Lévis, Canada
Server infrastructure for Real Estate & Property Businesses in Lévis
What Real Estate & Property Businesses actually need from a server is predictable performance under load, and enough headroom to grow into. For a medium Real Estate & Property business in Lévis that is about Single Core, 8 GB of memory and 80 GB of storage on VPS.
- ✓ 5 infrastructure tiers
- ✓ Sized for your workload, not a plan name
- ✓ Same price in all 24 locations
Estimated from fibre distance, not measured from Lévis. Your real figure depends on your connection and route, and lands inside this range.
Choose the infrastructure for your workload
Three sizes of business, each sized from an assumed traffic figure rather than a measured one. If you know your own numbers, tell us and the estimate changes with them.
Small Real Estate & Property
1–10 people · ~5,000 visits a month
On request
Shared Hosting
- Single Core
- 4 GB RAM
- 40 GB storage
About 0.5 requests a second at peak, holding roughly 1.4 GB of working data.
Configure this build →Medium Real Estate & Property Most likely here
11–50 people · ~50,000 visits a month
$97.40 USD USD
per month · VPS
- Single Core
- 8 GB RAM
- 80 GB storage
- Managed
About 5.4 requests a second at peak, holding roughly 4 GB of working data.
Configure this build →Large Real Estate & Property
51+ people · ~500,000 visits a month
$296.05 USD USD
per month · VDS
- 4 Cores
- 24 GB RAM
- 250 GB storage
- Managed
About 54.0 requests a second at peak, holding roughly 16 GB of working data.
Configure this build →These figures are assumptions stated out loud, not predictions about your business. Memory, cores and disk can all be raised on the same server later, usually within the hour, with no rebuild and no new IP address — so starting one size below the estimate is normally the cheaper mistake.
Which tiers suit Real Estate & Property Businesses
Including the ones that do not, and why — that is usually the more useful half.
| Infrastructure | Verdict | Why |
|---|---|---|
| Shared Hosting Managed space on a shared server | Workable | Workable for a single small property or practice, though a shared database is the first thing to strain when bookings cluster. |
| VPS Flexible virtual infrastructure with full root access | Recommended | A VPS handles a booking engine and its database comfortably, with predictable performance when enquiries spike. |
| VDS Virtual server with resources pinned to you alone | Recommended | Pinned resources matter here: a reservation that times out at the payment step is a booking you never see. |
| Dedicated Server An entire physical server, configured to your specification | Workable | Right once you are running several properties, or a property management system alongside the public site. |
| Bare Metal Physical compute for sustained, demanding workloads | Not this one | Reservation workloads are database-bound rather than compute-bound, so the extra physical capacity goes unused. |
Real Estate & Property Businesses workloads you can host
- Property listings
- Search & filtering
- Lead capture & CRM
- Document management
- Tenant portal
- Media galleries
Real Estate & Property in Lévis, business by business
These are not the same workload. Sized at the medium band, here is what each one actually needs.
| Business | Build | Tier | What decides it |
|---|---|---|---|
| Real Estate Agencies | 1 vCPU · 8 GB · 500 GB | VPS | Listings are mostly photographs, and they are republished to portals every time anything changes. |
| Property Management | 2 vCPU · 24 GB · 150 GB | VDS | Rent day and statement day are the two dates the system exists for; the rest of the month is maintenance ticke... |
| Commercial Property | 2 vCPU · 32 GB · 350 GB | VDS | Leases are long, complex documents and the service-charge calculation is the annual piece of real arithmetic. |
| Property Developers | 1 vCPU · 8 GB · 700 GB | VPS | Marketing runs on large renders long before there is anything to photograph. |
| Rental Management | 1 vCPU · 8 GB · 400 GB | VPS | Condition reports are photographic evidence, kept for the length of the tenancy and the dispute window after i... |
| Real Estate Portals | 4 vCPU · 64 GB · 1500 GB | VDS | Map-bounded search over a live inventory is the expensive query, and everybody runs it on the same evenings. |
| Property Valuation | 4 vCPU · 48 GB · 450 GB | VDS | A valuation is defensible only if the comparable evidence behind it is retrievable years later. |
| Facility Management | 4 vCPU · 48 GB · 700 GB | VDS | Building sensors report continuously, so the system is ingesting long after the maintenance team has gone home... |
Where your server runs
All 24 locations cost the same, so pick whichever sits closest to the people who will actually use the server.
Lévis is closest to New York. Every marker costs the same per month.
Show all 24 locations and distances from Lévis ▾
| Location | Distance | Est. round trip |
|---|---|---|
| Americas · 9 locations | ||
| New York, United States | 444 miles | 11–21 ms |
| Toronto, Canada | 454 miles | 11–22 ms |
| Chicago, United States | 879 miles | 21–42 ms |
| Atlanta, United States | 1,136 miles | 27–55 ms |
| Miami, United States | 1,536 miles | 37–74 ms |
| Dallas, United States | 1,658 miles | 40–80 ms |
| Seattle, United States | 2,357 miles | 57–114 ms |
| Los Angeles, United States | 2,583 miles | 62–125 ms |
| Santa Clara, United States | 2,636 miles | 64–127 ms |
| Europe, Middle East & Africa · 8 locations | ||
| London, United Kingdom | 3,099 miles | 75–150 ms |
| Amsterdam, The Netherlands | 3,270 miles | 79–158 ms |
| Madrid, Spain | 3,300 miles | 80–159 ms |
| Frankfurt, Germany | 3,486 miles | 84–168 ms |
| Stockholm, Sweden | 3,512 miles | 85–170 ms |
| Milan, Italy | 3,671 miles | 89–177 ms |
| Bucharest, Romania | 4,378 miles | 106–211 ms |
| Tel Aviv, Israel | 5,309 miles | 128–256 ms |
| Asia-Pacific · 7 locations | ||
| Tokyo, Japan | 6,426 miles | 155–310 ms |
| Delhi NCR, India | 6,874 miles | 166–332 ms |
| Mumbai, India | 7,364 miles | 178–356 ms |
| Kolkata, India | 7,476 miles | 180–361 ms |
| Hong Kong, China | 7,649 miles | 185–369 ms |
| Singapore | 9,096 miles | 220–439 ms |
| Sydney, Australia | 10,067 miles | 243–486 ms |
Distances are from Lévis. Round trips are estimated from fibre distance, not measured — the figure your users see depends on where they are.
Real Estate & Property Businesses in Lévis
The closest of our 24 data centres to Lévis is New York, about 444 miles away. Choosing the closest data centre is the cheapest performance improvement available, and it costs nothing extra.
Lévis has a population of about 143,414, which is why the medium build above is the one most likely to fit a Real Estate & Property business here — though the other two are a click away if it does not. Local time is America/Toronto, so routine maintenance and backups are scheduled against your overnight rather than ours.
Data stays in the jurisdiction you choose, which matters if you are working to PIPEDA. Pricing is quoted in CAD, and the figure is the same wherever the machine physically sits.
Network reach from Lévis
Estimated from fibre distance rather than measured, and stated as a range. Your own access network decides the rest.
| Data centre | Distance from Lévis | Estimated round trip |
|---|---|---|
| New Yorkamericas | 444 miles | 11–21 ms |
| Torontoamericas | 454 miles | 11–22 ms |
| Chicagoamericas | 879 miles | 21–42 ms |
Lévis sits in Quebec, and every one of our 24 locations costs the same — so the only thing worth optimising is which of them your users are closest to. At the medium size assumed above, that is roughly 116,667 requests a day crossing that link.
Real Estate & Property Businesses hosting in Lévis — FAQs
What size server does a Real Estate & Property business in Lévis, QC need?
Where would the server for my Lévis, QC business actually run?
Is a VPS enough for Real Estate & Property Businesses, or do we need a dedicated server?
Can you host property listings for us?
Can we start smaller and grow?
Other industries in Lévis
Same city, different workload.
Real Estate & Property Businesses hosting nearby
The same workload, in the nearest cities.