Lucene vs Qdrant
Overview
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Detailed Comparison
Lucene Core, our flagship sub-project, provides Java-based indexing and search technology, as well as spellchecking, hit highlighting and advanced analysis/tokenization capabilities. | It is an open-source Vector Search Engine and Vector Database written in Rust. It deploys as an API service providing search for the nearest high-dimensional vectors. With Qdrant, embeddings or neural network encoders can be turned into full-fledged applications for matching, searching, recommending, and much more. |
over 150GB/hour on modern hardware;small RAM requirements -- only 1MB heap;incremental indexing as fast as batch indexing;index size roughly 20-30% the size of text indexed;ranked searching -- best results returned first;many powerful query types: phrase queries, wildcard queries, proximity queries, range queries;fielded searching (e.g. title, author, contents);sorting by any field;multiple-index searching with merged results;allows simultaneous update and searching;flexible faceting, highlighting, joins and result grouping;fast, memory-efficient and typo-tolerant suggesters;pluggable ranking models, including the Vector Space Model and Okapi BM25;configurable storage engine (codecs) | Easy to use API;
Fast and accurate;
Advanced filtering;
Rich data types;
Cloud-native and horizontally scaleable;
Efficient & performant |
Statistics | |
GitHub Stars - | GitHub Stars 26.9K |
GitHub Forks - | GitHub Forks 1.9K |
Stacks 175 | Stacks 52 |
Followers 230 | Followers 20 |
Votes 2 | Votes 0 |
Pros & Cons | |
Pros
| No community feedback yet |
Integrations | |
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