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  1. Stackups
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  4. Search Engines
  5. Lucene vs MeiliSearch

Lucene vs MeiliSearch

OverviewComparisonAlternatives

Overview

Lucene
Lucene
Stacks175
Followers230
Votes2
MeiliSearch
MeiliSearch
Stacks125
Followers123
Votes10
GitHub Stars54.3K
Forks2.2K

Lucene vs MeiliSearch: What are the differences?

Introduction

Lucene and MeiliSearch are both search engines that are used to index and search through large amounts of data. While they share some similarities, there are several key differences between the two.

  1. Indexing Process: Lucene uses an inverted index to store and retrieve data, which involves creating a document index from the input text. On the other hand, MeiliSearch uses a custom indexing algorithm which allows for real-time updates and faster indexing process.

  2. Query Language: Lucene uses a query language called QueryParser, which allows for complex queries using Boolean operators and wildcards. MeiliSearch, on the other hand, provides a simpler query language that supports full-text search and filtering but lacks the advanced features of Lucene's query language.

  3. Scalability: Lucene is highly scalable and can handle large volumes of data by distributing the index across multiple shards. MeiliSearch, on the other hand, is designed for smaller to medium-sized datasets and does not have built-in support for sharding or distributed indexing.

  4. Customization: Lucene provides a high level of customization options, allowing users to tweak various parameters to optimize search performance. MeiliSearch, on the other hand, prioritizes simplicity and ease of use, providing fewer customization options but requiring less configuration.

  5. Real-time Updates: MeiliSearch is designed to handle real-time updates efficiently, allowing for instant search updates as soon as new data is added or modified. Lucene, on the other hand, requires the index to be rebuilt or updated manually after any changes to the data.

  6. Language Support: Lucene supports a wide range of programming languages including Java, C#, Python, and more. MeiliSearch currently has official SDKs for several programming languages including Python, JavaScript, and Ruby, with more being developed.

In summary, Lucene and MeiliSearch differ in terms of their indexing process, query language, scalability, customization options, real-time updates, and language support. They cater to different use cases, with Lucene being more suitable for large-scale applications requiring advanced search capabilities, while MeiliSearch is geared towards smaller projects that prioritize simplicity and real-time updates.

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CLI (Node.js)
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Manual

Detailed Comparison

Lucene
Lucene
MeiliSearch
MeiliSearch

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 a powerful, fast, open-source, easy to use, and deploy search engine. The search and indexation are fully customizable and handles features like typo-tolerance, filters, and synonyms.

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)
Search as-you-type experience (answers < 50ms); Full-text search; Typo tolerant (understands typos and spelling mistakes); Supports Kanji; Supports Synonym; Easy to install, deploy, and maintain; Whole documents returned; Highly customizable; RESTfull API
Statistics
GitHub Stars
-
GitHub Stars
54.3K
GitHub Forks
-
GitHub Forks
2.2K
Stacks
175
Stacks
125
Followers
230
Followers
123
Votes
2
Votes
10
Pros & Cons
Pros
  • 1
    Fast
  • 1
    Small
Pros
  • 1
    Great long tail search results
  • 1
    Fast responses to online chat
  • 1
    Facet search
  • 1
    Easy to deploy
  • 1
    Useful defaults
Integrations
Solr
Solr
Java
Java
No integrations available

What are some alternatives to Lucene, MeiliSearch?

Elasticsearch

Elasticsearch

Elasticsearch is a distributed, RESTful search and analytics engine capable of storing data and searching it in near real time. Elasticsearch, Kibana, Beats and Logstash are the Elastic Stack (sometimes called the ELK Stack).

Algolia

Algolia

Our mission is to make you a search expert. Push data to our API to make it searchable in real time. Build your dream front end with one of our web or mobile UI libraries. Tune relevance and get analytics right from your dashboard.

Typesense

Typesense

It is an open source, typo tolerant search engine that delivers fast and relevant results out-of-the-box. has been built from scratch to offer a delightful, out-of-the-box search experience. From instant search to autosuggest, to faceted search, it has got you covered.

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.

Amazon CloudSearch

Amazon CloudSearch

Amazon CloudSearch enables you to search large collections of data such as web pages, document files, forum posts, or product information. With a few clicks in the AWS Management Console, you can create a search domain, upload the data you want to make searchable to Amazon CloudSearch, and the search service automatically provisions the required technology resources and deploys a highly tuned search index.

Amazon Elasticsearch Service

Amazon Elasticsearch Service

Amazon Elasticsearch Service is a fully managed service that makes it easy for you to deploy, secure, and operate Elasticsearch at scale with zero down time.

Manticore Search

Manticore Search

It is a full-text search engine written in C++ and a fork of Sphinx Search. It's designed to be simple to use, light and fast, while allowing advanced full-text searching. Connectivity is provided via a MySQL compatible protocol or HTTP, making it easy to integrate.

Azure Search

Azure Search

Azure Search makes it easy to add powerful and sophisticated search capabilities to your website or application. Quickly and easily tune search results and construct rich, fine-tuned ranking models to tie search results to business goals. Reliable throughput and storage provide fast search indexing and querying to support time-sensitive search scenarios.

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.

Swiftype

Swiftype

Swiftype is the easiest way to add great search to your website or mobile application.

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