Apify vs Oxylabs in 2026: Full Platform vs Proxy-First Infrastructure
Apify vs Oxylabs is really a question of what you are buying. Oxylabs is fundamentally a proxy company — one of the largest premium proxy networks on earth — that added scraper APIs on top. Apify is fundamentally a scraping platform — a marketplace of 4,000+ finished scrapers plus a cloud to run them — that includes proxy infrastructure. The product order defines who each serves: Oxylabs sells to enterprises with engineering teams; Apify sells to everyone who wants data without building infrastructure.
I have used both. On common targets (Amazon, Google Maps, LinkedIn), Apify is not close — a maintained actor produces structured data in minutes while Oxylabs expects you to build extraction on their API. On the other side, an enterprise team running millions of requests through premium residential proxies for a proprietary system will find Oxylabs's network depth genuinely valuable — though they pay enterprise prices for it.
This comparison covers the proxy-vs-platform distinction, the scraper API layer, pricing reality, scale economics, and the decision framework. Related: [Apify vs Bright Data](/blog/apify-vs-bright-data), [Apify vs ScraperAPI](/blog/apify-vs-scraperapi), [Apify proxy guide](/blog/apify-proxy-guide).
Quick Answer
Apify vs Oxylabs: Oxylabs = premium proxy network + scraper APIs for enterprises (hundreds/mo, dev-required). Apify = complete platform with 4,000+ actors, datasets, scheduling, proxies included ($49/mo, no-code friendly). Different buyers — raw infrastructure vs finished pipelines.
Apify vs Oxylabs: Oxylabs = premium proxy network + scraper APIs for enterprises (hundreds/mo, dev-required). Apify = complete platform with 4,000+ actors, datasets, scheduling, proxies included ($49/mo, no-code friendly). Different buyers — raw infrastructure vs finished pipelines.
- Oxylabs is a proxy company that added scraper APIs; Apify is a scraping platform that includes proxies. The order matters — it defines what each does best.
- Oxylabs strength: one of the largest premium proxy networks (100M+ IPs) plus SERP/e-commerce scraper APIs aimed at enterprise teams.
- Apify strength: a complete data platform — 4,000+ maintained actors, datasets, scheduling, integrations, and proxies included, usable by non-developers.
- Pricing gap is the story: Oxylabs enterprise plans start in the hundreds/month; Apify Pro is $49/mo with comparable outcomes on most common targets.
- For covered targets (Amazon, Maps, LinkedIn): Apify wins — maintained actor beats building on a raw scraper API.
- Verdict: enterprise teams needing raw premium proxies/custom scraping at massive scale → Oxylabs. Everyone else needing finished data pipelines → Apify.
1. The core difference — proxy company vs scraping platform
What each company actually is:
- Oxylabs: started as a proxy network — 100M+ residential/datacenter IPs — then layered scraper APIs and datasets on top. Infrastructure-first.
- Apify: started as a scraping platform — actors, datasets, scheduling — with proxy infrastructure included. Pipeline-first.
- The buyer tells you: Oxylabs sells to teams BUILDING scraping systems. Apify sells to teams who want the data, not the system.
Oxylabs = proxy company + APIs (you build the scraper). Apify = scraping platform (the scraper often already exists). Building infrastructure vs consuming data.
2. Scraper APIs vs the actor marketplace
The extraction layer compared:
- Oxylabs Scraper APIs: SERP, e-commerce, web scraper APIs — you send requests, they handle unbanning, return data (structured for supported endpoints).
- Apify marketplace: 4,000+ maintained actors returning site-specific structured fields — plus custom actors when nothing fits.
- Coverage: Oxylabs APIs cover a focused set of targets. Apify covers vastly more sites via the marketplace.
- The gap: on covered targets both work; on everything else Apify has an actor or you build one — while Oxylabs expects you to build on their API regardless.
Oxylabs APIs cover a focused set of targets; Apify marketplace covers thousands. On a covered target both work — everywhere else, Apify wins on coverage.
Apify
4.7Verified partnerWeb scraping and automation platform — Free / $49/mo Starter
3. For non-developers — there is no contest
Who can actually use each product:
- Apify: no-code — pick an actor, fill a form, run it, get a dataset. A marketer can run a pipeline day one.
- Oxylabs: developer product — APIs you integrate into code. No finished-scraper marketplace for non-devs.
- Scheduling + storage: Apify includes cron, datasets, and exports natively. On Oxylabs you build the pipeline around their API.
- Team fit: marketing/ops/founders → Apify. Engineering orgs with scraper devs → Oxylabs is a candidate.
Oxylabs is a developer product — no marketplace, no no-code. If you do not have scraper engineers, it is not the tool. Apify produces finished pipelines without code.
4. Proxy infrastructure — where Oxylabs leads
The one area Oxylabs genuinely wins:
- Oxylabs proxy network: one of the largest — residential, datacenter, mobile IPs across nearly every geography. Best-in-class for raw proxy needs.
- Apify proxies: datacenter + residential tiers integrated into actors — sufficient for the vast majority of scraping jobs.
- When Oxylabs proxies matter: running YOUR OWN scrapers at massive scale on the hardest targets, where you need granular proxy control.
- When they do not: running actors where Apify already handles the proxying — the infrastructure detail is invisible.
Oxylabs wins on raw premium proxies for your own massive crawlers. But Apify proxies are already built into actors — for most jobs the proxy layer is solved invisibly.
5. Pricing — the honest math
Very different bills:
- Oxylabs: usage-based and enterprise-tilted — scraper API plans start around $99+/mo but serious volume runs hundreds to thousands. Proxies priced per GB/IP.
- Apify: $49/mo Pro + usage — covers most pipelines including proxies, compute, and storage.
- The math: a typical monitoring or lead pipeline is far cheaper on Apify. Oxylabs makes sense only at enterprise scale or for raw proxy needs.
- Watch on Oxylabs: the sticker is the API price — engineering time to build extraction is the real cost.
Oxylabs bills are API + proxy usage at enterprise scale + your dev time. Apify $49/mo covers most complete pipelines. Total-cost comparison favors Apify for almost every non-enterprise case.
6. Scale and reliability
Both can run big — differently:
- Oxylabs: built for massive request volume — the proxy network is the reliability story.
- Apify: cloud-parallelized actor runs, built-in retries, datasets — scale is the product, at lower per-job complexity.
- The difference: Oxylabs scale requires your orchestration code. Apify scale is a config slider.
- Reliability on covered targets: Apify maintained actors adapt when sites change — on Oxylabs your integration is yours to fix.
Both scale, but Oxylabs scale needs your orchestration; Apify scale is built-in. Maintained actors also absorb site-change breakage that is your problem on a raw API.
7. Decision framework
The 30-second call:
- Need a finished data feed from a known site? → Apify.
- Non-technical team? → Apify.
- Enterprise running proprietary scrapers needing premium proxies at massive scale? → Oxylabs.
- Need SERP/e-commerce API + in-house engineering? → compare Oxylabs API vs Apify actors on your specific target.
- Default for 90% of buyers: Apify — marketplace coverage + no-code + lower total cost.
Apify for finished pipelines and non-devs; Oxylabs for enterprises building proprietary crawlers on premium proxies. The 90% case is Apify.
Apify
4.7Verified partnerWeb scraping and automation platform — Free / $49/mo Starter
Apify vs Oxylabs is pipeline vs plumbing: Oxylabs sells premium proxy infrastructure and scraper APIs to engineering teams building their own systems at enterprise scale. Apify sells finished data pipelines — 4,000+ actors, scheduling, datasets, included proxies — to everyone who wants the data, at $49/mo instead of enterprise pricing.
For the overwhelming majority of scraping needs, Apify is the faster, cheaper, and more complete answer. Oxylabs makes sense for enterprise teams with scraper engineers and massive proprietary-proxy requirements. Related: Apify vs Bright Data, Apify vs Zyte, Apify proxy guide.
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FAQ
Is Apify better than Oxylabs?
For most buyers: yes — 4,000+ actors, no-code, scheduling, datasets, included proxies at $49/mo. Oxylabs is for enterprises building proprietary scrapers on premium proxies. Finished pipeline vs raw infrastructure.
What is Oxylabs used for?
A premium proxy network (residential/datacenter/mobile IPs) plus scraper APIs (SERP, e-commerce, web). Serves engineering teams building their own scraping systems at scale.
Which is cheaper, Apify or Oxylabs?
Apify — $49/mo Pro covers most pipelines. Oxylabs plans start ~$99+/mo but serious usage runs hundreds+, plus engineering cost to build extraction. For typical use cases Apify is far cheaper in total cost.
Do I need coding for Apify vs Oxylabs?
Apify: no — marketplace actors run without code. Oxylabs: yes — their APIs require development work; there is no finished-scraper marketplace for non-devs.
Which has better proxies?
Oxylabs — one of the largest premium proxy networks, best-in-class for raw proxy needs. But Apify includes datacenter + residential proxies inside actors, sufficient for the vast majority of jobs.
Can Oxylabs replace Apify?
Only if you have engineers to build on their APIs — Oxylabs gives infrastructure, not finished scrapers. Apify gives both: pre-built actors AND a platform to build custom ones.
Who should choose Oxylabs over Apify?
Enterprise teams running proprietary large-scale crawlers who need granular premium-proxy control and have scraper engineers. Everyone else is better served by Apify's finished pipelines.
Tools mentioned in this article
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Apify
4.7Verified partnerWeb scraping and automation platform — Free / $49/mo Starter
Alex Mercer
AI Marketing Strategist · 8+ years
Alex has tested 200+ AI marketing tools on real campaigns with $50,000+ in ad spend. He writes hands-on reviews based on actual usage data, not press kits. His work has helped 10,000+ marketers build AI automation stacks that generate real ROI.