← AI Recommendation IndexOpen Data · Rolling 4-week window

Node-RED vs PostgreSQL

A fact-by-fact comparison of Node-RED 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 6, 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

Node-RED

0.3%

PostgreSQL

2.6%

GEMINI

Node-RED

0.2%

PostgreSQL

3.9%

GROK

Node-RED

0.5%

PostgreSQL

7.2%

CHATGPT

Node-RED

0.3%

PostgreSQL

2.8%

PERPLEXITY

Node-RED

0.2%

PostgreSQL

1.8%

The facts — sourced & dated

nodered.org

Features

  • collect, transform and visualize real-time dataSource · Verified Sep 5, 2026
  • low-code programmingSource · Verified Sep 5, 2026

Platforms

  • DockerSource · Verified Sep 5, 2026
  • BeagleBone BlackSource · Verified Sep 5, 2026
  • ArduinoSource · Verified Sep 5, 2026
  • AndroidSource · Verified Sep 5, 2026
  • Amazon Web ServicesSource · Verified Sep 5, 2026
  • Microsoft AzureSource · Verified Sep 5, 2026
  • Raspberry PiSource · Verified Sep 5, 2026
  • Node.jsSource · Verified Sep 5, 2026
postgresql.org

Features

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

Node-RED vs PostgreSQL — FAQ

Does AI recommend Node-RED or PostgreSQL more?

PostgreSQL is recommended more often: it appears in 3.2% of sampled AI answers versus 0.2% for Node-RED, measured across the live AI engines over a rolling 4-week window.

Which AI engines were used to compare Node-RED 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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