Sphinx or SOLR: Which Stand-Alone Full-Text Search Server Best Meets My Needs?

Choosing a Stand-Alone Full-Text Search Server: Sphinx vs. SOLR

Problem Overview

When seeking a stand-alone full-text search server that meets specific criteria, such as serving multiple clients, enabling bulk indexing, operating with MySQL on Linux, and offering high performance, developers often encounter three prominent options: Sphinx, ElasticSearch, and Solr.

Comparison of Sphinx and SOLR

• Objectivity: The author acknowledges a bias towards Solr due to personal experience but intends to present an objective comparison.
• Similarities: Both Sphinx and Solr fulfill the specified requirements, boasting high performance and large-scale data indexing capabilities. They also have established user bases and offer commercial support.

• Differences:

  • Licensing: SOLR is Apache2-licensed, while Sphinx is GPLv2-licensed. This distinction has implications for commercial use.
  • Embeddability: Solr can be easily embedded in Java applications.
  • Technology base: Solr is built on Lucene, a widely trusted technology with a vast community.
  • RDBMS integration: Sphinx has tighter integration with RDBMSs, particularly MySQL.
  • Additional features: Solr offers capabilities such as Hadoop integration, proprietary format indexing, spell-checking, facet support, and field collapsing.
  • Indexed content: Sphinx retrieves only document IDs, whereas SOLR can retrieve whole documents.

Alternatives and Considerations

• ElasticSearch: Not discussed in detail, but also a viable option based on Lucene.
• Use Cases: The choice between Sphinx and SOLR should consider factors such as commercial licensing concerns, need for embedded capabilities, integration requirements with specific RDBMSs, and specific feature requirements. Additionally, Solr's integration with Hadoop makes it suitable for distributed applications, and its compatibility with proprietary formats and direct document retrieval capabilities offer additional advantages.

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