How this works
How we research providers
Transparent methodology beats mysterious rankings. Here's exactly how pricing data is collected, what the provider profiles cover, and what we deliberately don't pretend to measure.
Pricing data
- Prices are observed directly from each provider's pricing page
- Every snapshot is dated (Observed as of YYYY-MM-DD) — we don't claim prices are permanent
- Where providers use non-USD currencies (€), we note both the local price and an approximate USD equivalent
- Entry prices are for the smallest practical plan — not artificially stripped-down tiers
- Hidden costs (backups, IPv4, snapshots, setup fees) are called out separately on each profile
Provider profiles
- Each profile covers: who it fits, why people choose it, pricing, regions, hidden costs, good/bad fit scenarios, and a direct comparison to 1–2 competitors
- Profiles are written from a buyer's perspective — not a vendor's
- Region coverage lists specific cities, not vague "Asia-Pacific" buckets
- Profiles are updated when pricing or product structure changes significantly
What VPSLocate focuses on
Practical, developer-facing VPS providers — the kind you actually compare when building real projects. Vultr, Linode, Hetzner, OVHcloud, Contabo, and similar platforms.
This site exists to help developers and small teams make faster, better-informed decisions. We focus on: pricing clarity, region fit, operational friction, and real trade-offs.
What this site deliberately skips
AWS, Azure, and GCP are not part of this site's scope. They solve a different class of problem — enterprise scale, compliance, managed service breadth — and comparing them to Hetzner or Vultr would confuse, not clarify.
We also don't publish fake universal rankings. A provider that's great for EU hosting might be a poor choice for Asia-Pacific workloads. Context matters.
Core principles
- Date every data point — no eternal "from $X" claims
- Separate observed facts from editorial opinion
- Document provider quirks and operational friction, not just spec sheets
- Be honest when sample size or data is limited
- Buyer decision support first — SEO optimization second