PostgreSQL vs MySQL Decision Tool
Deterministic fit scoring and a cost worksheet from your own numbers — no vendor prices, no sponsored ranking.
At a glance
PostgreSQL vs MySQL Decision Tool scores your workload against a fixed, documented weight table and compares monthly costs from your own quotes. It recommends the better fit from your answers — for a JSON-heavy, geospatial, extension-first team it scored PostgreSQL 90.0 vs MySQL 63.5 — and asserts no vendor prices.
100% Private Decision Math
Your answers and your quoted prices stay in your browser. Nothing is uploaded — the scoring and cost model run locally.
Workload-fit questionnaire
Each answer contributes fixed 0–10 points per engine; category score = points ÷ 10 × weight. Weights sum to 100 — identical answers always give identical scores. No benchmarks, no LLM verdicts.
Your cost worksheet (same data size, two quotes)
Paste the rates from your own quotes below. The pre-filled numbers are editable arithmetic illustrations — never vendor quotes, and the tool asserts no vendor prices.
Worked example loaded. Review the static tables below, or press “Score & compare”.
Worked example — fit scores for the default answers
| Category (weight) | PostgreSQL points → score | MySQL points → score |
|---|---|---|
| JSON / document data (20) | 10 pts → 20.0 | 6 pts → 12.0 |
| Geospatial needs (15) | 10 pts → 15.0 | 4 pts → 6.0 |
| Extensions (15) | 10 pts → 15.0 | 5 pts → 7.5 |
| Team experience (10) | 6 pts → 6.0 | 10 pts → 10.0 |
| Read/write profile (15) | 8 pts → 12.0 | 8 pts → 12.0 |
| Replication / HA (15) | 8 pts → 12.0 | 8 pts → 12.0 |
| Licensing stance (10) | 10 pts → 10.0 | 4 pts → 4.0 |
| Weighted total (100) | 90.0 — recommended fit | 63.5 |
Score per category = points ÷ 10 × weight. Answers scored with fixed tables — nothing about your ranking is influenced by commission or sponsorship (this page is unmonetized).
Worked example — cost worksheet at 250 GB data
| Meter | PostgreSQL path ($60 base, $0.115/GB-mo, $15 backup) | MySQL path ($45 base, $0.10/GB-mo incl. 100 GB, $12 backup, $120 ops) |
|---|---|---|
| Data size | 250.00 GB | 250.00 GB |
| Base | $60.00 | $45.00 |
| Storage overage | $28.75 (250.00 GB over) | $15.00 (150.00 GB over) |
| Backup | $15.00 | $12.00 |
| Ops estimate | $0.00 | $120.00 |
| Monthly total | $103.75 — cheaper by $88.25 | $192.00 |
Formula per path: total = base + max(0, data GB − included GB) × $/GB-month + backup + ops estimate. Break-even: the PostgreSQL path is cheaper below ~6,133.33 GB of data and the MySQL path above it, holding every other input fixed. All rates are user inputs; no vendor prices are asserted.
Why Use This PostgreSQL vs MySQL Decision Tool?
How to Use PostgreSQL vs MySQL Decision Tool
Answer the fit questionnaire
Pick your workload type, whether you need geospatial and extensions, your team's engine experience, your scale profile, replication needs and licensing stance.
Enter your cost inputs
Type data size in GB and each path's base monthly price, storage rate and included GB, backup and ops estimates — your own quotes; the pre-filled numbers are editable illustrations.
Read the verdict and break-even
Compare the weighted fit scores, the monthly totals, the cheaper option and the data-size break-even; copy a summary of the whole comparison.
JSON API team choosing an engine at 250 GB data
The engine scores the questionnaire against fixed weight tables (weights sum to 100) and computes each path's monthly total = base + max(0, data GB − included GB) × $/GB-month + backup + ops, then solves the linear crossing of the two totals over data size.
Fit: JSON-heavy API, geospatial needed, extensions important, team from MySQL, typical web writes, async replication, avoid Oracle-controlled core. Cost: 250 GB data; PostgreSQL path $60 base, $0.115/GB-mo, $15 backup, $0 ops; MySQL path $45 base, $0.10/GB-mo incl. 100 GB, $12 backup, $120 ops.
PostgreSQL fit 90.0 vs MySQL 63.5 -> recommendation PostgreSQL; PostgreSQL $103.75/mo vs MySQL $192.00/mo (PostgreSQL cheaper by $88.25/mo); break-even ~6,133.33 GB — MySQL becomes cheaper above it, holding all other inputs fixed.
Technical Specifications & Engine Details
| Specification | Details |
|---|---|
| Decision model | Weighted questionnaire: category score = answer points (0-10) / 10 x weight; weights sum to 100 — json_document 20, geospatial 15, extensions 15, team_experience 10, scale_profile 15, replication_ha 15, licensing 10 |
| Cost model | Monthly total = base + max(0, data GB - included GB) x $/GB-month + backup + ops estimate |
| Break-even axis | Data size (GB) — where the two monthly totals cross |
| Prices asserted by this tool | None. Every rate is a user input; paste your own current quotes. |
| Execution mode | 100% client-side in browser (no uploads, no network calls) |
| Browser requirements | Modern browser with JavaScript and HTML5 APIs enabled |
100% Client-Side Privacy Guarantee
Questionnaire answers and quote values stay on your device. The fit scoring and cost math run client-side in memory; zero data is transmitted or stored.
Frequently Asked Questions
Is PostgreSQL better than MySQL?
How does the fit score work?
How much does each database cost?
Can I move an existing MySQL schema to PostgreSQL?
Is my data sent anywhere?
Methodology
Fit scores use fixed weights across the questionnaire categories; cost totals use the storage, backup and operations rates you enter.
Last updated .