Amazon RDS vs Neon
Ten of fourteen models named Amazon RDS first on the direct prompt; zero named Neon. Amazon RDS was named by fourteen of the fourteen models and Neon by ten and Amazon RDS carries 70 labels and Neon 23, so the shares are not directly comparable.
Named in two categories this edition.
Named in two categories this edition.
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; every quote names the model and the prompt it came from. Both figures come from the managed relational databases page.
By framing
Amazon RDSFirst choices, of fourteen modelsNeon
Across every category in the October 2026 Edition, Amazon RDS and Neon were named in the same answer fifty-eight times, of the 189 answers naming Amazon RDS and the 78 naming Neon. In those answers Neon took the first choice eleven times and Amazon RDS thirteen.
Every model, every framing
| Model | Direct | Paraphrase | Comparative | Budget-constrained | Scale-constrained | Negative |
|---|---|---|---|---|---|---|
| Claude Haiku 4.5 | | | | | | |
| GPT-5.4 mini | | | | | | |
| Gemini 3.5 Flash | | | | | | |
| Perplexity Sonar | | | | | | |
| Grok 4.1 Fast | | | | | | |
| Mistral Small | | | ||||
| DeepSeek V4 Flash | | | | | | |
| Llama 4 Maverick | | | | | ||
| Qwen 3.7 Flash | | | | |||
| Kimi K2 | | | | | | |
| GLM 4.7 FlashX | | | | | | |
| MiniMax M2.5 | | | | | | |
| GPT-6 Luna | | | | |||
| Muse Glimmer 30B | | | | | | |
Amazon RDS Neon first choice named as an alternative argued againstblank: not namedEach cell is one answer, Amazon RDS on the left and Neon on the right.The direct prompt
Amazon RDS first, Neon an alternative
10 of 14 modelsNeon was named in the answer but not as the choice, or not at all.Neither was the first choice, one was named
3 of 14 modelsThe answer put something else first and named one of the two as an alternative.Neither was named
1 of 14 modelsThe answer made no first choice from these two in this category.Bold names in an answer are the products the judge labeled a first choice; a model naming several gives each of them that label. The full answer text for every row is in the record.
By buyer segment
Amazon RDS24%#1 of 8Neon10%#5 of 8Amazon RDS45%#1 of 9Neon10%#4 of 9What the models said about Amazon RDS
Every negative label with a quote, up to three, then the highest-weighted positives, up to three. Six of eight in this category shown.
“Some models explicitly recommend avoiding RDS for production core systems unless absolutely necessary.” Mistral Small · negative prompt · hard negative
“are cautious with AWS RDS SQL Server for point-in-time restore expectations and with any RDS engine for globally distributed strong-consistency writes” Muse Glimmer 30B · negative prompt · soft negative
“It is widely used and legitimate, but multiple sources note that it can carry premium instance pricing, hidden ancillary costs” Perplexity Sonar · negative prompt · soft negative
“Amazon RDS, for example, supports MySQL, PostgreSQL, MariaDB, SQL Server, Oracle, and Amazon Aurora, and automates provisioning, patching, backups, and failover.” Llama 4 Maverick · comparative 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
“The top managed relational database services are Amazon RDS, Google Cloud SQL, Azure SQL Database, and Oracle Autonomous Database” Perplexity Sonar · comparative prompt · first choice
What the models said about Neon
Every negative label with a quote, up to three, then the highest-weighted positives, up to three. Three of four in this category shown.
“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
Comparisons are drawn for the top eight products in each category, each against each. The output is the models' output; nothing here is a recommendation by the index.