← AI Recommendation IndexOpen Data · Rolling 4-week window

Kubernetes vs PostgreSQL

A fact-by-fact comparison of Kubernetes and PostgreSQL — sourced and dated — plus the part no generic comparison shows: which one AI assistants actually recommend more, engine by engine.

Measured by Orbatormethodology owner Henrik Tellewindow ends Sep 5, 2026

What AI recommends — by engine

Recommendation share = the % of sampled AI answers, over a 4-week rolling window, that recommend each product. Higher is better.

CLAUDE

Kubernetes

2%

PostgreSQL

2.4%

GEMINI

Kubernetes

3%

PostgreSQL

4%

GROK

Kubernetes

7.7%

PostgreSQL

7.2%

CHATGPT

Kubernetes

3.4%

PostgreSQL

2.9%

PERPLEXITY

Kubernetes

2.1%

PostgreSQL

2%

The facts — sourced & dated

kubernetes.io

Features

  • Automated rollouts and rollbacksSource · Verified Sep 5, 2026
  • Service discovery and load balancingSource · Verified Sep 5, 2026
  • Storage orchestrationSource · Verified Sep 5, 2026
  • Secret and configuration managementSource · Verified Sep 5, 2026
  • Automatic bin packingSource · Verified Sep 5, 2026
  • Batch executionSource · Verified Sep 5, 2026
  • Self-healingSource · Verified Sep 5, 2026
  • Horizontal scalingSource · Verified Sep 5, 2026
  • Vertical scalingSource · Verified Sep 5, 2026
  • IPv4/IPv6 dual-stackSource · Verified Sep 5, 2026
postgresql.org

Features

  • reliabilitySource · Verified Sep 5, 2026
  • performanceSource · Verified Sep 5, 2026
  • feature robustnessSource · Verified Sep 5, 2026
  • object-relational database systemSource · Verified Sep 5, 2026
  • reliability, feature robustness, and performanceSource · Verified Sep 5, 2026

Kubernetes vs PostgreSQL — FAQ

Does AI recommend Kubernetes or PostgreSQL more?

PostgreSQL is recommended more often: it appears in 3.2% of sampled AI answers versus 3.1% for Kubernetes, measured across the live AI engines over a rolling 4-week window.

Which AI engines were used to compare Kubernetes and PostgreSQL?

Recommendation share is measured on CLAUDE, GEMINI, GROK, CHATGPT, PERPLEXITY using neutral, buyer-shaped prompts (no product names), aggregated over a 4-week rolling window. See the methodology for prompt design and sample sizes.

Own one of these products? Claim your profile to keep its facts accurate.

Recommendation share and entity resolution follow the Index methodology. Facts are sourced from each vendor's own pages and re-verified periodically. Customer status does not affect measurement. Free to use with attribution to orbator.io.

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