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Solr

673
539
+ 1
125
Sphinx

268
241
+ 1
27
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Solr vs Sphinx: What are the differences?

What is Solr? An open source enterprise search server based on Lucene search library, with XML/HTTP and JSON APIs, hit highlighting, faceted search, caching, replication etc. 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.

What is Sphinx? Open source full text search server, designed from the ground up with performance, relevance (aka search quality), and integration simplicity in mind. Sphinx 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 Sphinx pretty much as with a database server. A variety of text processing features enable fine-tuning Sphinx for your particular application requirements, and a number of relevance functions ensures you can tweak search quality as well.

Solr and Sphinx can be categorized as "Search Engines" tools.

Some of the features offered by Solr are:

  • Advanced Full-Text Search Capabilities
  • Optimized for High Volume Web Traffic
  • Standards Based Open Interfaces - XML, JSON and HTTP

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

  • Output formats: HTML (including Windows HTML Help), LaTeX (for printable PDF versions), ePub, Texinfo, manual pages, plain text
  • Extensive cross-references: semantic markup and automatic links for functions, classes, citations, glossary terms and similar pieces of information
  • Hierarchical structure: easy definition of a document tree, with automatic links to siblings, parents and children

"Powerful" is the primary reason why developers consider Solr over the competitors, whereas "Fast" was stated as the key factor in picking Sphinx.

According to the StackShare community, Solr has a broader approval, being mentioned in 139 company stacks & 42 developers stacks; compared to Sphinx, which is listed in 38 company stacks and 13 developer stacks.

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Pros of Solr
Pros of Sphinx
  • 35
    Powerful
  • 22
    Indexing and searching
  • 20
    Scalable
  • 19
    Customizable
  • 13
    Enterprise Ready
  • 5
    Apache Software Foundation
  • 5
    Restful
  • 4
    Great Search engine
  • 2
    Security built-in
  • 15
    Fast
  • 7
    Simple deployment
  • 5
    Open source
  • 0
    Lots of extentions

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What is 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.

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 Solr?
What companies use Sphinx?
See which teams inside your own company are using Solr or Sphinx.
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What tools integrate with Solr?
What tools integrate with Sphinx?

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What are some alternatives to Solr and Sphinx?
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.
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.
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 Spark
Spark is a fast and general processing engine compatible with Hadoop data. It can run in Hadoop clusters through YARN or Spark's standalone mode, and it can process data in HDFS, HBase, Cassandra, Hive, and any Hadoop InputFormat. It is designed to perform both batch processing (similar to MapReduce) and new workloads like streaming, interactive queries, and machine learning.
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