Scraping API Pricing 2026: What $500/Month Actually Gets You From Each Provider

Most scraping API pricing pages are built to confuse you. Compute units. Bandwidth tiers. Results-based billing. CPM rates. By the time you've compared three providers, you've lost an hour and still don't know which one is cheaper for your actual use case.

This post cuts through it. We benchmarked the four most-evaluated scraping APIs — Bright Data, Oxylabs, Scrapeless, and Apify — around a single question: what does $500/month actually buy you? Then we'll show you what each pricing model hides, which hidden costs blow up budgets, and when a managed alternative makes more sense than any of them.

Scraping API Pricing Comparison 2026: The Full Table

Here's the side-by-side view at $500/month, using each provider's standard public pricing — no enterprise negotiation, no undisclosed volume discounts:

Provider	Billing model	$500/mo buys you	Per-1K requests	Free tier	Annual discount
Bright Data	Pay-per-request	~167K page loads	$3.00	Trial credits	Yes
Oxylabs	Results-based subscription	~312K results	$1.60	Free trial only	10%
Apify	Compute units	~$500 in platform credits	$0.20–$2.00+ (varies)	$5/mo credits	Yes
Scrapeless	CPM + hourly usage	Varies by tier	$0.30 (SERP); $0.09/hr (Basic)	No	Yes
ScrapeWise	Managed/outcome-based	Dedicated infrastructure + delivery	Not applicable	No	Custom

The table tells one story. What happens when you actually use each service tells another.

Bright Data Pricing: Pay-As-You-Go With No Monthly Floor

Bright Data's Web Scraper API charges $3 per 1,000 page loads at standard rates. No monthly minimum, no commitment required. At $500/month, you're buying approximately 167,000 page loads — enough to monitor 5,000 products across 30+ pages daily with some budget left over.

The pay-as-you-go model is genuinely flexible. You can run a one-week campaign, go quiet for a month, and come back without losing anything. That flexibility is the reason Bright Data is the default evaluation target for teams who need occasional high-volume bursts rather than continuous monitoring.

Where it gets expensive: JavaScript-rendered pages cost more than standard HTML. CAPTCHA solving, when needed, runs as an additional fee layered on top. If your target sites serve dynamic product listings or lazy-loaded prices — which most major European retailers including Zalando and Otto do — your effective cost can climb to $5–8 per 1,000 pages without warning.

Bright Data's per-unit pricing is the most transparent of the four. The unpredictability comes from variable uplift on complex targets. For teams running competitor price tracking across JavaScript-heavy e-commerce sites, this cost variance needs to be modeled before committing.

At scale (1M+ pages/month), Bright Data offers bundled enterprise pricing. Per Bright Data's public pricing pages, buyers scraping at that volume typically secure rates 20–40% below pay-as-you-go. But you won't see those figures until you're in a sales conversation.

Oxylabs Pricing: Results-Based Billing and What That Means

Oxylabs starts at $49/month and bills on a results basis — you pay for successful responses delivered, not raw requests sent. The advertised rate is $1.60 per 1,000 results, which looks cheaper than Bright Data until you understand what "results" actually means.

A result is a successfully scraped content entity. If Oxylabs sends a request and gets blocked, that doesn't count as a result — in theory, you don't pay for failures. In practice, this means the infrastructure has every incentive to return something even when the target site has changed structure, returned a soft 404, or served a challenge page. Validating data quality on top of raw delivery remains your responsibility.

The 10% annual discount is real and worth taking if you're committed to Oxylabs long-term. Their SERP Scraper API is priced separately at $0.80–$1.00 per 1,000 queries, which matters if you need search data alongside product scraping.

The cap problem: The $49/month entry plan comes with a fixed monthly result allowance. If your scraping volume spikes — a competitor runs a flash sale, you need to audit 50,000 SKUs in 48 hours — you'll hit your cap and face overage rates or a forced wait until reset. Teams doing product data extraction at variable volumes find this the most limiting constraint in practice.

According to Oxylabs' billing documentation, some features like Headless Browser use substantially more traffic than simple requests, which increases billing costs beyond the headline rate.

Oxylabs suits teams with predictable, steady-state scraping needs who want block-failure protection built into their billing model.

Apify Pricing: Compute Units, Not Requests

Apify is the outlier in this comparison. Where Bright Data and Oxylabs price by the request, Apify prices by compute consumption: 1 Compute Unit = 1 GB of RAM running for 1 hour. You're buying platform capacity, not data delivery.

The free tier gives you $5 in monthly credits — enough to run hundreds of small scrapes against standard targets (Google Maps, Amazon product pages, basic HTML sites). The Starter plan at $29/month works for small projects. The Scale plan at $199/month is where professional teams typically start.

At $500/month you'd be negotiating a custom plan between Scale ($199) and Business ($999). CU rates range from $0.20/CU on the Business plan to $0.30/CU on Free and Starter tiers. For comparison, scraping approximately 250,000–500,000 simple HTML pages per month at efficient actor configurations is realistic at the $199 Scale tier — more pages than you'd expect, because lightweight scrapes consume very few CUs.

Why Apify is structurally different: You're not just buying scraping capacity. The platform includes pre-built actors, orchestration, scheduling, and storage. If you need to run a Google Maps scraper, an Amazon product actor, and a LinkedIn data collector in sequence, Apify handles that pipeline natively. Per Apify's pricing page, the Business tier supports 2,048 concurrent runs — a ceiling few teams hit.

The hidden complexity: Cost per scrape varies wildly by actor and target. Simple HTML pages cost fractions of a cent each. JavaScript-heavy sites, pages requiring browser rendering, or actors with slow execution can consume CUs 10–50x faster. Modeling actual monthly cost before committing requires benchmarking your specific workflow — which most buyers skip.

Apify suits teams building multi-step data pipelines who need orchestration and pre-built connectors, not just raw scraping capacity.

Scrapeless Pricing: Low Entry, Hidden Rollover Risk

Scrapeless uses a CPM (cost per mille) rate system with hourly usage billing. The Basic tier has no monthly minimum but charges $0.090 per hour of usage — a model that looks attractive on paper but requires careful volume monitoring.

Their SERP API is notably cheap at $0.30 per 1,000 queries, which undercuts Bright Data and Oxylabs significantly for search data collection. For teams whose primary use case is SERP monitoring — tracking keyword rankings, competitor ad placements, or search result volatility — Scrapeless pricing deserves a close look before defaulting to pricier options.

The rollover problem: Scrapeless packages work as pre-deposited balances. When your billing cycle ends, unused balance does not carry forward. If you purchased a package expecting 100,000 requests and only used 60,000, the remaining credit is forfeit. This makes Scrapeless economical only when your volume is consistent and predictable — exactly the situation where it's hardest to justify switching from an established provider you've already integrated.

At $500/month, volume-tier discounts reduce the effective CPM meaningfully. But the no-rollover policy means you're planning usage carefully each month or effectively subsidizing Scrapeless with unused credits.

Scrapeless suits cost-conscious teams with a primary SERP data use case and stable, predictable usage patterns.

The Hidden Costs Most Buyers Miss

The sticker price on any scraping API is a floor, not a ceiling. These are the cost layers that don't appear on pricing pages:

CAPTCHA solving. Sites with CAPTCHA challenges require a solving service. Some providers include it; others bill it as an add-on. If 20% of your target pages serve CAPTCHAs, your effective cost can increase 30–50% before you notice.

Residential proxy uplift. Datacenter IPs get blocked on high-value targets — Amazon, major price comparison engines, most large Nordic and DACH retailers. Residential proxy routing costs 3–8x more than datacenter traffic. If your monitoring targets require residential routing, the advertised per-request rate becomes largely theoretical.

JavaScript rendering. Headless browser rendering for JS-heavy pages consumes more resources than raw HTTP requests. Oxylabs, Bright Data, and Scrapeless all charge more for JavaScript-rendered responses. Most major e-commerce sites now load prices dynamically — if you're doing competitive price monitoring at scale, budget 2–3x the base rate for real-world targets.

Failure rate variance. On difficult targets, success rates can fall to 85–95% even with premium providers. On a results-based model like Oxylabs, this risk is theoretically absorbed by the provider — but as noted, "results" can be returned loosely.

Infrastructure management time. This is the cost nobody puts in their comparison spreadsheet. Configuring proxies, managing rate limits, handling IP rotation, debugging block detection, writing retry logic, maintaining selectors as sites update — this is real engineering work. According to Ahrefs' analysis of scraping infrastructure costs, teams routinely underestimate ongoing maintenance at 3–4x their initial estimates. For a team of two to three developers, proxy and scraping infrastructure maintenance can consume 20–40% of a sprint.

Scraping API Pricing Comparison 2026: When Managed Delivery Changes the Equation

Per-request billing makes sense when you have the engineering bandwidth to run and maintain your own scraping stack. When you don't — or when you're spending more on infrastructure management than on the API itself — the comparison shifts.

ScrapeWise operates on an outcome-based model: dedicated scraping infrastructure per client, no per-request billing, and data delivered against your agreed specifications. You don't buy compute capacity and hope it returns useful data. You define what data you need, and you receive it — with CAPTCHA solving, proxy management, and selector maintenance handled as part of the service.

This matters most for teams tracking prices across sophisticated targets — Zalando, Cdiscount, MediaMarkt, Allegro — where bot detection is advanced and DIY maintenance burden is high. Per-request billing with a general-purpose API puts you on a treadmill of selector updates, proxy refreshes, and retry cycles. The anti-bot landscape has become sophisticated enough that maintaining competitive scraping coverage is a specialization in its own right.

The right comparison isn't "which API is cheapest per request." It's "what is the total cost of owning a scraping stack versus receiving clean data as a service." For teams focused on competitive intelligence rather than scraping infrastructure, that question usually has a clear answer.

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