Full-Text Search Explained — How It Works + PostgreSQL vs MongoDB vs ElasticSearch vs Apache Solr
In this video we cover Full-Text Search (FTS) from scratch —
what it is, how it works under the hood, and which database
you should actually be using for it.
Here is what we cover:
→ What Full-Text Search is and why it exists
→ The complete FTS pipeline — tokenization, stop word removal,
stemming, and how the inverted index is built
→ How relevance scoring works (BM25, TF-IDF, ts_rank)
→ Query types — exact phrase, boolean, wildcard, fuzzy,
and proximity search
→ Head-to-head benchmark comparison of PostgreSQL, MongoDB,
ElasticSearch, and Apache Solr on 3 million records
→ When to use which database for full-text search
Key findings from the benchmark:
ElasticSearch and Solr are ~100× faster for phrase matching
PostgreSQL surprisingly beats ElasticSearch on boolean AND queries
MongoDB is the slowest in almost every single scenario
PostgreSQL has the fastest data insertion speed
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Resources mentioned in this video:
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https://www.scitepress.org/Papers/202...
https://www.elastic.co/docs/solutions...
https://www.postgresql.org/docs/curre...
https://stackoverflow.com/questions/3...
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Tags:
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#elasticsearch #postgresql #fulltext
#mongodb #apache #solr #invertedindex #BM25
#database #searchengine #searchengineoptimization #searchengineoptimisation #searchenginerankings #tsvector #GINindex
#backenddevelopment #development #databaseengineering #systemdesign