ripgrep 15.2: The gitignore-aware search tool that outruns grep on real codebases

What problem ripgrep solves and who it is for

ripgrep solves the problem of searching source code and large text files quickly while respecting the filtering rules developers already have in place. The README positions it as a line-oriented search tool that recursively searches the current directory for a regex pattern. Its default behavior skips hidden files, binary files, and anything matched by .gitignore, .ignore, or .rgignore. That means a typical search does not return vendored dependencies, build artifacts, or minified binaries, which are common noise in code search. The intended audience is developers who work in repositories with many files, especially those who have used The Silver Searcher, ack, or plain grep and found them too slow or too noisy. It is also aimed at users who want a single tool that works consistently on Windows, macOS, and Linux, since the README states first class support for all three platforms with binary downloads for every release.

The mechanics: regex engine, filtering, and parallelism

ripgrep's speed comes from several design choices visible in the README and repository layout. It uses Rust's regex engine, which compiles patterns to a finite automaton and performs literal optimizations. The README's benchmarks show that patterns with literal substrings, like 'Sherlock', are much faster than patterns without any literals, such as '[A-Za-z]{30}'. This indicates the engine's optimization strategy relies on finding literal candidate matches before running the full regex. The filtering mechanism is also built into the search process: the tool reads gitignore files and applies them during directory traversal, so it does not waste time opening files it will skip. The README mentions that automatic filtering can be disabled with 'rg -uuu', which implies a three-level verbosity flag that progressively ignores more rules. The tool also supports file type filtering via flags like '-tpy' for Python and '-Tjs' to exclude JavaScript, which suggests a built-in mapping of extensions to type names. Parallelism is implied by the performance on multi-core systems, though the README does not detail the thread model. The repository includes a GUIDE.md and FAQ.md, which likely cover the architecture, but those files are not included in the README.

Getting it running: installation and basic commands

The README points to binary downloads for every release on GitHub, which is the simplest path for most users. For package managers, the README links to repology.org, which tracks ripgrep packages across distributions, so you can install via apt, brew, or similar. If you prefer to build from source, the README links to a 'Building' section in the README itself, though the exact commands are not shown in the provided excerpt. The basic usage is straightforward: run 'rg' followed by a pattern, and it searches the current directory recursively. The README gives an example: 'rg -n -w '[A-Z]+_SUSPEND'' to search for uppercase words ending in SUSPEND with line numbers and word boundaries. To search specific file types, you use '-tpy foo' to limit to Python files and '-Tjs foo' to exclude JavaScript. Configuration files are documented in the GUIDE.md, which is linked but not included, so the exact config key syntax is not available here. Shell completions are also documented in the FAQ, but again the details are outside the README.

Performance: what the benchmarks show and what they hide

The README includes several benchmarks on the Linux kernel source tree and a 13GB decompressed file. On the kernel tree, ripgrep took 0.082 seconds for a Unicode search with word boundaries, while git grep took 0.273 seconds and The Silver Searcher took 0.443 seconds. On the single large file, ripgrep was 1.042 seconds versus ugrep's 1.339 seconds and GNU grep's 6.577 seconds. These numbers are specific to the hardware and corpus, and the README itself warns that a single benchmark is never enough. The author also points out performance cliffs: a pattern with two literal words 'Sherlock' and a capital letter caused ugrep to take 28.973 seconds while ripgrep took 1.053 seconds. The most revealing benchmark is the one with no literal optimizations: '[A-Za-z]{30}' took 15.569 seconds for ripgrep, which is still faster than ugrep and GNU grep but shows that ripgrep is not magic. High match counts also flatten differences, as shown by the 'rg the' benchmark where all tools were within a factor of two. The caveat is that these benchmarks are self-reported by the author, so you should treat them as indicative, not as a guarantee for your own files.

A real limitation: binary file skipping and regex syntax differences

ripgrep's default behavior of skipping binary files is a feature for code search but a limitation if you need to search binary formats or log files with null bytes. The README says it automatically skips binary files, and to disable all filtering you need 'rg -uuu', which is a non-obvious flag. If you forget this, you might miss matches in binary files without realizing it. Another limitation is the regex syntax. The README links to the Rust regex crate's syntax documentation, which is not identical to GNU grep's extended regex. The FAQ linked in the README discusses whether ripgrep can truly replace grep, and the title suggests there are caveats. For example, backreferences and lookaround are not supported in the default regex engine, which can break patterns that work in Perl-compatible regex tools. The README also shows that the number of matches can differ: in the kernel benchmark, ack found 2677 lines while ripgrep found 536, which the README attributes to ack's different default behavior, but it highlights that you cannot assume identical results across tools.

Alternatives: ugrep and git grep take different approaches

The most direct alternative is ugrep, which is also a recursive search tool with gitignore support. The README benchmarks show ugrep is consistently slower than ripgrep, but ugrep offers features ripgrep may lack, such as more extensive PCRE2 support and a different set of default filters. The key difference in approach is that ugrep uses a different regex engine and its own filtering logic, which can be faster or slower depending on the pattern. Another alternative is git grep, which is built into Git and works only within a Git repository. git grep respects the index and tracked files, so it does not search untracked files unless you pass flags. That is a fundamental difference: ripgrep searches the filesystem, while git grep searches the Git object database. For users who only need to search tracked files, git grep may be sufficient, but it lacks ripgrep's file type filtering and automatic binary skipping. GNU grep is another alternative for single-file searches, but it does not do recursive search by default and has no gitignore awareness. The README's benchmarks show GNU grep is much slower on Unicode patterns, especially with the UTF-8 locale, which can be a deciding factor for international text.

Maintenance and licensing: what the repository tells us

The repository is actively maintained, with the latest release 15.2.0 pushed on 2026-07-15, roughly a year after 15.0.0. The release cadence of about three releases per year suggests regular feature additions and bug fixes. The project is dual-licensed under MIT or the Unlicense, which is permissive and places minimal restrictions on use. This means you can incorporate ripgrep into proprietary tools without legal friction, though you should still review the license text if you distribute binaries. The README links to a CHANGELOG.md for release history, which is the place to look for breaking changes when upgrading. The project has a user guide and FAQ, which are maintained resources for learning about new flags and behavior changes. The maintenance cost for users is low: since it is a command-line tool, you only need to update the binary when a new release comes out. The build-from-source path is available for those who need custom patches, but the binary downloads are the recommended route. There is no indication of a plugin ecosystem or configuration file format that would require ongoing maintenance, so the upgrade cost is minimal.

Editorial conclusion

Adopt ripgrep if you work in large codebases, value gitignore-aware defaults, and need fast recursive search with Unicode support. Skip it if you require full POSIX grep compatibility or need to search binary content by default, since ripgrep skips binaries and has a different regex syntax. Before adopting, verify your team's regex patterns against ripgrep's syntax, especially if you rely on backreferences or lookaround, and test the -uuu flag if you need to search hidden or ignored files. The 15.2 release is actively maintained, and the dual MIT/Unlicense licensing removes most legal friction, so the main cost is learning the flag differences from grep.

Official sources

1. Official README
2. Project repository
3. Release notes