# Amazon Aurora vs Neon: which do AI models recommend for managed databases, October 2026

IT AI Recommendation Index, October 2026 Edition, Managed relational databases. Four of fourteen models named Amazon Aurora first on the direct prompt; zero named Neon. Page: https://it-ai-index.com/it-data/managed-relational-databases/amazon-aurora-vs-neon/

| | First-choice share | Rank | Negative rate | Labels | Models naming it |
|---|---|---|---|---|---|
| Amazon Aurora | 12% | #2 of 9 | 21% | 39 | 13 of 14 |
| Neon | 10% | #4 of 9 | 0% | 23 | 10 of 14 |

## The direct prompt, model by model

- GPT-5.4 mini: amazon aurora first (first choices: Amazon Aurora, Amazon RDS) (alternatives: Azure Database for PostgreSQL, Azure SQL Database, Google Cloud SQL)
- Gemini 3.5 Flash: amazon aurora first (first choices: Amazon Aurora) (alternatives: Aiven, AlloyDB for PostgreSQL, Azure SQL Database, Neon)
- Mistral Small: amazon aurora first (first choices: Amazon Aurora) (alternatives: Azure SQL Database, Google Cloud SQL)
- Llama 4 Maverick: amazon aurora first (first choices: Amazon Aurora, Amazon RDS) (alternatives: Ntirety, Rackspace Technology)
- Qwen 3.7 Flash: neither first, one named (first choices: Amazon RDS) (alternatives: Azure Database for SQL Server / PostgreSQL, Neon, Vercel Postgres)
- Kimi K2: neither first, one named (first choices: Amazon RDS) (alternatives: Amazon Aurora, Azure SQL Database, Google Cloud SQL, Neon)
- MiniMax M2.5: neither first, one named (first choices: Amazon RDS) (alternatives: Amazon Aurora, DigitalOcean Managed Databases, Google Cloud SQL)
- GPT-6 Luna: neither first, one named (first choices: Amazon RDS) (alternatives: Amazon Aurora, Azure Database for PostgreSQL, Google Cloud SQL)
- Muse Glimmer 30B: neither first, one named (first choices: Amazon RDS) (alternatives: Amazon Aurora, Azure SQL Database, Google Cloud SQL)
- Claude Haiku 4.5: neither named (first choices: Amazon RDS) (alternatives: Azure SQL Database)
- Perplexity Sonar: neither named (first choices: Amazon RDS) (alternatives: Azure SQL Database, Google Cloud SQL)
- Grok 4.1 Fast: neither named (first choices: Google Cloud SQL) (alternatives: Aiven, Amazon RDS, Azure SQL Database, DigitalOcean Managed Databases)
- DeepSeek V4 Flash: neither named (first choices: Amazon RDS) (alternatives: Azure SQL Database, Google Cloud SQL)
- GLM 4.7 FlashX: neither named (first choices: Google Cloud SQL) (alternatives: Amazon RDS, Azure Database)

## What the models said about Amazon Aurora

- "Experts advise caution or avoidance for production environments where stable performance is critical." (Mistral Small, negative prompt, hard negative)
- "Aurora uses internal optimizations and sometimes proprietary features ... that can make migrating back to standard MySQL/Postgres difficult" (Qwen 3.7 Flash, negative prompt, soft negative)
- "While Aurora is popular, be cautious about: Complex pricing - I/O charges can escalate unpredictably" (Kimi K2, negative prompt, soft negative)
- "a recommended hosted SQL database could be PostgreSQL with a cloud-managed service like AWS Aurora, as it balances capability, cost, and operational simplicity" (Llama 4 Maverick, paraphrase prompt, first choice)
- "Pick AWS RDS/Aurora for broadest engine breadth and ecosystem maturity, and for cloud-native Aurora performance with MySQL/PostgreSQL compatibility." (Muse Glimmer 30B, comparative prompt, first choice)
- "is Amazon Relational Database Service (RDS) or Amazon Aurora, as they are fully managed relational database services" (Llama 4 Maverick, direct prompt, first choice)

## What the models said about Neon

- "Supabase or Neon (both serverless PostgreSQL) stand out as the best managed relational database services" (Grok 4.1 Fast, budget prompt, first choice)
- "or Neon if you have very sporadic usage patterns and want to minimize costs" (Kimi K2, budget prompt, first choice)
- "For a budget-conscious company using PostgreSQL, I'd start with Neon" (GPT-6 Luna, budget prompt, first choice)

Share is the count of first choices across the direct, paraphrase, budget and scale prompts over all fourteen models, for a mid-market B2B company; rank is within the category. Comparisons are drawn for the top eight products in each category. Published under CC BY 4.0; the output is the models' output, and nothing here is a recommendation by the index.