Plenty of teams run their web scraping on Apify, and for good reason: it is a mature platform with a marketplace of pre-built scrapers, serverless compute, datasets, scheduling, and an active developer ecosystem. If you are reading this, you are probably not unhappy with Apify so much as wondering whether a simpler model would fit your particular job. Some teams just want an API that returns a page, billed only when the page comes back, without designing actors or watching compute usage.
This piece compares Apify and Crawlbase fairly, on the dimensions that actually decide the call: the core model, setup and complexity, JavaScript rendering, proxy and CAPTCHA handling, data output, scale, the pricing model, and support. It leads with what each tool is genuinely good at, includes one head-to-head table, and ends with an honest section on when Apify is the better choice. The goal is to help you match the tool to your workload, not to crown a winner.
Quick overview: Apify vs Crawlbase
Apify is a full automation and scraping platform. Its core unit is the "actor," a serverless program (often written in JavaScript or Python) that you configure, run, and scale on Apify's infrastructure. It ships with a large marketplace of ready-made actors for popular sites, plus datasets, key-value stores, request queues, scheduling, and an SDK. If you want to build scraping pipelines, reuse them as components, or even publish a scraper as a product, Apify gives you a deep, flexible toolbox to do it.
Crawlbase takes a narrower, API-first approach. Instead of designing actors and managing compute, you send a request to an endpoint with your token and a target URL, and you get back the page as raw HTML or fully rendered content. Proxy rotation, CAPTCHA handling, and retries happen inside the service. There is less to learn and less to operate, which suits teams whose priority is the data itself rather than a platform to build on. The trade is that you give up the actor marketplace and the workflow-orchestration layer that Apify is built around.
A useful way to frame it: Apify is a workshop with every tool for builders who want to assemble pipelines; Crawlbase is a focused service that hands back finished pages with the least setup. Both scrape at scale; they differ in how much of the machinery you operate.
Head-to-head comparison
Here is how the two line up across the dimensions that usually decide the choice. Read it against your own workload rather than as a scoreboard: a row that is decisive for one team is irrelevant for another.
| Dimension | Apify | Crawlbase |
|---|---|---|
| Core model | Actor-based serverless functions on a full platform | API-first: REST endpoint plus an async crawler |
| Setup & complexity | Pick or build an actor, configure it, manage runs and triggers | One API request with a token and a URL |
| JavaScript rendering | Yes, via browser-based actors you configure | Yes, a render parameter on the same endpoint |
| Proxy & CAPTCHA | Proxy product available; you wire it into the actor | Built-in rotation and CAPTCHA handling, on by default |
| Data output | Datasets, key-value stores, request queues | Raw HTML or JSON, direct or via webhook callback |
| Scale | Scales actors; you manage concurrency and tuning | Server-side retries plus async Crawler for high volume |
| Pricing model | Subscription plus compute units and platform usage | Pay only for successful requests, 1,000 free to start |
| Support | Docs, community, marketplace, support by plan | Docs, libraries, and 24/7 support |
The pattern across the rows is consistency of shape. Apify gives you more surface area to build on; Crawlbase gives you fewer moving parts to operate. Neither is automatically better. The next sections walk the dimensions that tend to matter most.
Ease of use: setup and integration
The first thing you notice with any scraping tool is how much effort it takes to get from nothing to actual data. With Crawlbase there is little to set up. You do not create a project, build a dataset, or learn a framework to fetch HTML. A single request with your token and the target URL returns the page:
curl "https://api.crawlbase.com/?token=YOUR_TOKEN&url=YOUR_ENCODED_URL"
For larger or high-volume workloads, the async Crawler queues jobs and delivers results to your endpoint, so you are not holding open thousands of synchronous requests. Either way, there is no actor to author and no deployment to manage; the page comes back ready to process.
Apify works around the actor model, which is more flexible but asks for more before you see results. A typical flow is: pick or build an actor (usually JavaScript or Python), configure it with your target, run it, then pull the output from a dataset or store. That structure is a genuine strength when you want fine-grained control or plan to reuse a scraper as a reusable component. If your priority is speed to first result on a straightforward target, the API approach tends to feel lighter to start with. This is the classic difference between an API-based scraper and a build-it-yourself stack.
Pricing model: compute units vs pay-per-success
The clearest structural difference is in how each platform bills, so compare the models rather than today's numbers (both change their published prices, and you should check each provider's current pricing page before deciding).
Apify runs on a subscription plus compute units. You are effectively renting machine time: a light, fast run costs little, while a heavier crawl that uses more resources consumes more units. Storage and proxy usage can add to the bill as well. The model is flexible and fits complex, long-running workflows, but it can be harder to predict, because consumption depends on how efficient an actor is and is known mostly after the run. Note too that compute can be spent on a run that ultimately fails to return the data you wanted.
Crawlbase bills per successful request. One successful request equals one delivered page, raw HTML or JavaScript-rendered, and failed or blocked requests are not charged. Job size and bandwidth do not change the price of a delivered page; JavaScript-rendered requests simply cost more credits than plain ones. That makes spend easier to forecast across thousands of crawls, because you are only paying for results you actually received. You can start with 1,000 free requests and no credit card, and the published model is laid out in Crawlbase pricing explained, with live numbers on the pricing page.
Put simply: with Apify you pay for the resources your jobs consume; with Crawlbase you pay per delivered page. The compute-unit model is not a flaw, it is a different shape that rewards efficient, custom pipelines. If predictable, results-only billing is what you want, the per-success model is usually easier to reason about.
If the appeal of an alternative is fewer moving parts, the Crawling API is the API-first version of the job: send a URL and it rotates the IP, handles CAPTCHAs, renders the page when a browser is needed, retries blocks server-side, and returns the finished HTML or parsed data. No actors to design, and you pay only for successful requests. Start with 1,000 free, no credit card.
Reliability and scale
Once setup is handled, the real question is how each platform behaves as volume grows. Crawlbase publishes its own framing of throughput and reliability: close to 99% success on major sites and around 20 requests per second out of the box, with limits that can be raised for larger workloads. Those are Crawlbase's stated figures rather than an independent benchmark, and the only number that matters for you is the one you measure on your own targets. Proxy rotation, retries, and CAPTCHA handling are built in, so the service absorbs blocks and tries again server-side rather than handing the failure back to your code. For more on that approach, see how to scrape without getting blocked.
Apify scales through its actor model, which gives developers real power and control. Because actors run in containers that you configure, you also own more of the tuning: concurrency settings, batching, and proxy wiring are yours to manage, and complex or long-running jobs can need adjustment to stay consistent under heavy load. That control is exactly what some teams want; it is also more to operate. The honest summary is that Crawlbase optimizes for strong defaults with little tuning, while Apify optimizes for flexibility you steer yourself.
When Apify is the better choice
A fair comparison has to say where the other tool wins, and there are clear cases where Apify is the right call.
You want the actor marketplace. If a ready-made actor already exists for the exact site or task you need, Apify can get you to results faster than writing anything yourself. That library of community and official actors is a genuine advantage an API-first service does not replicate.
You are building reusable scrapers as a product. If your value lies in authoring scrapers, packaging them, scheduling them, and even publishing or selling them, Apify's platform is built for exactly that. The actor model, datasets, and orchestration layer are features, not overhead, when the pipeline itself is what you are creating.
You already have an Apify workflow. If your team has invested in actors, dataset structures, and integrations that work, the switching cost is real and the platform is doing its job. There is no reason to move a working pipeline just to change the billing shape.
In short, Apify is the stronger fit when the platform and its ecosystem are part of what you are buying. It is a capable, well-built product, and for builders who want to operate the whole pipeline, that depth is the point.
Final verdict: choosing the right fit
The choice comes down to how much of the stack you want to operate. If you want a platform to build, schedule, and reuse custom scraping pipelines, lean on a marketplace of pre-built actors, or ship scrapers as a product, Apify is a strong and mature choice. If you want finished pages from a single API call, with proxies, CAPTCHAs, rendering, and retries handled for you and billing tied to successful results, Crawlbase is likely the simpler fit.
The cleanest way to decide is to try both on your own hardest target. Apify's free tier lets you run an actor; Crawlbase's 1,000 free requests let you measure success rate and time-to-result on the same pages. Convert each to cost per successful request on your real workload, factor in how much setup and tuning each asked of you, and the right answer for your team will be clear. If you want to see how the API-first model handles your case, you can start free. For a broader view, our how to evaluate Crawlbase against alternatives guide lays out the same criteria you can apply to any vendor.
Key takeaways
- Apify is a full platform; Crawlbase is API-first. Apify centers on configurable actors and a marketplace; Crawlbase returns finished pages from a single endpoint.
- Setup is the main day-one difference. Apify asks you to pick or build and configure an actor; Crawlbase needs one request with a token and a URL.
- Compare pricing models, not numbers. Apify bills subscription plus compute units; Crawlbase charges only for successful requests, with 1,000 free to start. Check each provider's current pricing page.
- Apify wins when the platform is the point. The actor marketplace, building reusable scrapers as a product, or an existing Apify workflow are real reasons to choose it.
- Decide on your own target. Trial both on your hardest pages, convert to cost per successful request, and let your workload pick the fit.
Frequently Asked Questions (FAQs)
Is Crawlbase a good alternative to Apify?
For teams that want a simpler, API-first model it often is. Instead of designing and running actors, you send a URL to an endpoint and get the page back, with proxy rotation, CAPTCHA handling, rendering, and retries built in. If your priority is the data with the least setup, and predictable billing tied to successful requests, Crawlbase fits. If you want a platform to build and orchestrate pipelines, Apify may still be the better match.
How do Apify and Crawlbase differ in pricing?
They use different models. Apify charges a subscription plus compute units (machine time), with storage and proxy usage potentially adding to the bill, so cost depends on how resource-heavy your runs are. Crawlbase charges per successful request: one delivered page, with failed or blocked requests not billed, and JavaScript-rendered requests costing more credits than plain ones. Compare the models, and check each provider's current pricing page for live numbers.
When should I stay with Apify?
Stay with Apify when its platform is part of what you need: a ready-made actor already covers your target, you are building or publishing reusable scrapers as a product, or you have an existing workflow built on actors and datasets that works. In those cases the actor model and marketplace are genuine advantages, and the switching cost of moving a working pipeline is not worth it.
Does Crawlbase handle JavaScript-heavy sites?
Yes. The Crawling API can render pages in a real browser when a site builds its content with JavaScript, so single-page apps and dynamic listings return fully assembled HTML rather than an empty shell. Rendering is a parameter on the same endpoint, and rendered requests use more credits than plain ones. See crawling JavaScript websites for the mechanics.
How quickly can I get started with Crawlbase?
Usually within minutes. You sign up for a free account, get a token, and make a single API request with your target URL. There is no actor to author or deployment to manage, and the first 1,000 requests are free with no credit card required, which is enough to test success rate and time-to-result on your own pages.
Can I use Crawlbase for large-scale scraping?
Yes. Alongside the synchronous API, the async Crawler queues high-volume jobs and delivers results to your endpoint via webhook, with server-side retries on blocks. That removes the need to hold open thousands of live requests or manage concurrency by hand, which makes it well suited to large, ongoing crawls.
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