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  1. Stackups
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  3. Search
  4. Search Engines
  5. Carrot2 vs Lucene

Carrot2 vs Lucene

OverviewComparisonAlternatives

Overview

Lucene
Lucene
Stacks175
Followers230
Votes2
Carrot2
Carrot2
Stacks7
Followers13
Votes0
GitHub Stars834
Forks218

Lucene vs Carrot2: What are the differences?

Lucene: A high-performance, full-featured text search engine library written entirely in Java. Lucene Core, our flagship sub-project, provides Java-based indexing and search technology, as well as spellchecking, hit highlighting and advanced analysis/tokenization capabilities; Carrot2: An Open Source Search Results Clustering Engine. It organizes your search results into topics. With an instant overview of what's available, you will quickly find what you're looking for.

Lucene and Carrot2 can be categorized as "Search Engines" tools.

Some of the features offered by Lucene are:

  • over 150GB/hour on modern hardware
  • small RAM requirements -- only 1MB heap
  • incremental indexing as fast as batch indexing

On the other hand, Carrot2 provides the following key features:

  • Visualization
  • Clustering
  • Integration

Carrot2 is an open source tool with 377 GitHub stars and 155 GitHub forks. Here's a link to Carrot2's open source repository on GitHub.

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Detailed Comparison

Lucene
Lucene
Carrot2
Carrot2

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 organizes your search results into topics. With an instant overview of what's available, you will quickly find what you're looking for.

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)
Visualization; Clustering; Integration
Statistics
GitHub Stars
-
GitHub Stars
834
GitHub Forks
-
GitHub Forks
218
Stacks
175
Stacks
7
Followers
230
Followers
13
Votes
2
Votes
0
Pros & Cons
Pros
  • 1
    Fast
  • 1
    Small
No community feedback yet
Integrations
Solr
Solr
Java
Java
C#
C#
PHP
PHP
.NET
.NET
Ruby
Ruby
Bing Maps API
Bing Maps API

What are some alternatives to Lucene, Carrot2?

Sphinx

Sphinx

It lets you either batch index and search data stored in an SQL database, NoSQL storage, or just files quickly and easily — or index and search data on the fly, working with it pretty much as with a database server.

MkDocs

MkDocs

It builds completely static HTML sites that you can host on GitHub pages, Amazon S3, or anywhere else you choose. There's a stack of good looking themes available. The built-in dev-server allows you to preview your documentation as you're writing it. It will even auto-reload and refresh your browser whenever you save your changes.

Google

Google

Search the world's information, including webpages, images, videos and more. Google has many special features to help you find exactly what you're looking for.

YugabyteDB

YugabyteDB

An open-source, high-performance, distributed SQL database built for resilience and scale. Re-uses the upper half of PostgreSQL to offer advanced RDBMS features, architected to be fully distributed like Google Spanner.

Searchkick

Searchkick

Searchkick learns what your users are looking for. As more people search, it gets smarter and the results get better. It’s friendly for developers - and magical for your users.

Apache Solr

Apache Solr

It uses the tools you use to make application building a snap. It is built on the battle-tested Apache Zookeeper, it makes it easy to scale up and down.

Qdrant

Qdrant

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.

Weaviate

Weaviate

It is an open-source vector search engine. It allows you to store data objects and vector embeddings from your favorite ML-models, and scale seamlessly into billions of data objects.

AddSearch

AddSearch

We help your website visitors find what they are looking for. AddSearch is a lightning fast, accurate and customizable site search engine with a Search API. AddSearch works on all devices and is easy to install, customize and tweak.

ArangoSearch

ArangoSearch

It is a C++ based full-text search engine including similarity ranking capabilities natively integrated into ArangoDB. It allows users to combine two information retrieval techniques: boolean and generalized ranking retrieval. Search results “approved” by the boolean model can be ranked by relevance to the respective query using the Vector Space Model in conjunction with BM25 or TFIDF weighting schemes.

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