Residential vs Datacenter Proxies: Which One for Web Scraping?

You need a proxy for web scraping. There are two real categories. One is cheap and fast and gets blocked half the time. The other costs roughly 10x more per gigabyte and gets through almost everywhere. The choice is rarely about which is "better" in the abstract. It is about which one matches the target site and the scale you are running.

This guide compares datacenter and residential proxies on the dimensions that actually matter when picking a web scraping proxy service in 2026: detection rates, real per-GB pricing, rotation patterns, geo coverage, and total cost when you factor in retries. Real numbers, real code, and a decision framework you can apply to any target site.

Pricing is pulled from public rate cards across the major proxy providers. Detection patterns come from how popular targets actually behave (Amazon, Airbnb, Reddit, eBay). The code samples use Browserbeam's built-in proxy switch.

What you'll learn:

• The actual difference between datacenter and residential proxies (and why the marketing makes it sound bigger than it is)
• Real per-GB pricing for both types from the major proxy providers in 2026
• Which sites you can scrape with cheap datacenter proxies and which ones force residential
• How rotating, sticky session, and static residential (ISP) proxies differ
• A decision framework matching proxy type to target site
• Three real-world scraping use cases with code
• The five most expensive proxy mistakes teams make
• How Browserbeam handles datacenter and residential proxies through a single API parameter

TL;DR: Datacenter proxies are cheap (~$0.40-1 per GB), fast, and work fine on roughly half the public web, including Airbnb, eBay, Wikipedia, and most news sites. Residential proxies cost 5-10x more (~$2-6 per GB) but rotate through real consumer ISP IPs and get past aggressive anti-bot systems on Amazon, Reddit, LinkedIn, Walmart, and most bot-protected SaaS dashboards. Pick datacenter first. Switch to residential only when datacenter requests start getting blocked. Most teams overpay by defaulting to residential everywhere.

What a Web Scraping Proxy Actually Does

Your scraper sends a request. A proxy intercepts it, swaps in a different IP, and forwards it to the target. The target never sees your real address. Simple plumbing.

But which IP the proxy uses is everything. That single fact decides whether your scraper sees the page or a 403.

How a Proxy Sits Between Your Scraper and the Target

Without a proxy, your scraper hammers the target from a single IP. After roughly 50-200 requests, most production sites either rate-limit you, throw a CAPTCHA, or ban the IP outright.

What Sites See When You Use a Proxy

Sites check more than the bare IP. They look at the IP's reputation. Each IP belongs to an Autonomous System Number (ASN), and ASNs are publicly classified. Cloudflare, Akamai, and DataDome all maintain feeds of which ASNs belong to:

• Cloud hosting providers (AWS, GCP, Azure, OVH, Hetzner, DigitalOcean)
• Consumer ISPs (Comcast, Verizon, Vodafone, BT, Deutsche Telekom)
• Mobile carriers (T-Mobile, AT&T, EE, Orange)
• Known proxy services (which they actively reverse-engineer)

A datacenter proxy lives on a hosting provider ASN. A residential proxy lives on a consumer ISP ASN. That ASN classification is the single biggest signal anti-bot systems use.

Why You Almost Always Need One

You need a proxy when at least one of these is true: the site rate-limits per IP, the site geo-blocks content, the site runs an anti-bot system, or you need to make more than a few hundred requests per hour. For anything beyond a hobby script, that covers nearly every real target.

For a deeper look at site-by-site detection patterns, the web scraping in 2026 guide breaks down how each major target behaves.

Datacenter Proxies: How They Work and Where They Win

Datacenter proxies are the workhorse option. Cheap, fast, available in bulk. The IP belongs to a cloud hosting provider (AWS, OVH, Hetzner), not a consumer ISP. Pools range from tens of thousands to a few million IPs, and you pay per gigabyte of traffic or per IP per month. The tradeoff: anti-bot systems know exactly what a hosting ASN looks like.

How They Are Built

Provider buys IP blocks from cloud hosts (AWS, OVH, Hetzner) or operates their own infrastructure. Each request from your scraper enters a rotating endpoint, and the provider picks a fresh IP from the pool. Latency is low because data center peering is excellent. Throughput is high because nothing is bottlenecked by a home internet connection.

Where Datacenter Proxies Win

• Cost. $0.40-1 per GB at the wholesale level. Some providers offer unlimited bandwidth plans because IPs are cheap to acquire.
• Speed. 50-150ms typical proxy round-trip. Often faster than residential by 3-10x.
• Reliability. Datacenter networks rarely drop connections. Residential connections drop constantly because real homes go offline.
• Predictable performance. No "the user behind this IP just rebooted their router" surprises.

Where Datacenter Proxies Lose

• Detection. Cloudflare, DataDome, PerimeterX, and Akamai Bot Manager all tag known hosting ASNs. On aggressively protected sites, the request gets a CAPTCHA or 403 before the page loads.
• IP reputation contagion. When one buyer abuses an IP, every other buyer using that pool inherits the bad reputation.
• Concentrated geography. Datacenter IPs cluster in countries with cheap hosting (US, Germany, Romania, Singapore). Less coverage in places where consumer browsing actually happens.

Bottom line: Start here. Datacenter works on roughly half the public web. Test it first, measure the block rate, and only upgrade when you see real failures. Every dollar spent on residential for a site that datacenter handles is a dollar wasted.

Residential Proxies: How They Work and Where They Win

Residential proxies are the premium option, and the price reflects it. Your traffic routes through a real consumer device on a real ISP connection. The IP looks like any other home broadband customer because it literally is one. Pool sizes reach 10 million to 100 million IPs across nearly every country. Anti-bot systems have a hard time blocking these without catching real users in the crossfire.

How They Are Built

Most residential pools are sourced through SDK partnerships with mobile and desktop apps that opt users into "earn money / get free service" programs. Other pools come from explicit affiliate or VPN exchange networks. The ethics vary wildly by provider — some are transparent about consent, others wave their hands — and the providers that disclose their consent flow most clearly (Bright Data, Oxylabs, Decodo) tend to be the ones serious customers use. If a provider can't explain where their IPs come from, that's a red flag, not a feature.

When you send a request, the provider picks an active peer that matches your country (and sometimes city or ASN) filter, opens a connection through them, and forwards your request. The peer's home ISP forwards it to the target. The target sees a normal residential IP.

Where Residential Proxies Win

• Detection avoidance. Most anti-bot systems will not block consumer ISP traffic by default because doing so blocks legitimate users.
• Geographic coverage. Country and city level targeting in places no datacenter proxy reaches (rural India, secondary cities in Brazil, smaller European countries).
• Pool size. 10M+ IPs means rotation is effectively unlimited and IP reuse is rare across short windows.
• Sticky sessions. Most providers offer 10-30 minute session stickiness through one peer, which matches real human browsing patterns and survives multi-page workflows.

Where Residential Proxies Lose

• Cost. $2-6 per GB retail, depending on volume. A 1 MB page costs roughly $0.002-0.006 in proxy bandwidth alone.
• Latency. 200-800ms round-trip. The peer's home connection is the bottleneck.
• Reliability. Connections drop. Peers go offline. Requests retry. Plan on a 2-5% failure rate even on healthy pools.
• Bandwidth blow-up. Because every byte costs real money, blocking unnecessary resources (images, fonts) suddenly matters a lot.

When do you actually need a web scraping residential proxy? When datacenter fails. Amazon, Reddit, LinkedIn, Walmart, most ticketing sites. If you're getting clean responses with datacenter, stay there. If you're hitting walls, residential is the answer. Just know what you're paying for.

Side-by-Side: Datacenter vs Residential Proxies

If you bookmark one thing from this post, make it this table. It captures every dimension that actually matters when you're staring at two proxy provider checkout pages at 2 AM.

For a quick mental model: datacenter is the express lane on a toll road. Residential is a country road through every town. The express lane is faster and cheaper when it gets you there. The country road is the only option when the express lane is closed.

Rotating, Sticky, and Static: Proxy Rotation Patterns

"Residential" and "datacenter" are about IP type. "Rotating", "sticky", and "static" are about how often the IP changes. Both axes matter, and the marketing tends to mash them together.

Rotating Proxies

Every request comes from a different IP. The provider picks a fresh peer (residential) or fresh datacenter IP for each new connection. This is the default for high-volume scraping where each page is independent: search result lists, sitemap crawls, Google SERP scraping, news indexing.

Both datacenter and residential pools support rotation. The difference is the size of the pool you rotate through. A 10K-IP datacenter pool burns through itself fast; a 50M-IP residential pool effectively never repeats. Rotating residential is the standard answer for "I need to scrape 1M product pages on Amazon and not get blocked".

Sticky Sessions

The same IP holds for a defined window: typically 1, 10, or 30 minutes. This matches real human browsing: when a person logs into a site, navigates through five pages, and submits a form, every request comes from the same residential IP. A sticky session emulates that.

Sticky sessions are essential for: authenticated sessions, multi-step forms, cart and checkout flows, paginated dashboards behind login. Without them, the site sees a "user" whose IP changes every request, which is itself a strong bot signal.

Browserbeam's residential proxy keeps a sticky session for the full lifetime of each browser session (about 30 minutes by default), so logged-in workflows hold a single residential IP without any extra configuration on your side.

Static Residential (ISP Proxies)

Static residential proxies (sometimes branded as "ISP proxies") are dedicated IPs that look residential but live on always-on infrastructure. They combine the detection avoidance of residential with the speed and uptime of datacenter. The catch is they are sold as fixed IPs, not as a rotating pool, and they are priced per IP per month rather than per GB.

When to use static residential / ISP proxies:

• Long-running authenticated sessions where IP changes break the session
• Sneaker, ticketing, and limited-stock automation where consistency matters
• Account warmup workflows for SaaS testing

When not to use them: large-scale scraping where rotation is the whole point.

Quick decision matrix

Pricing in 2026: How Much Each Type Actually Costs

Every proxy provider's marketing page has a big "from $X" that conveniently omits the asterisks. If you plan to buy residential proxies or cheap residential proxies for scraping, the number on the checkout page will look different from the headline. We pulled the actual public pricing as of May 2026 directly from major provider rate cards so you don't have to.

Datacenter proxy pricing

Prices as of May 2026. Excludes VAT where applicable.

Datacenter pricing has fallen sharply since 2023 because the underlying IP supply is cheap. At wholesale rates, $0.40-$1.00 per GB is the realistic range. Webshare sells datacenter proxies per IP with unlimited bandwidth rather than per GB, so the effective cost depends on how much traffic you push through each IP.

Residential proxy pricing

Prices as of May 2026. Excludes VAT where applicable.

Residential pricing scales with volume commits. Pay-as-you-go starts around $4-6/GB at the major providers. At 100+ GB monthly commits, expect $2.50-3.50/GB. Below 50 GB, the price rarely drops below $3.50/GB. The cheapest credible residential pricing in 2026 sits around $2/GB at the 1 TB+ tier from Decodo and Oxylabs.

Bandwidth math: what 1k, 10k, and 100k pages actually cost

A modern e-commerce product page weighs 1-3 MB after JavaScript. A search result page is closer to 0.5-1.5 MB. With image and font blocking enabled, you can typically halve those numbers. Here is the real cost per 1,000 pages at three representative bandwidth levels.

Two takeaways. First, even at 100k pages/month, residential bandwidth alone is rarely the whole bill. The bigger factor is what runs on top: cloud browser runtime, CAPTCHA solving, retry overhead. Second, "rotating proxy unlimited bandwidth" is almost always datacenter. There is no honest unlimited residential offer at consumer prices because the underlying COGS is real.

For Browserbeam's exact credit math, see the billing reference, which spells out the credit-per-MB rates for each proxy kind.

Residential vs Datacenter vs ISP vs Mobile

The "vs" articles pile up because there are really four proxy categories worth knowing. Here is the four-way summary.

Mobile proxies are a niche tool. The IPs are pristine because mobile carriers use carrier-grade NAT and rotate IPs for legitimate users constantly, so anti-bot systems cannot reliably block them without breaking real traffic. Pricing reflects the rarity. For 99% of scraping work, the choice is between datacenter and residential. Mobile is a tool you reach for only after residential fails, which is rare.

Using Proxies in Browserbeam

Browserbeam routes every session through a managed proxy by default. You opt into residential by adding one field to the session create call. The same body works in any of the SDKs.

Don't have an API key yet? Create a free Browserbeam account for a residential proxy free trial with 5,000 credits, no card required. The same residential proxy API handles datacenter and residential through a single parameter.

Default datacenter, with one country pin

# Create the session
SESSION=$(curl -s -X POST https://api.browserbeam.com/v1/sessions \
  -H "Authorization: Bearer YOUR_API_KEY" \
  -H "Content-Type: application/json" \
  -d '{
    "url": "https://books.toscrape.com",
    "proxy": { "kind": "datacenter", "country": "us" }
  }')

echo "$SESSION" | jq '.page.title'

# Close the session
SESSION_ID=$(echo "$SESSION" | jq -r '.session_id')
curl -s -X DELETE "https://api.browserbeam.com/v1/sessions/$SESSION_ID" \
  -H "Authorization: Bearer YOUR_API_KEY"

from browserbeam import Browserbeam

client = Browserbeam(api_key="YOUR_API_KEY")
session = client.sessions.create(
    url="https://books.toscrape.com",
    proxy={"kind": "datacenter", "country": "us"},
)
print(session.page.title)
session.close()

import Browserbeam from "@browserbeam/sdk";

const client = new Browserbeam({ apiKey: "YOUR_API_KEY" });
const session = await client.sessions.create({
  url: "https://books.toscrape.com",
  proxy: { kind: "datacenter", country: "us" },
});
console.log(session.page?.title);
await session.close();

require "browserbeam"

client = Browserbeam::Client.new(api_key: "YOUR_API_KEY")
session = client.sessions.create(
  url: "https://books.toscrape.com",
  proxy: { kind: "datacenter", country: "us" }
)
puts session.page.title
session.close

That is a US-pinned datacenter session. You pay 30 credits per MB of proxy bandwidth, billed per the credit rates. For roughly half of the sites you will scrape, this is enough.

Switching to residential for protected targets

When the target site blocks datacenter (Amazon, Reddit, Walmart, most ticketing platforms), flip the kind field. Everything else stays the same.

session = client.sessions.create(
    url="https://news.ycombinator.com",
    proxy={"kind": "residential", "country": "us"},
)
# ... extract data ...
session.close()

Residential is billed at 300 credits per MB, ten times the datacenter rate, which mirrors the wholesale cost ratio. The session also gets a sticky 30-minute residential IP, so logged-in workflows hold a single peer across multi-step flows.

Country-aware routing with auto

If you scrape across many target countries and want each session pinned to the matching geography, pass country: "auto". Browserbeam reads the URL's TLD and picks a country from the supported pool.

session = client.sessions.create(
    url="https://books.toscrape.com",
    proxy={"kind": "residential", "country": "auto"},
)
# ... extract data ...
session.close()

European ccTLDs that do not have a dedicated endpoint fall through to the EU pool. Unknown TLDs fall through to the global rotating endpoint. The full list of supported countries is in the API docs.

Bring your own proxy

If you have an existing contract with Bright Data, Decodo, or any other vendor, pass a string proxy URL instead. Browserbeam routes the session through it without touching the credit pool for proxy bandwidth.

session = client.sessions.create(
    url="https://books.toscrape.com",
    proxy="http://user:pass@gate.decodo.com:7000",
)
# ... extract data ...
session.close()

This is useful when you have negotiated bulk rates that beat Browserbeam's per-MB pricing or when you need a specific provider for compliance reasons.

Decision Framework: Which Proxy Should You Use?

Here is the shortest decision tree that holds up across hundreds of real scraping targets.

Start with datacenter

Always test datacenter first. It is 10x cheaper per byte, and on lightly-protected sites the success rate is identical to residential. If you can get a clean response with a datacenter proxy, every dollar you spend on residential is wasted.

Sites where datacenter typically works:

• Public records sites
• News, blog, and content sites without aggressive WAFs
• Wikipedia and open knowledge bases
• Real estate and marketplace sites with light protection (Airbnb, Zillow listings, Trulia)
• Most B2B SaaS public-facing pages
• Hacker News, Reddit's public RSS endpoints, Lobsters

For real worked examples, the scrape Airbnb guide and scrape eBay guide both use datacenter and explain why.

Switch to residential when datacenter fails

Symptoms that mean you should switch: 403/429 responses on the first request, CAPTCHAs (DataDome, Cloudflare, hCaptcha) before the page loads, served HTML that is missing the data you need (cloaked content), or block rates above 5% on real traffic.

Sites that almost always need residential:

• Amazon (catalog, search, product pages)
• Walmart, Target, Best Buy
• Reddit (public pages and authenticated)
• LinkedIn (any scraping at all)
• Instacart, DoorDash, ticketing platforms
• Most major banking and financial dashboards

The scrape Amazon guide and scrape Reddit guide show the working residential setups for both.

Use static residential / ISP for account-bound work

If your target keeps you logged in across days or weeks, rotating IPs will eventually trip a "suspicious login" guard. Static residential gives you a fixed, residential-class IP that survives across sessions. Sneaker bots, ticketing, niche SaaS testing.

Promote to mobile only when residential fails

This is rare. If TikTok, Instagram's mobile API, or a mobile-only carrier-gated endpoint blocks even residential traffic, mobile proxies are the next step. Expect 4-10x the residential cost per GB.

One-page decision tree

Real-World Use Cases

Three concrete scraping jobs, three different proxy choices. Each one with the actual code that works.

1. E-commerce price monitoring on Amazon (residential)

Amazon's anti-bot system, Project Sentinel, blocks datacenter traffic on the first request. Residential is required, with sticky sessions to keep a coherent search-to-detail flow.

from browserbeam import Browserbeam

client = Browserbeam(api_key="YOUR_API_KEY")

session = client.sessions.create(
    url="https://www.amazon.com/s?k=wireless+headphones",
    proxy={"kind": "residential", "country": "us"},
    locale="en-US",
    timezone="America/New_York",
    block_resources=["image", "font", "media"],
)

result = session.extract(
    products=[{
        "_parent": "[data-component-type='s-search-result']",
        "_limit": 20,
        "title": "h2 a span >> text",
        "price": ".a-price .a-offscreen >> text",
        "rating": ".a-icon-alt >> text",
    }]
)

for p in result.extraction["products"]:
    print(p)

session.close()

Amazon's DOM structure changes periodically. Test selectors before running at scale, or use Browserbeam's AI extraction to avoid hardcoded selectors entirely.

Why residential here: Amazon serves a CAPTCHA wall to datacenter ASNs within seconds. Why country=us: you want USD prices and US Prime availability. Why image/font blocking: residential bandwidth is metered, and product images alone weigh 5-10 MB per page if you let them load. The price monitoring bot guide walks through the full ingestion pipeline.

2. Travel and hospitality data on Airbnb (datacenter)

Airbnb does not block datacenter ASNs. It serves the same content to every IP type. Save 90% on proxy bandwidth by using datacenter.

session = client.sessions.create(
    url="https://www.airbnb.com/s/Paris/homes?currency=USD",
    proxy={"kind": "datacenter", "country": "us"},
    locale="en-US",
    timezone="America/New_York",
    block_resources=["image", "font", "media"],
)

result = session.extract(
    listings=[{
        "_parent": "[itemprop='itemListElement']",
        "_limit": 10,
        "title": "[data-testid='listing-card-title'] >> text",
        "price": "[data-testid='price-availability-row'] >> text",
        "url": "a[aria-labelledby] >> href",
    }]
)

session.close()

Airbnb changes its CSS class hashes frequently, so avoid selectors like ._tt122m. Use data-testid attributes or semantic selectors instead. The scrape Airbnb guide has the latest verified selectors.

Why datacenter here: every test we ran on Airbnb returned identical content from datacenter and residential proxies, and datacenter is 10x cheaper. Why a US datacenter pin: you want USD pricing and US locale formatting. The scrape Airbnb guide covers the full pipeline including detail pages.

3. News aggregation across 20 countries (rotating datacenter, country-pinned)

For a content aggregator pulling top stories from local news sites in 20 markets, you need country-correct geo-targeting (so French news sites serve French content) but not residential-grade evasion. Country-pinned datacenter is the sweet spot.

targets = [
    "https://news.ycombinator.com",
    "https://www.lemonde.fr",
    "https://www.spiegel.de",
    "https://www.bbc.co.uk/news",
]

for url in targets:
    session = client.sessions.create(
        url=url,
        proxy={"kind": "datacenter", "country": "auto"},
        block_resources=["image", "font", "media"],
    )
    result = session.observe()
    print(url, len(result.page.markdown.content))
    session.close()

Why country: "auto": Browserbeam parses the TLD and pins each session to the matching datacenter pool (fr for lemonde.fr, de for spiegel.de, gb for bbc.co.uk). Why datacenter at all: news sites serve content to anyone, and the cost of running 100k pages a day matters more than the marginal detection benefit.

Common Mistakes When Choosing Proxies

These five mistakes show up in nearly every proxy setup we review. Each one is avoidable, and each one costs real money when you don't catch it.

1. Defaulting to residential because "it works on more sites"

Residential is 10x more expensive than datacenter. If half your targets work fine with datacenter, defaulting to residential everywhere doubles your proxy bill for nothing. What to do instead: A/B test new targets with both, measure the real success rate, and only promote to residential when datacenter blocks above 5%.

2. Ignoring bandwidth costs

A scraping job that loads images, fonts, and tracking scripts on a 3 MB Amazon page burns through a 50 GB monthly residential plan in 16,000 page loads. The same job with block_resources: ["image", "font", "media"] stretches that same plan to 100,000 page loads. Six times the output, same budget. Always block non-essential resources unless you specifically need them. Browserbeam blocks images and fonts by default for this reason.

3. Using rotating residential when you need a sticky session

Authenticated workflows break when the IP rotates per request. The site sees an "account holder" whose IP changes every page load — which itself is a strong bot signal and often triggers a security lockout. Any logged-in or multi-step flow needs a sticky session. With Browserbeam this is automatic for residential: the proxy holds the session ID for the full browser session lifetime.

4. Geo-mismatching the proxy and the locale

Pinning a US datacenter proxy to a Paris Airbnb URL while keeping locale: "en-GB" and timezone: "Europe/London" creates an obviously inconsistent fingerprint. Sites cross-check IP geolocation against browser locale and timezone. The mismatch lights up fraud detection like a Christmas tree. Keep all three aligned. If you want US prices, use country: "us", locale: "en-US", and timezone: "America/New_York".

5. Treating "rotating" and "session" as interchangeable

Many marketing pages use both terms to mean "you get many IPs". They mean different things. Rotating = new IP per request. Session = same IP for a window. Simple rule: if each request is independent (catalog scrapes, SERP, sitemaps), rotate. If a sequence of requests must look like one user, stick.

Frequently Asked Questions

Best proxy for web scraping?

There is no single best proxy. Datacenter wins on cost and speed for lightly-protected sites. Residential wins on detection avoidance for hostile targets. Static residential and ISP proxies win for account-bound automation. The right answer is the cheapest type that gets your block rate under 5% on the actual target. Test before committing.

Residential vs datacenter proxies — which should I pick first?

Start with datacenter. It is roughly 10x cheaper per gigabyte and works on about half of public web targets. Switch to residential only when you see real failures (403s, CAPTCHAs, missing data). Defaulting to residential everywhere is the most common over-spend in scraping budgets.

Are residential proxies legal?

Buying and using residential proxies from reputable providers (Oxylabs, Bright Data, Decodo) is legal in the US and EU as long as the underlying peers consented and the scraping work itself respects copyright, terms of service, and applicable regulations like GDPR. Where residential proxies become problematic is when peers were enrolled without informed consent. Pick providers that publish their consent flow, and treat scraping legality and proxy legality as two separate questions.

How much do residential proxies cost in 2026?

Pay-as-you-go starts around $4-6/GB at most major providers (Oxylabs, Bright Data, Decodo). With 100+ GB monthly commits, expect $2.50-3.50/GB. The cheapest credible residential pricing in 2026 sits around $2/GB at the 1 TB+ tier from Decodo and Oxylabs. Anyone advertising "unlimited residential bandwidth" at consumer prices is either rebranding datacenter or running an unsustainable promotion.

What is a rotating residential proxy?

A rotating residential proxy assigns a fresh IP from a residential pool to each connection. The pool typically holds 10-100 million IPs, so the same IP rarely repeats within a short window. Rotating is the right pattern for parallel, independent requests like catalog scraping, sitemap crawls, or SERP collection. It is the wrong pattern for logged-in workflows, where you want a sticky session instead.

ISP proxy vs residential proxy?

ISP proxies (also called static residential) are residential-class IPs hosted on always-on infrastructure and sold as fixed IPs you keep for the month. Rotating residential proxies cycle through millions of consumer-device peers. ISP proxies are faster and more reliable but smaller pools and pricier per IP. Rotating residential is for scale; ISP is for account-bound automation that needs a single, consistent residential IP.

Mobile proxy vs residential proxy?

Mobile proxies route through 4G/5G carrier IPs, which are nearly impossible to block because mobile carriers use carrier-grade NAT, so blocking one IP would block thousands of real users. Residential proxies route through home ISP peers. Mobile is harder to detect, more expensive ($20-40/GB versus $2-6/GB residential), and only worth it for the small set of mobile-app endpoints, social platforms, and ad networks where residential still fails. For 99% of scraping work, residential is enough.

Decodo vs Oxylabs — which is better for scraping?

Both run large residential pools (Decodo 125M+ IPs, Oxylabs 100M+) and ship comparable self-service products. Oxylabs tends to win on enterprise contracts and publishes the more detailed consent flow. Decodo (formerly Smartproxy) has cleaner self-service onboarding and competitive pricing on smaller plans. For most scraping budgets the practical difference is small; pick the one that matches your billing model. If you would rather not pick at all, a managed cloud browser API like Browserbeam handles proxy selection for you and lets you switch between datacenter and residential with one parameter.

Conclusion

Proxy selection isn't a belief system — it's an engineering decision with a dollar sign attached. Datacenter wins on cost and speed for the half of the public web that doesn't aggressively profile traffic. Residential wins on detection avoidance for the other half. ISP and mobile are sharper tools for narrower jobs. No universal answer, just a mapping from target site to proxy type.

The mistake most teams make is defaulting to residential because the marketing makes it sound safer, and quietly burning 5-10x more on bandwidth than they need to. The opposite mistake (cheaping out on datacenter for a site that hard-blocks it) wastes engineering time chasing fixes for what is fundamentally a wrong-tool problem.

If you want to skip building proxy rotation and bandwidth tracking yourself, Browserbeam routes every session through a managed proxy by default and lets you switch types with a one-line change. The Python SDK guide covers the full session lifecycle, the scaling guide covers concurrent scraping patterns that work cleanly on top of either proxy type, and the billing reference has the exact per-MB credit math.

What will you scrape first, and which type fits the target?