ScraperAPI vs ScrapingBee: 2026 Head-to-Head Comparison
I get asked about these two more than almost any other pair in the scraping infrastructure space, mostly because they solve the same problem from slightly different angles. Neither ScraperAPI nor ScrapingBee is a raw proxy provider in the way Bright Data or Oxylabs is. You don’t get a list of IPs and a username/password to plug into your own scraper. Instead you send a request to their API endpoint, they handle proxy rotation, retries, CAPTCHA solving, and (optionally) headless browser rendering, and hand you back the HTML or JSON. That distinction matters for this category page, because if you actually want a raw residential or mobile IP pool to route through your own tooling, neither of these is the right fit, look at a dedicated proxy network instead.
If you want the proxy headache abstracted away behind one API call, though, these two are the category leaders and have been for a few years running. I’ve run both in production for client scraping jobs, mostly e-commerce price monitoring and SERP tracking, and the differences show up less in “does it work” and more in cost at volume, how much control you get over IP behavior, and how well each one handles JavaScript-heavy targets.
Short version: ScraperAPI tends to win on raw price per successful request at high volume and gives you more granular control over proxy type per request. ScrapingBee’s headless Chrome rendering is more mature out of the box and its API is slightly easier to reason about for teams that don’t want to think about proxy types at all. Neither one is a bad choice, but which one costs you less money depends entirely on what you’re scraping and how much JavaScript rendering you need.
TL;DR comparison table
| ScraperAPI | ScrapingBee | |
|---|---|---|
| Starting paid plan | Around $49/mo for 100,000 API credits | Around $49/mo for 150,000 API credits |
| Free tier | 5,000 free API credits on signup, no card | 1,000 free API credits, no card required |
| Proxy types | Datacenter, residential, and mobile, selectable per request | Standard and “premium” proxy pool, fewer explicit tiers |
| JS rendering | Optional, billed at a credit multiplier | Real headless Chrome, mature and well-documented |
| Geotargeting | Country-level across dozens of countries, city-level on higher tiers | Country-level, smaller list on the premium pool |
| Extras | Structured data endpoints for Amazon, Google Search, autoparsing | Screenshot API, Google/Amazon extraction endpoints |
| Support | Email and live chat, dedicated Slack on Business/Enterprise | Email and live chat, strong self-serve docs |
| Best target user | High-volume scrapers optimizing cost per successful request | Teams that want fewer configuration decisions and reliable JS rendering |
Pricing on both sides shifts periodically, I’d treat the numbers above as directional rather than gospel and check the current ScraperAPI documentation and ScrapingBee documentation before you commit to a plan.
ScraperAPI at a glance
ScraperAPI runs on a pay-per-successful-request model, meaning failed requests generally don’t burn your credit balance, which sounds like a small thing until you’ve eaten a $200 bill from a provider that charges you for every 403 and timeout. Credits get consumed at different rates depending on what you ask for: a plain HTTP GET against a low-difficulty site costs one credit, but flip on JS rendering or ask for a premium residential IP and the cost multiplier goes up, sometimes by 10x or more depending on the target’s difficulty tier.
The plan structure runs Hobby (~$49/mo, 100K credits), Startup (~$149/mo, 1M credits), Business (~$299/mo, 3M credits, higher concurrency), and a custom Enterprise tier above that. Concurrent thread limits scale with the plan too, Business-tier accounts get meaningfully more parallel connections than Hobby, which matters if you’re trying to crawl a large catalog inside a tight window.
Where ScraperAPI differentiates is per-request control. You can specify render=true for JS pages, pick a premium=true flag to route through their residential pool, set country_code for geotargeting, and pass session_number to keep the same IP across a sequence of requests. It’s more knobs than ScrapingBee exposes, which is good if you’re optimizing cost aggressively (only pay for JS rendering on pages that actually need it) and mildly annoying if you just want a single toggle that works everywhere.
They also ship structured data endpoints for Amazon product pages, Google Search results, and Walmart listings that return parsed JSON instead of raw HTML, which saves you from writing your own parser for those specific targets.
ScrapingBee at a glance
ScrapingBee’s core pitch is simplicity: one endpoint, one API key, and a small number of parameters that cover most of what you need. render_js=true gets you a full headless Chrome session including screenshots, premium_proxy=true routes through their higher-quality IP pool, and country_code handles geotargeting. The credit system works similarly to ScraperAPI’s, a standard request costs 1 credit, JS rendering costs roughly 5 credits, and premium proxy plus JS rendering stacks the multipliers further.
Plans start around $49/mo for roughly 150,000 credits on the Freelance tier, stepping up to Startup (~$99/mo, 1M credits) and Business (~$249/mo, 3M credits), with Enterprise above that for custom volume and SLAs. ScrapingBee’s headless rendering has historically felt more “just works” for sites with heavy client-side JavaScript, things like infinite-scroll product listings or SPA-rendered content, because they’re running an actual Chrome instance rather than a lighter rendering layer.
They also offer a screenshot API as a first-class product (useful if part of your workflow needs visual QA of rendered pages) and Google Search / Amazon extraction endpoints similar to ScraperAPI’s structured data tools. Their documentation is genuinely good, if you’re a solo operator or small team without a dedicated scraping engineer, ScrapingBee’s onboarding curve is shorter.
head-to-head
IP pool size
Both companies market large IP counts on their homepages, and I’d treat those numbers skeptically since neither publishes independently audited figures. ScraperAPI’s marketing claims access to tens of millions of IPs blended across datacenter, residential, and mobile categories. ScrapingBee doesn’t publish a specific IP count as prominently, framing its pool instead around “premium” vs standard proxy tiers. In practice, pool size matters less than how the rotation and retry logic behaves under load, which is where the real differences show up.
rotation control
ScraperAPI gives you more explicit control here. You can force a new IP on every request (default behavior), or hold a sticky session with session_number for a set duration, and choose which proxy type to rotate through per call. ScrapingBee rotates automatically behind the scenes with less exposed configuration, you get premium vs standard, JS vs no-JS, but not the same level of manual session steering. If your workflow needs precise control over when an IP changes (logging into a site and staying logged in across several requests, for example), ScraperAPI’s session parameter is the more predictable tool.
geo coverage
ScraperAPI edges ahead on breadth, supporting country-level targeting across a longer list of countries and offering city-level precision on higher-tier plans. ScrapingBee supports country-level targeting too but its premium proxy pool, where the more precise geotargeting lives, covers a narrower list of countries than ScraperAPI’s residential/mobile tiers. If your project needs granular geo-targeting outside the usual US/UK/EU cluster, verify country availability directly against each vendor’s current docs before you build around it, coverage lists change more often than marketing pages get updated.
connection success rate
This is the metric vendors are least willing to publish honestly, and the one that matters most in production. In my own runs against moderately protected e-commerce sites, both services land success rates in a similar range on standard datacenter/residential requests, with ScrapingBee’s headless Chrome rendering giving it a slight edge on JS-heavy, bot-detection-hardened targets specifically because it’s running a real browser rather than a lighter-weight fetch layer. On plain server-rendered pages the gap mostly disappears. Neither company publishes independently verified uptime or success-rate numbers, so any specific percentage you see quoted (by them or by anyone else) should be treated as a marketing claim, not an audited stat.
speed
ScraperAPI’s non-JS requests tend to return faster on average simply because you’re not paying the overhead of spinning up a browser context. Once you flip on JS rendering, both providers slow down comparably, real Chrome rendering takes real time regardless of who’s running it, often adding several seconds per request versus a plain HTML fetch. If your job is high-volume and doesn’t need JS, ScraperAPI’s lighter default path will usually clear a queue faster. If you need JS rendering on most requests, the speed gap between the two narrows to the point where it’s not a deciding factor.
pricing per GB
Neither service prices by bandwidth the way raw proxy networks do, they price by API credit, which is really a proxy for request count and complexity. That said, if you back-calculate an effective cost per successful request at comparable volume tiers, ScraperAPI generally comes out cheaper for simple, non-JS requests because of its lower base credit cost and pay-for-success model. Once JS rendering and premium proxies enter the mix, the gap narrows significantly and can flip depending on your specific mix of request types. Run the math on your actual target list before assuming either one is categorically cheaper, credit multipliers on both platforms vary by site difficulty, not just by plan tier.
session persistence
Both support sticky sessions for maintaining the same IP across a sequence of calls, useful for anything involving pagination, cart flows, or authenticated scraping. ScraperAPI’s session_number parameter is well documented and predictable. ScrapingBee supports a similar concept through its session_id parameter but historically has had less granular control over session duration. If your workflow depends heavily on maintaining IP consistency across a long multi-step scrape, test both against your actual flow rather than trusting the docs alone, session behavior under real load can differ from the documented spec.
concurrent connections
Concurrency limits scale with plan tier on both platforms, and this is one area where I’d tell you to actually read the current plan pages rather than trust anything written here, both vendors have adjusted thread caps over time as they’ve repriced tiers. Generally, ScraperAPI’s higher tiers (Business and above) have offered more concurrent threads out of the box, which matters if your crawl needs to hit hundreds of URLs in parallel within a tight window. For lower-volume or scheduled batch jobs where you’re not racing a clock, concurrency differences between the two matter less.
use-case verdicts
Large-scale e-commerce price monitoring (thousands of SKUs daily, mostly server-rendered): ScraperAPI wins here. The pay-per-success model plus lower base credit cost for non-JS requests makes it cheaper at volume, and the structured Amazon/Walmart endpoints save engineering time if those are your targets.
JS-heavy SPA scraping (React/Vue-rendered listings, infinite scroll, dynamic pricing widgets): ScrapingBee edges ahead. Its headless Chrome rendering has felt more reliable against harder JS targets in my own testing, and the screenshot API is a genuine bonus if you need visual verification of what got rendered.
SEO / SERP rank tracking: Close call, both offer Google Search extraction endpoints. I’d lean ScraperAPI slightly for cost at high query volume, but if you’re tracking a smaller set of keywords and want simpler setup, ScrapingBee’s docs make onboarding faster.
Small team or solo operator building a first scraper, unsure of proxy types needed: ScrapingBee. Fewer configuration decisions, solid default behavior, and documentation that doesn’t assume you already know the difference between datacenter and residential proxies. You’ll pay a little more per request as you scale, but you’ll spend less time debugging config.
who should pick ScraperAPI
Pick ScraperAPI if you’re running high-volume scraping jobs where most requests don’t need JS rendering, you want granular control over proxy type and session behavior per request, and cost per successful request at scale is your primary constraint. It also makes sense if you’re already scraping Amazon, Google, or Walmart specifically and want to skip writing your own parser. Read the full breakdown in our ScraperAPI review.
who should pick ScrapingBee
Pick ScrapingBee if your targets are JS-heavy and you want headless Chrome rendering that works reliably without a lot of tuning, if you’re a smaller team that values simple configuration over maximum control, or if you need the screenshot API as part of your workflow. See the details in our ScrapingBee review.
verdict overall
There’s no universal winner here, it genuinely depends on your traffic mix. If I had to run one default recommendation for a client starting from zero with a high-volume, mostly-static scraping job, I’d start with ScraperAPI and only pay the JS rendering multiplier on the specific pages that need it. If the client’s target list is dominated by JavaScript-rendered pages or they don’t have the engineering time to tune proxy-type parameters, I’d point them at ScrapingBee instead and accept the slightly higher per-request cost for the smoother default experience.
One thing worth flagging regardless of which you pick: both services route your requests through their proxy pools, but you’re still responsible for respecting target sites’ terms of service and robots.txt directives where applicable, the API vendor handling your proxy rotation doesn’t change your obligations as the party issuing the requests. If you’re scraping at volume and start seeing a wall of HTTP 429 responses, that’s the target telling you to slow down regardless of how good your proxy pool is, no proxy service fixes a scraping strategy that’s too aggressive for the target’s rate limits. This isn’t legal advice, just an operator’s observation after running both of these against a lot of real targets.
If you’re also dealing with fingerprinting and detection on the browser side rather than just the network side, that’s a separate problem from proxy rotation, worth reading up on over at antidetectreview.org’s blog if bot detection beyond IP reputation is part of what you’re fighting. For more comparisons like this one, check the rest of our blog.
Written by Xavier Fok
disclosure: this article may contain affiliate links. if you buy through them we may earn a commission at no extra cost to you. verdicts are independent of payouts. last reviewed by Xavier Fok on 2026-07-20.