Tantivy

8 reviews

It is closer to Apache Lucene than to Elasticsearch or Apache Solr in the sense it is not an off-the-shelf search engine server, but rather a crate that can be used to build such a search engine. Companies like Element, Humanfirst, and Nuclia have used Tantivy to unleash the horse-powers in their search queries. There are many ways to use Tantivy. Tantivy can be run in the browser with a WASM file. For Ruby-lovers, Tantiny offers close Ruby bindings for Tantivy . Lastly, you can install Python bindings in Tantivy-Py repo. Features of Tantivy include, but are not limited to: - Full-text search - Configurable tokenizer (stemming available for 17 Latin languages with third party support for Chinese (tantivy-jieba and cang-jie), Japanese (lindera, Vaporetto, and tantivy-tokenizer-tiny-segmenter) and Korean (lindera + lindera-ko-dic-builder) - Fast (check out the 🐎 ? benchmark ? 🐎) - Tiny startup time (<10ms), perfect for command-line tools - BM25 scoring (the same as Lucene) - Natural query language (e.g. (michael AND jackson) OR "king of pop") - Phrase queries search (e.g. "michael jackson") - Incremental indexing - Multithreaded indexing (indexing English Wikipedia takes < 3 minutes on my desktop) - Mmap directory - SIMD integer compression when the platform/CPU includes the SSE2 instruction set - Single valued and multivalued u64, i64, and f64 fast fields (equivalent of doc values in Lucene) - &[u8] fast fields - Text, i64, u64, f64, dates, and hierarchical facet fields - LZ4 compressed document store - Range queries - Faceted search - Configurable indexing (optional term frequency and position indexing) - JSON Field - Aggregation Collector: range buckets, average, and stats metrics - LogMergePolicy with deletes - Searcher Warmer API - Cheesy logo with a horse (obviously an amazing feature) Non-features include: Distributed search is out of the scope of Tantivy, but if you are looking for this feature, check out Quickwit. It is our search engine, built on top of Tantivy.

Quickwit

0 reviews

Quickwit is the next-gen log management & analytics platform to manage petabytes of logs. We have decoupled compute and storage to allow businesses to scale independently and according to their needs. It is a highly reliable & cost-efficient alternative to Elasticsearch. Built by and built for teams to ingest, index with an embedded UI, and analyse logs with Quickwit. Ingested logs can be investigated on an object storage with sub-second queries. Features include, but are not limited to: - Index data persisted on object storage - Ingest JSON documents with or without a strict schema - Aggregation API Elasticsearch compatible - Runs on a fraction of the resources: written in Rust, powered by the mighty tantivy - Works out of the box with sensible defaults - Optimized for multi-tenancy. Add and scale tenants with no overhead costs - Distributed search - Cloud-native: Kubernetes ready - Add and remove nodes in seconds - Decoupled compute & storage - Sleep like a log: all your indexed data is safely stored on object storage (AWS S3...) - Ingest your documents with exactly-once semantics - Kafka-native ingestion - Search stream API that notably unlocks full-text search in ClickHouse AWS S3, PostgreSQL, Kubernetes, Kafka, Amazon Kinesis, Ceph, and Minio are some of the tools that integrate with Quickwit.