Best databases for web apps (buyer asking for advice)

We asked 10 models: I'm starting a new web app and need to pick a database. Which would you recommend? Each named its own top 10.

Asked 4 ways: List request · Buyer asking for advice · Search query · Worth paying for?. Share of voice pools every wording.

Agreement between models
76%
Same model, run twice
82%
Different picks
18

When agreement between models is well below a model's agreement with itself, the split reflects real differences in taste rather than randomness.

The consensus

Each cell is the position that model gave the pick; blank means it left the pick off. Click a row for each model's reasoning.

#PickScoreListed byClaude Haiku 5.5GPT-6 LunaGemini 4 ArgonQwen 3.8 FlashDeepSeek V4 ProGLM-5.3Kimi K3MiniMax M3Mistral Large 4Nemotron 3 Ultra

3 lower-scoring picks are not shown; every ballot below lists them in full.

Most divisive

Picks most models listed, at very different positions

Hot takes

Picks that appear on only one ballot

Every ballot

Hover a pick to find it on the other ballots. Marked picks appear on no other ballot.

Claude Haiku 5.5

  1. PostgreSQL
  2. MySQL
  3. SQLite
  4. MongoDB
  5. Redis
  6. Amazon DynamoDB
  7. Cassandra
  8. MariaDB
  9. CockroachDB
  10. Firestore

89% with consensus · 95% self-consistent

GPT-6 Luna

  1. PostgreSQL
  2. MySQL
  3. SQLite
  4. MongoDB
  5. Supabase
  6. CockroachDB
  7. Redis
  8. Microsoft SQL Server
  9. Amazon DynamoDB
  10. Amazon Aurora

87% with consensus · 92% self-consistent

Gemini 4 Argon

  1. PostgreSQL
  2. Supabase
  3. SQLite
  4. MySQL
  5. MongoDB
  6. Redis
  7. Firestore
  8. Amazon DynamoDB
  9. CockroachDB
  10. MariaDB

76% with consensus · 94% self-consistent

Qwen 3.8 Flash

  1. PostgreSQL
  2. MongoDB
  3. MySQL
  4. SQLite
  5. Supabase
  6. Redis
  7. Neon
  8. Amazon DynamoDB
  9. Amazon Aurora
  10. Microsoft SQL Server

86% with consensus · 57% self-consistent

DeepSeek V4 Pro

  1. PostgreSQL
  2. SQLite
  3. MongoDB
  4. Supabase
  5. MySQL
  6. Redis
  7. PlanetScale
  8. Neon
  9. Firestore
  10. Microsoft SQL Server

79% with consensus · 71% self-consistent

GLM-5.3

  1. PostgreSQL
  2. Supabase
  3. MongoDB
  4. MySQL
  5. SQLite
  6. Redis
  7. PlanetScale
  8. Amazon DynamoDB
  9. Neon
  10. Firebase

81% with consensus · 80% self-consistent

Kimi K3

  1. PostgreSQL
  2. MySQL
  3. SQLite
  4. MongoDB
  5. Redis
  6. CockroachDB
  7. PlanetScale
  8. MariaDB
  9. ClickHouse
  10. Elasticsearch

88% with consensus · 87% self-consistent

MiniMax M3

  1. PostgreSQL
  2. MySQL
  3. MongoDB
  4. SQLite
  5. Redis
  6. Supabase
  7. MariaDB
  8. Amazon DynamoDB
  9. Firebase
  10. PlanetScale

97% with consensus · 88% self-consistent

Mistral Large 4

  1. PostgreSQL
  2. MongoDB
  3. Redis
  4. SQLite
  5. MySQL
  6. Supabase
  7. PlanetScale
  8. Firebase
  9. Amazon Aurora
  10. Amazon DynamoDB

81% with consensus · 73% self-consistent

Nemotron 3 Ultra

  1. PostgreSQL
  2. MySQL
  3. MongoDB
  4. Redis
  5. SQLite
  6. Amazon DynamoDB
  7. MariaDB
  8. PlanetScale
  9. Cassandra
  10. Microsoft SQL Server

92% with consensus · 84% self-consistent

Who agrees with whom

Overlap between two models' lists, weighted toward the top · 100 means identical · Color runs from 68 (lightest) to 91 (darkest)

Claude Haiku 5.5GPT-6 LunaGemini 4 ArgonQwen 3.8 FlashDeepSeek V4 ProGLM-5.3Kimi K3MiniMax M3Mistral Large 4Nemotron 3 Ultra
Claude Haiku 5.5877677727091887089
GPT-6 Luna878082787489867279
Gemini 4 Argon768077808874757068
Qwen 3.8 Flash778277818274868579
DeepSeek V4 Pro727880818375778072
GLM-5.3707488828371807876
Kimi K3918974747571867385
MiniMax M3888675867780868191
Mistral Large 4707270858078738177
Nemotron 3 Ultra897968797276859177