What is the project about?

Tantivy is a fast, full-text search engine library written in Rust. It's designed to be a core component for building search engine capabilities into applications, similar to Apache Lucene.

What problem does it solve?

It provides the building blocks for creating powerful search functionality without the overhead of a full-fledged search engine server. It offers a flexible and efficient way to index and search large amounts of text data. It addresses the need for fast, local search capabilities within applications.

What are the features of the project?

• Full-text search with configurable tokenizers (including stemming for multiple languages and third-party support for CJK languages).
• BM25 scoring (like Lucene).
• Natural query language and phrase query support.
• Fast and efficient indexing (multithreaded).
• Incremental indexing.
• Various field types: text, numeric (i64, u64, f64), dates, IP addresses, booleans, facets, and byte arrays.
• Compressed document storage.
• Range queries and faceted search.
• JSON Field.
• Aggregation Collector.
• LogMergePolicy with deletes.
• Searcher Warmer API.

What are the technologies used in the project?

• Rust: The core programming language.
• SIMD (SSE2): For integer compression (where available).
• Compression Libraries: LZ4, Zstd for document storage.
• Mmap: For memory-mapped file access.

What are the benefits of the project?

• Speed: High performance for both indexing and searching.
• Efficiency: Low memory and CPU usage.
• Flexibility: Highly configurable indexing and search options.
• Embeddability: Designed to be integrated directly into applications.
• Small Footprint: Tiny startup time, suitable for command-line tools.
• Extensibility: Supports custom tokenizers.

What are the use cases of the project?

• Building custom search engines.
• Adding search functionality to applications (desktop, web, or command-line).
• Creating specialized search tools (e.g., code search, log analysis).
• Powering search within larger systems (as a component).
• Any application requiring fast, local, full-text search.