DigitalOcean Managed Databases vs Neon
Zero of fourteen models named DigitalOcean Managed Databases first on the direct prompt; zero named Neon. DigitalOcean Managed Databases was named by eleven of the fourteen models and Neon by eleven and DigitalOcean Managed Databases carries 16 labels and Neon 20, so the shares are not directly comparable.
Named in one category this edition.
Named in one category 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
DigitalOcean Managed DatabasesFirst choices, of fourteen modelsNeon
Across every category in the November 2026 Edition, DigitalOcean Managed Databases and Neon were named in the same answer thirty times, of the 55 answers naming DigitalOcean Managed Databases and the 71 naming Neon. In those answers Neon took the first choice seven times and DigitalOcean Managed Databases seven.
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 4.20 | | | | | ||
| 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 | |
DigitalOcean Managed Databases Neon first choice named as an alternative argued againstblank: not namedEach cell is one answer, DigitalOcean Managed Databases on the left and Neon on the right.The direct prompt
Neither was the first choice, one was named
1 of 14 modelsThe answer put something else first and named one of the two as an alternative.Neither was named
13 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
DigitalOcean Managed Databases10%#3 of 8Neon7%#4 of 8DigitalOcean Managed Databases8%#6 of 11Neon4%#7 of 11DigitalOcean Managed Databases0%#– of 8Neon0%#– of 8What the models said about DigitalOcean Managed Databases
Every negative label with a quote, up to three, then the highest-weighted positives, up to three. Four of five in this category shown.
“scaling limits, higher relative costs at volume, and less enterprise-grade SLAs make them riskier for mission-critical apps” Grok 4.20 · negative prompt · soft negative
“DigitalOcean Managed Databases is often the best default: it offers managed PostgreSQL and MySQL with predictable pricing starting around $15/month” Perplexity Sonar · budget prompt · first choice
“DigitalOcean Managed Databases (for PostgreSQL or MySQL) is often the best overall choice.” Grok 4.20 · budget prompt · first choice
“Best for Predictable Flat-Rate Pricing: DigitalOcean Managed Databases” Gemini 3.5 Flash · budget 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. Five of six in this category shown.
“can be attractive depending on your architecture, but I'd be more cautious for core production systems” GPT-5.4 mini · paraphrase prompt · soft negative
“These are rising for mid-sized B2B but less "enterprise battle-tested" than the big three.” Grok 4.20 · paraphrase prompt · soft negative
“If you're just starting out: Use Neon (free tier) or Supabase (free tier).” Kimi K2 · budget prompt · first choice
“Go with Supabase or Neon if you are building a new web app” Qwen 3.7 Flash · budget prompt · first choice
“consider Neon instead: its Postgres pricing is usage-based with no monthly minimum, and it has a free tier” GPT-6 Luna · budget prompt · alternative
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.