Google Cloud SQL vs Neon
Two of fourteen models named Google Cloud SQL first on the direct prompt; zero named Neon. Google Cloud SQL was named by fourteen of the fourteen models and Neon by ten and Google Cloud SQL carries 66 labels and Neon 23, so the shares are not directly comparable.
Named in one category 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
Google Cloud SQLFirst choices, of fourteen modelsNeon
Across every category in the October 2026 Edition, Google Cloud SQL and Neon were named in the same answer fifty-four times, of the 186 answers naming Google Cloud SQL and the 78 naming Neon. In those answers Neon took the first choice twelve times and Google Cloud SQL four.
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 | | | | | | |
Google Cloud SQL Neon first choice named as an alternative argued againstblank: not namedEach cell is one answer, Google Cloud SQL on the left and Neon on the right.The direct prompt
Google Cloud SQL first, Neon not the choice
2 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
10 of 14 modelsThe answer put something else first and named one of the two as an alternative.Neither was named
2 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
Google Cloud SQL16%#3 of 8Neon10%#5 of 8Google Cloud SQL10%#3 of 9Neon10%#4 of 9Google Cloud SQL9%#4 of 8Neon0%#– of 8What the models said about Google Cloud SQL
Every negative label with a quote, up to three, then the highest-weighted positives, up to three. Six of eight in this category shown.
“extended support is paid, and Cloud SQL automatically enrolls EOL-version instances. Check the exact engine version and upgrade dates before committing.” GPT-6 Luna · negative prompt · soft negative
“it has the same class of cautions as other DBaaS offerings: you should check pricing, scaling model, maintenance control...” Perplexity Sonar · negative prompt · soft negative
“Less ideal for global/multi-region strong consistency writes.<br>- Scaling not as elastic for extreme loads.” Grok 4.1 Fast · negative prompt · soft negative
“I'd recommend considering Amazon RDS (Relational Database Service) or Google Cloud SQL as your primary options” GLM 4.7 FlashX · paraphrase prompt · first choice
“The top managed relational database services are Amazon RDS, Google Cloud SQL, Azure SQL Database” Perplexity Sonar · comparative prompt · first choice
“Amazon RDS or Google Cloud SQL offer the best balance of features, scalability, and reliability” Claude Haiku 4.5 · paraphrase 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.