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Comparing open source
search engines
Richard Boulton
@rboulton
richard@cnav.co.uk
Search Engine?
Document oriented database
Inverted index
Ranking / weighting algorithm
Lucene
Java
Apache License
Low-level: Java API
Lucene Family
Solr: “REST-like” XML/JSON API
ElasticSearch: REST API
… and many commercial engines
Xapian
C++
GPLv2
Low-level: C++ API
Python/Ruby/PHP/Perl/Java bindings
Xapian
C++
GPLv2
Low-level: C++ API
Python/Ruby/PHP/Perl/Java bindings
Partiality
Risk
Xapian Family
Omega: Indexer + CGI interface
Flax: REST API
Xappy: Python wrapper
Sphinx
C++
GPLv2
SQL-like API
Others
Riak Search
Terrier
MySQL Fulltext
PostgreSQL FTS
Redis
Whoosh
Logos
Document model
Lucene, Xapian:
List of terms
Solr, Sphinx:
Fields in a predefined fixed schema.
Flax, Xappy:
Fields, with associated modifiable schema.
ElasticSearch:
Fields, document types, free schema.
Updates
Lucene, Xapian + families:
Dynamic updates
Use batches for fastest updates
Sphinx:
No updates to existing indexes
(“Realtime indexing” in beta with SQL API)
Data structures
Lucene:
Hash based segments
Heirarchical merge
Xapian:
B-tree, transactional
Scaling / replication
● All engines allow searches across databases
● Allows sharding
● All engines allow replication
● Allows spreading load and high availability
● Had difficulty with Sphinx
● Elastic search does it completely transparently
Commercial Support
Lucene: Lucid Imagination, Sematext, …
Xapian: Oligarchy Ltd, Flax, me
Sphinx: Sphinx Technologies Inc
● Lucene / Solr community – revolting (they say)
● Xapian – quieter, but steadily growing
● Sphinx – popular amongst relational database
users (apparently)
Community

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