“Best database hosting for Postgres”
Which brands do AI models actually recommend for this developer infrastructure question? We re-run this regularly and track how the answers shift.
6
AI Models
18
Snapshots
80
Brands Detected
54
Sources Cited
66 brands come up when 6 AI models answer “Best database hosting for Postgres”. We re-run this prompt every few days with web search on across ChatGPT, Claude, Gemini, Grok, DeepSeek, and Perplexity.
What AI models recommend
6 models queried · Last scanned Mar 29
Unanimous
6/6 models recommend DigitalOcean
ChatGPT
Claude
DeepSeek
Gemini
Grok
Perplexity| Brand | ChatGPT | Claude | DeepSeek | Gemini | Grok | Perplexity | Total |
|---|---|---|---|---|---|---|---|
 DigitalOcean | 6/6 | ||||||
 Neon | 6/6 | ||||||
 PostgreSQL | 6/6 | ||||||
 Postgres | 6/6 | ||||||
 AWS | 5/6 | ||||||
 Aiven | 5/6 | ||||||
 Google | 5/6 | ||||||
 Google Cloud | 5/6 | ||||||
 SQL | 5/6 | ||||||
 Supabase | 5/6 | ||||||
 AWS RDS | 4/6 | ||||||
 Azure | 4/6 | ||||||
 GCP | 4/6 | ||||||
 Google Cloud SQL | 4/6 | ||||||
 Aurora | 4/6 | ||||||
 Northflank | 3/6 | ||||||
 pgvector | 3/6 | ||||||
 IONOS | 2/6 | ||||||
 Render | 2/6 | ||||||
 SOC 2 | 2/6 | ||||||
 HIPAA | 2/6 | ||||||
 SaaS | 2/6 | ||||||
 Amazon | 2/6 | ||||||
 Git | 2/6 | ||||||
 Next.js | 2/6 | ||||||
 Vertex AI | 2/6 | ||||||
 PostGIS | 2/6 | ||||||
 Koyeb | 2/6 | ||||||
 CLEAR | 1/6 | ||||||
 Google Cloud Platform | 1/6 | ||||||
 Kinsta | 1/6 | ||||||
 Ease | 1/6 | ||||||
 PlanetScale | 1/6 | ||||||
 ScaleGrid | 1/6 | ||||||
 Fortune 500 | 1/6 | ||||||
 GCP Cloud SQL | 1/6 | ||||||
 PostgreSQL 18 | 1/6 | ||||||
 React | 1/6 | ||||||
 Tembo | 1/6 | ||||||
 Vercel | 1/6 | ||||||
 Vercel Postgres | 1/6 | ||||||
 AlloyDB for PostgreSQL | 1/6 | ||||||
 Aurora PostgreSQL | 1/6 | ||||||
 Azure Cosmos DB for PostgreSQL | 1/6 | ||||||
 Azure Database for PostgreSQL Flexible Server | 1/6 | ||||||
 Cloud SQL for PostgreSQL | 1/6 | ||||||
 Crunchy Bridge | 1/6 | ||||||
 Docs | 1/6 | ||||||
 OpenAI | 1/6 | ||||||
 RDS for PostgreSQL | 1/6 | ||||||
 microsoft.com | 1/6 | ||||||
 Firebase | 1/6 | ||||||
 Instaclustr | 1/6 | ||||||
 NetApp | 1/6 | ||||||
 Reddit | 1/6 | ||||||
 reddit.com | 1/6 | ||||||
 CleverCloud | 1/6 | ||||||
 Crunchy Data | 1/6 | ||||||
 ElephantSQL | 1/6 | ||||||
 Heroku Postgres | 1/6 | ||||||
 Hostinger | 1/6 | ||||||
 InMotion | 1/6 | ||||||
 InMotion Hosting | 1/6 | ||||||
 Kamatera | 1/6 | ||||||
 Scalingo | 1/6 | ||||||
 York | 1/6 |
Key Quotes
Claude Sonnet 4.6Claude“🔴 Google Cloud SQL — Best for GCP Ecosystems Google Cloud SQL, Supabase, and IONOS consistently top 2026 rankings for reliability and features.”
DeepSeek V3.2DeepSeek“- Scalability: Both vertical and horizontal scaling should be easy (DigitalOcean, AWS RDS).”
Gemini 3 FlashGemini“Google Cloud SQL: Now features deep integration with Vertex AI, allowing you to run vector searches and model inferences directly within your SQL queries.”
GPT-5ChatGPT“Aiven for PostgreSQL: managed PG across AWS/Azure/GCP with automated encrypted backups and PITR; 99.99% SLA and lots of extensions.”
Grok 4.1 FastGrok“Aiven/Koyeb: 1–5 GB storage, extensions.() Caveat: Free plans often sleep on inactivity and limit concurrency/performance.() Quick Pick: Start with Neon or Supabase for most projects—easy, modern, cost-effective.”
Developer Infrastructure brand rankings
Brands ranked by how many AI models mention them. Trend shows change since the last scan.
Developer Infrastructure brand visibility over time
Track how brand mentions shift across AI models over time.
What changed and when
Every brand addition, removal, and citation change logged with timestamps.
grok-4-1-fast rank changed for Aivengpt-5 started mentioning HIPAAgpt-5 started mentioning Docsgpt-5 started mentioning SOC 2gpt-5 started mentioning PostgreSQLgpt-5 started mentioning microsoft.comgpt-5 stopped mentioning Databricksgpt-5 stopped mentioning Crunchy Datagpt-5 stopped mentioning EDB BigAnimalgpt-5 stopped mentioning AWS RDSWhere AI models get their sources
Domains cited by AI models when answering this prompt, ranked by how many models reference them.
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