Elasticsearch vs Supabase Vector / other Postgres-hosted vectors: what AI actually recommends
The same buying questions, run after run, to ChatGPT, Claude, Gemini, and Perplexity: the record of which of these two they name first. No opinions, no scores we invented: what the models said.
AI currently favors Elasticsearch. Ahead in 1 of 1 shared category on consensus rank.
That is the latest close, not a verdict for all time. The model-by-model board below shows where they agree, where they split, and how both brands moved.
At the latest close, Elasticsearch leads 1 and Supabase Vector / other Postgres-hosted vectors leads 0 across the 1 category they both appear in.
Beyond this pairing, Elasticsearch is ranked in 2 categories; Supabase Vector / other Postgres-hosted vectors is ranked in 1 category. The board below is the shared slice, where the four models place these two side by side.
The record, category by category.
Consensus rank · latest close- #13ElasticsearchNew entry at the last closespread 10Gemini#9
- #16Supabase Vector / other Postgres-hosted vectorsNew entry at the last closespread 10PPLX#10
On consensus rank, Elasticsearch leads here, #13 to Supabase Vector / other Postgres-hosted vectors's #16. 7 to 6 on the 0-100 score. Every model that separates the two ranks Elasticsearch ahead. Elasticsearch is new to the board at this close.
What the models actually said.
The ranking is the answer; these are the words behind it. Every quote is from a recorded model answer — follow the category to read it whole.
Elasticsearch
Elasticsearch — Best when search itself is a core product surface and you need mature lexical search, structured filtering, aggregations, and hybrid retrieval in the same engine—not just a RAG chunk store.
ChatGPT
Supabase Vector / other Postgres-hosted vectors
Supabase Vector / other Postgres-hosted vectors: A pragmatic choice for early startups using Supabase or managed Postgres, giving you decent vector capabilities with very low operational overhead and a familiar SQL-centric workflow.
Perplexity
Where the models split.
Across the 1 category Elasticsearch and Supabase Vector / other Postgres-hosted vectors share, the models line up cleanly in 0 and split in the 0 that remain.
Model by model, Gemini is Elasticsearch's strongest backer, placing it ahead in 1 of the 1; Perplexity leans the other way, favoring Supabase Vector / other Postgres-hosted vectors in 1.
- ChatGPTsplit 0-0
- Claudesplit 0-0
- Geminifavors Elasticsearch 1-0
- Perplexityfavors Supabase Vector / other Postgres-hosted vectors 1-0