Best databases for web apps (worth paying for?)

We asked 10 models: Which hosted databases are actually worth paying for? 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
35%
Same model, run twice
59%
Different picks
27

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

12 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. Amazon Aurora
  2. Google Cloud Spanner
  3. Neon
  4. Amazon DynamoDB
  5. Supabase
  6. Google Cloud SQL
  7. PlanetScale
  8. Amazon RDS
  9. MongoDB Atlas
  10. Azure SQL Database

33% with consensus · 63% self-consistent

GPT-6 Luna

  1. Amazon Aurora
  2. Google Cloud SQL
  3. Azure SQL Database
  4. MongoDB Atlas
  5. Snowflake
  6. Neon
  7. Supabase
  8. CockroachDB
  9. Amazon DynamoDB
  10. Redis

35% with consensus · 83% self-consistent

Gemini 4 Argon

  1. Supabase
  2. Neon
  3. Amazon RDS
  4. MongoDB Atlas
  5. PlanetScale
  6. CockroachDB
  7. Turso
  8. Upstash
  9. ClickHouse Cloud
  10. Amazon DynamoDB

51% with consensus · 85% self-consistent

Qwen 3.8 Flash

  1. Amazon Aurora
  2. Supabase
  3. PlanetScale
  4. Neon
  5. MongoDB Atlas
  6. Snowflake
  7. Cloudflare D1
  8. CockroachDB
  9. Turso
  10. Fauna

63% with consensus · 61% self-consistent

DeepSeek V4 Pro

  1. Supabase
  2. PlanetScale
  3. MongoDB Atlas
  4. Neon
  5. CockroachDB
  6. Turso
  7. Fauna
  8. Aiven for PostgreSQL
  9. Aiven
  10. Railway

57% with consensus · 84% self-consistent

GLM-5.3

  1. Amazon RDS
  2. MongoDB Atlas
  3. Snowflake
  4. Supabase
  5. PlanetScale
  6. Neon
  7. Google Cloud SQL
  8. Azure SQL Database
  9. BigQuery
  10. Amazon DynamoDB

53% with consensus · 50% self-consistent

Kimi K3

  1. MongoDB Atlas
  2. Amazon Aurora
  3. Supabase
  4. PlanetScale
  5. CockroachDB
  6. PostgreSQL
  7. PostgreSQL on Amazon RDS
  8. Redis
  9. Amazon RDS
  10. Google Cloud SQL

73% with consensus · 25% self-consistent

MiniMax M3

  1. MongoDB Atlas
  2. Supabase
  3. PlanetScale
  4. Redis
  5. Neon
  6. PostgreSQL
  7. PostgreSQL on Amazon RDS
  8. PostgreSQL on managed clouds (RDS/Cloud SQL)
  9. Amazon RDS
  10. Google Cloud SQL

80% with consensus · 44% self-consistent

Mistral Large 4

  1. Snowflake
  2. MongoDB Atlas
  3. PlanetScale
  4. Amazon RDS
  5. Redis
  6. Amazon Aurora
  7. Supabase
  8. Amazon DynamoDB
  9. BigQuery
  10. Databricks

52% with consensus · 53% self-consistent

Nemotron 3 Ultra

  1. MongoDB Atlas
  2. PlanetScale
  3. Amazon RDS
  4. Amazon Aurora
  5. Google Cloud SQL
  6. Azure Database for PostgreSQL
  7. Google Cloud Spanner
  8. Neon
  9. Snowflake
  10. CockroachDB

71% with consensus · 12% self-consistent

Who agrees with whom

Overlap between two models' lists, weighted toward the top · 100 means identical · Color runs from 18 (lightest) to 72 (darkest)

Claude Haiku 5.5GPT-6 LunaGemini 4 ArgonQwen 3.8 FlashDeepSeek V4 ProGLM-5.3Kimi K3MiniMax M3Mistral Large 4Nemotron 3 Ultra
Claude Haiku 5.5532858212434211827
GPT-6 Luna532159203137192731
Gemini 4 Argon282148714637463033
Qwen 3.8 Flash585948563454493435
DeepSeek V4 Pro212071563644563138
GLM-5.3243146343639445749
Kimi K3343737544439724258
MiniMax M3211946495644724654
Mistral Large 4182730343157424651
Nemotron 3 Ultra273133353849585451