String Similarity Checker
Compare two strings and calculate similarity. Levenshtein distance and similarity percentage.
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💡 Use cases:
• Typo detection • Plagiarism check • Fuzzy matching • DNA sequence comparison
About String Similarity Checker
Compare any two strings and get detailed similarity metrics: Levenshtein edit distance (minimum number of insertions, deletions, and substitutions to transform one string to the other), normalized similarity percentage (0–100%), longest common substring, and Jaro-Winkler similarity. Useful for typo detection, duplicate detection, fuzzy search calibration, and plagiarism checking.
All processing happens entirely in your browser using modern web APIs. Nothing is uploaded to our servers — your data stays local and private. Free to use forever, with a Pro plan for power users who want an ad-free experience and API access.
Common use cases
- Detecting typos in user input by comparing against a known-good string
- Measuring similarity between search query and product names for fuzzy matching
- Checking whether two strings are likely duplicates in data cleaning
- Calibrating a fuzzy search threshold (what similarity % counts as a match)
- Comparing two versions of a file name or identifier for change detection
How it works
Levenshtein distance uses dynamic programming: builds a (m+1) × (n+1) matrix where each cell represents the edit distance of the first i characters of string A to the first j characters of string B. The similarity percentage is 1 - (distance / max(len(A), len(B))). Jaro-Winkler additionally rewards matching characters in the same relative positions and rewards common prefixes.