Need advice about which tool to choose?Ask the StackShare community!

Lucene

170
228
+ 1
2
Sphinx

892
299
+ 1
32
Add tool

Lucene vs Sphinx: What are the differences?

Introduction

Lucene and Sphinx are both popular open-source search engines used for information retrieval purposes. While both share some similarities, there are key differences between the two.

  1. Indexing Approach: Lucene uses an inverted index approach to store data, which allows for efficient and fast full-text searching. Sphinx, on the other hand, focuses on real-time indexing and retrieval, making it more suitable for quickly updating data sources.

  2. Scalability and Distributed Searching: Lucene is primarily designed for single-node deployments, and scaling it to support a distributed search infrastructure requires additional development effort. Sphinx, on the other hand, offers built-in support for distributed searching, making it easier to scale across multiple nodes.

  3. Query Languages: Lucene uses a query language based on Boolean operators, where queries can be constructed using logical combinations. Sphinx, however, supports an extended SQL-like query language, making it more familiar and easier to use for developers familiar with SQL syntax.

  4. Supported Document Formats: Lucene is capable of indexing and searching various document formats like text, HTML, PDF, etc., thanks to its analyzers and parsers. Sphinx, while it supports a wide range of document formats, primarily focuses on indexing and searching text-based documents.

  5. Integrations and Language Support: Lucene has extensive integrations with programming languages like Java, Python, and Ruby, making it accessible for developers using these languages. Sphinx, while it also supports multiple programming languages, has stronger integration with PHP, as it was originally developed for PHP-based projects.

  6. Community and Documentation: Lucene has a larger and more active community, resulting in a wider array of resources, forums, and documentation available. Sphinx, while having a smaller community, still has sufficient resources and documentation available for developers to utilize.

In Summary, Lucene and Sphinx differ in their indexing approach, scalability, query languages, supported document formats, integrations, and community size.

Get Advice from developers at your company using StackShare Enterprise. Sign up for StackShare Enterprise.
Learn More
Pros of Lucene
Pros of Sphinx
  • 1
    Fast
  • 1
    Small
  • 16
    Fast
  • 9
    Simple deployment
  • 6
    Open source
  • 1
    Lots of extentions

Sign up to add or upvote prosMake informed product decisions

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 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.

Need advice about which tool to choose?Ask the StackShare community!

What companies use Lucene?
What companies use Sphinx?
See which teams inside your own company are using Lucene or Sphinx.
Sign up for StackShare EnterpriseLearn More

Sign up to get full access to all the companiesMake informed product decisions

What tools integrate with Lucene?
What tools integrate with Sphinx?

Sign up to get full access to all the tool integrationsMake informed product decisions

Blog Posts

What are some alternatives to Lucene and Sphinx?
Solr
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
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).
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.
Hadoop
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.
MongoDB
MongoDB stores data in JSON-like documents that can vary in structure, offering a dynamic, flexible schema. MongoDB was also designed for high availability and scalability, with built-in replication and auto-sharding.
See all alternatives