PostgreSQL Full-Text Search vs Elasticsearch: Performance Comparison and Findings

PostgreSQL Full-Text Search

Most of my projects use the Django web framework with PostgreSQL. PostgreSQL has supported full‑text search (FTS) since 2008, and Django added FTS support via django.contrib.postgres in version 1.10 (2016), making it the fastest and simplest integration option. My findings are:

Cheaper and faster because it requires no additional setup or maintenance.

On a local machine (Razer Blade, 2.4 GHz 6‑core i7) using a GIN index, queries on up to 500,000 rows consistently return results in about 30 ms. Public benchmarks show roughly 30‑50 ms for 1.5 million rows.

Using Trigram can slow queries up to five‑fold.

The current Django integration does not directly support stemming or fuzziness.

Elasticsearch

Elasticsearch is a mature search engine with many libraries for integration with Django and other frameworks. Findings include:

It is optimized for search, but setting up and maintaining the infrastructure can be time‑consuming.

Self‑hosting requires dedicated servers or services, making it more expensive than the PostgreSQL option.

Scaling with growing data is easier, and it supports all common search features such as Trigram, EdgeGram, stemming, and fuzziness.

On the same local hardware, queries on up to 500,000 records consistently return results in about 25 ms; public benchmarks show 5‑30 ms for 1.5 million records.

Comparison Graph

Postgresql vs ElasticSearch performance graph

Conclusion

With each new PostgreSQL release, search response times improve, and the gap with Elasticsearch narrows. Therefore, unless a project expects tens of millions of records or massive data scale, PostgreSQL full‑text search is the best choice.

Terms

Stemming : Reducing a word to its root form so that different variants match during search (e.g., "Referencing", "Reference", "References" all map to "refer").

NGram : A sliding window of characters over a word, producing continuous character sequences of a specified length. Used for partial and middle‑of‑word searches; common types are Trigram and EdgeGram.

Fuzziness : Allows matching of approximate terms, useful for misspellings (e.g., searching for "box" also returns results containing "fox").