntax differences, case sensitivity, and cross-database compatibility, applications can achieve consistent pattern-matching behavior across SQLite and MS Access 97.