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Lucene vs MeiliSearch: What are the differences?


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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Pros of Lucene
Pros of MeiliSearch
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    Great long tail search results
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    Fast responses to online chat

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What is Lucene?

Lucene Core, our flagship sub-project, provides Java-based indexing and search technology, as well as spellchecking, hit highlighting and advanced analysis/tokenization capabilities.

What is MeiliSearch?

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.

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What companies use MeiliSearch?
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What tools integrate with Lucene?
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What are some alternatives to Lucene and MeiliSearch?
Solr is the popular, blazing fast open source enterprise search platform from the Apache Lucene project. Its major features include powerful full-text search, hit highlighting, faceted search, near real-time indexing, dynamic clustering, database integration, rich document (e.g., Word, PDF) handling, and geospatial search. Solr is highly reliable, scalable and fault tolerant, providing distributed indexing, replication and load-balanced querying, automated failover and recovery, centralized configuration and more. Solr powers the search and navigation features of many of the world's largest internet sites.
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).
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.
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.
The Apache Hadoop software library is a framework that allows for the distributed processing of large data sets across clusters of computers using simple programming models. It is designed to scale up from single servers to thousands of machines, each offering local computation and storage.
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