Leaderboards · developer tools

Who AI recommends for databases, orms & hosted postgres

136 answers to 39 questions across 5 engines, Oct 13 to Oct 13, 2026.

Share of answers naming each brandTop rankOthers
0% 10% 20% 30% 40% 50% =1 Neon 29% =1 SQLite 24% =1 Drizzle 22% =1 Supabase 22% =1 Prisma 21% =1 pgvector 18% =2 Qdrant 14% =2 SQLAlchemy 14% 3 Pinecone 11% 5 DBeaver 10% =6 Cloudflare D1 9% =6 MongoDB 9% =6 Turso 9% =7 Weaviate 7% =7 Kysely 6%

The bar behind each point is its likely range (95%). Brands whose ranges overlap share a rank (=).

Engine by engine.

The same questions, answered differently.

Gemini (coding)Google AI OverviewsCodexPerplexityPerplexity (coding)
Neon 24% 27% 36% 32% 24%
SQLite 24% 27% 24% 23% 24%
Drizzle 32% 17% 28% 16% 20%
Supabase 16% 33% 20% 26% 12%
Prisma 24% 17% 36% 19% 12%
pgvector 16% 27% 16% 16% 16%
Qdrant 16% 13% 12% 16% 12%
SQLAlchemy 12% 13% 20% 13% 12%
Pinecone 12% 17% 4% 16% 4%
DBeaver 8% 13% 8% 10% 8%
Cloudflare D1 8% 13% 8% 6% 8%
MongoDB 0% 33% 0% 6% 0%

Chat and code disagree.

Developers ask their editor, not just a chatbot. The same questions, asked both ways.

About the coding lane
BrandChatCodingGap
Neon30%28% -1
SQLite25%24% -1
Drizzle16%27% +10
Supabase30%16% -13
Prisma18%24% +6
pgvector21%16% -5
Qdrant15%13% -1
SQLAlchemy13%15% +2
Pinecone16%7% -10
DBeaver12%8% -4

How it's measured.

We ask each engine the category's questions as a buyer would, read every answer, and count which brands it names. The last 90 days are pooled; each answer counts once. A board is published once it covers most of the category's questions.

Rates carry a 95% range. A brand's rank counts only the brands clearly ahead of it, so close calls tie.

Full methodology · All leaderboards

Where does your brand rank?

One field. A report you can share.

https://
Free, no signup, about two minutesor open the demo