Apify vs ScrapingAnt: Which Web Scraping Platform Is Better?
Apify and ScrapingAnt represent two different ways to build a web-data pipeline. Apify is a programmable cloud platform where ready-made and custom “Actors” can crawl, parse, transform, store, and deliver data. ScrapingAnt is an API-first web-access service combining headless Chrome, rotating proxies, Markdown output, and prompt-based AI extraction.
Choose Apify when you want the entire workflow hosted together. Choose ScrapingAnt when your application already owns orchestration and storage and needs an uncomplicated fetching or extraction layer. This comparison uses current public pricing and documentation, separates API credits from compute costs, and avoids unsupported cross-provider speed or success claims.
Apify wins for complete automation; ScrapingAnt wins for lean API access and AI extraction
Apify is our overall choice for complex, recurring data products: it combines an enormous Actor ecosystem, custom JavaScript/Python code, schedules, webhooks, storage, and integrations. ScrapingAnt is more direct for retrieval: one API can return rendered HTML, clean Markdown, or AI-extracted JSON, and its entry plan matches Apify Starter’s $19 price.
Do not compare “credits” directly. One ScrapingAnt request can consume 1–125 credits before AI charges; Apify usage can include compute, proxy bandwidth, storage, transfer, and Actor pricing.

Table of Contents
At a glanceApify vs ScrapingAnt Comparison
| Category | Apify | ScrapingAnt | Edge |
|---|---|---|---|
| Core product | Programmable Actor/cloud automation platform | Managed browser, proxy, Markdown, and AI extraction API | Depends on architecture |
| Free access | $5 recurring monthly platform usage | 10,000 recurring monthly API credits; no card | ScrapingAnt for testing volume |
| First paid plan | $19/month + pay as you go | $19/month for 100,000 credits | Tie on commitment |
| Ready-made tools | 70,000+ Store tools advertised; listing-specific quality/pricing | General, Markdown, and AI extraction endpoints; no comparable scraper marketplace | Apify |
| Custom logic | Hosted JavaScript/Python Actors and crawler frameworks | Request parameters, custom JavaScript snippet, or prompt-defined extraction | Apify |
| Browser rendering | Actor-controlled Playwright/Puppeteer/Crawlee | Fresh managed Chrome by default; selector waits and custom JS | Control vs convenience |
| Structured output | Actor-defined datasets and schemas | Plain-English field description to typed JSON; Markdown/text endpoints | ScrapingAnt for generic AI extraction |
| Scheduling/storage | Native schedules, datasets, key-value stores, queues | Bring a scheduler and durable storage; integrations can trigger calls | Apify |
| Concurrency | 5/32/128/256 concurrent Actor runs by public plan | Website advertises no concurrency cap; error docs still define HTTP 409 for exceeded limit | Confirm sustained-volume policy |
| Billing unit | Dollars fund compute, proxies, transfer, storage, and Actor events/results | Credits by request mode plus character-based AI extraction cost | ScrapingAnt is easier to scenario-model |
The deciding differenceEnd-to-End Platform vs Focused Web-Data API
You want the complete workflow in one cloud
An Actor can discover pages, interact with a browser, parse records, transform them, store datasets, and notify another system. Tasks, schedules, webhooks, APIs, integrations, and Actor-to-Actor calls make Apify suited to recurring data operations rather than only retrieving pages.
The Store accelerates prototypes, but “70,000+ tools” does not mean standardized quality. Each listing can have a different owner, update cadence, output schema, and pricing model. Test the exact Actor with a capped sample.
See our detailed Apify review.
You want retrieval or extraction behind one API
ScrapingAnt’s general endpoint can return raw or browser-rendered HTML through rotating datacenter or residential routes. Separate endpoints turn pages into Markdown or extract requested fields into JSON. Your system normally owns URL discovery, job scheduling, validation, history, and downstream storage.
It also exposes proxy mode, an MCP server, Make and n8n integrations, and a GitHub Action. Proxy mode is a front end to the same API and pricing, but its documentation requires disabling SSL certificate verification—an important security review item.
See our ScrapingAnt review, ScrapingAnt vs Octoparse, and ScrapingAnt vs Scrape.do.
Costs decodedApify vs ScrapingAnt Pricing
Both services have a $19 entry plan, but the similarity ends there. Apify provides prepaid dollars spent across platform resources and Actor charges. ScrapingAnt provides credits whose consumption changes with browser mode, proxy type, Google targeting, and AI text volume.
| Plan | Monthly price | Included value | Execution/support | Notable limits |
|---|---|---|---|---|
| Apify Free | $0 | $5 usage | 5 concurrent runs; community | $0.20/CU; 16 GB max Actor RAM |
| Apify Starter | $19 + overage | $19 usage | 32 runs; chat | $0.20/CU; 64 GB RAM |
| Apify Scale | $199 + overage | $199 usage | 128 runs; priority chat | $0.16/CU; 256 GB RAM |
| Apify Business | $999 + overage | $999 usage | 256 runs; account manager | $0.13/CU; 512 GB RAM |
| ScrapingAnt Free | $0 | 10,000 credits | Self-service | Recurring monthly; no card |
| ScrapingAnt Enthusiast | $19 | 100,000 credits | Email; docs-only integration | No expert assistance listed |
| ScrapingAnt Startup | $49 | 500,000 credits | Priority email; code snippets | Expert assistance listed |
| ScrapingAnt Business | $249 | 3 million credits | Priority email; debug sessions | Custom pools/anti-bot; account manager |
| ScrapingAnt Business Pro | $599 | 8 million credits | Priority email/debug sessions | Custom pools/anti-bot; account manager |
| ScrapingAnt Custom | $699+ | 10 million+ | Priority/dedicated; onboarding | Contract-specific scope |
ScrapingAnt says unused credits do not roll into the next subscription period. Its site says a plan can be restarted immediately when credits run out. Apify’s unused monthly prepaid usage also expires; paid plans can enter overage subject to configured limits.
Monthly commitment on a shared $0–$999 scale
List price only. Included credits, platform usage, and outputs are not equivalent.
ScrapingAnt request-credit multipliers
Documented credits per successful API request
Before AI extraction’s character-based charge. Bars share a 0–125-credit scale.
ScrapingAnt’s default browser-rendered request with a datacenter proxy costs 10 credits. A simple non-browser request costs one; a simple residential request costs 25; browser rendering with residential routing costs 125. Google-domain requests using standard proxies cost 10. The response’s Ant-credits-cost header reports actual consumption, and unsuccessful/error responses are documented as free.
| ScrapingAnt plan | Simple datacenter (1) | Default rendered datacenter (10) | Simple residential (25) | Rendered residential (125) |
|---|---|---|---|---|
| Free — 10K | 10,000 | 1,000 | 400 | 80 |
| Enthusiast — 100K | 100,000 | 10,000 | 4,000 | 800 |
| Startup — 500K | 500,000 | 50,000 | 20,000 | 4,000 |
| Business — 3M | 3,000,000 | 300,000 | 120,000 | 24,000 |
Theoretical maximum successful requests if every call uses the same documented mode. These are not valid-record, speed, or success guarantees, and AI extraction consumes additional credits.
Apify’s main cost drivers
One Apify compute unit is 1 GB of memory for one hour. Current CU prices are $0.20 on Free/Starter, $0.16 on Scale, and $0.13 on Business. Other charges can include residential proxy traffic ($8/$8/$7.50/$7 per GB), transfer, storage operations, SERP/Unblocker products, and Store Actor events or results.
Capability mapFeatures and Developer Experience
| Capability | Apify | ScrapingAnt |
|---|---|---|
| Getting started | Run a Store Actor or build from JavaScript/Python templates | Call /v2/general, /v2/markdown, or /v2/extract |
| Browser control | Full crawler/browser code and custom dependencies | Managed Chrome, JS snippet, selector wait, cookies, headers, timeout |
| Proxy routing | Datacenter, residential, SERP, Unblocker; Actor-specific config | Datacenter/residential API modes, country selection, automatic rotation |
| Output | Actor-defined records plus dataset exports | HTML, page source, Markdown, plain text, or AI-extracted JSON |
| Scheduling | Native schedules, tasks, webhooks, API triggers | No comparable native scheduler documented; use Make, n8n, GitHub Actions, cron, or your app |
| Storage | Datasets, key-value stores, request queues | Response delivery; customer supplies durable storage/history |
| Agent access | Apify MCP and Actor ecosystem | MCP with HTML, Markdown, and text tools; same API credits |
| Integration modes | REST API, webhooks, SDKs, integrations, MCP | REST API, proxy port, MCP, Make, n8n, GitHub Action, Python/JS clients |
| Managed service | Custom solutions and professional services | Custom scraping engagements and contract plans |
Editorial product-fit profile
Qualitative decision aid based on documented product scope—not a performance benchmark.
Apify ScrapingAnt
Structured outputAI Extraction and LLM-Ready Data
ScrapingAnt’s /v2/extract endpoint accepts a URL plus a natural-language description such as “product title, price(number), reviews(list: author, rating, text)” and returns matching camelCase JSON. The model works from a Markdown transformation of the page, supports nested output, and can coerce requested types where possible.
That convenience has two caveats. First, the model may return null when it cannot find a field, so validate every property. Second, billing adds the underlying web-request cost to ceil((Markdown characters + output characters) / 30). A large page can therefore consume far more than the base 10-credit browser request. Test Markdown length before projecting cost.
Apify does not force a single extraction method. Actors can use deterministic selectors, target-specific APIs, custom code, or LLM-powered extraction. That is more flexible and auditable, but it requires choosing or building the workflow. ScrapingAnt’s prompt-to-JSON endpoint is faster to start when fields are known and occasional model variability is acceptable.
Evidence, not guessworkPerformance, Reliability, and Concurrency
No universal speed or success winner can be established from public specifications. Apify performance depends on Actor code, allocated memory, browser choice, proxy path, and target behavior. ScrapingAnt latency changes radically between a one-credit direct request, a managed Chrome session, residential routing, and AI inference.
ScrapingAnt’s current homepage says there is no concurrency cap on any plan and invites users to send 1,000 requests in parallel. A current documentation migration guide also says concurrent requests are not limited. However, the API error reference still defines HTTP 409 as “concurrent requests limit exceeded” and suggests upgrading. Treat “unlimited” as provider-advertised elastic capacity, load-test responsibly, and confirm sustained-volume behavior before designing around it.
ScrapingAnt advertises 3M+ rotating proxies. Its API proxy documentation lists 24 selectable countries and older pool figures, while its separately billed residential proxy product advertises 100+ countries. Do not assume standalone-proxy coverage automatically applies to API geotargeting; check the current API country list for your required location.
Best fitWhen Each Platform Makes More Sense
Apify is better for…
- Complex crawls: discovery, pagination, logins, browser interaction, transformations, and enrichment.
- Recurring business datasets: schedules, storage, exports, webhooks, and integrations together.
- Target-specific reliability: a maintained Store Actor may encode years of domain knowledge.
- Reusable internal tools: publish custom code behind an input schema and REST API.
- Auditable parsing: deterministic code when exact extraction behavior matters.
ScrapingAnt is better for…
- Existing applications: outsource browser/proxy infrastructure while keeping your pipeline.
- RAG and agents: retrieve clean Markdown/text through API or MCP.
- Flexible schemas: prompt the AI extractor for structured JSON without maintaining selectors.
- Burst workloads: provider-advertised parallel scaling without a plan concurrency ladder.
- Simple static retrieval: one-credit non-browser requests make large easy-site jobs economical.
Neither service removes your obligation to respect applicable law, privacy duties, contracts, and site controls. The neutral Robots Exclusion Protocol (RFC 9309) explains crawler directives but does not grant authorization. Developers can also consult the MDN Fetch API guide.
Buying frameworkHow to Run a Fair Pilot
- Create a representative target setInclude static, rendered, protected, geo-sensitive, long-text, paginated, and known-failure pages.
- Match the output schemaChoose an Apify Actor or custom parser and a ScrapingAnt extraction mode that produce the same required fields.
- Record actual meteringCapture Apify’s itemized run usage and ScrapingAnt’s
Ant-credits-costresponse header. - Validate contentReject block pages, consent screens, empty browser shells, duplicates, stale values, missing fields, and AI hallucinations.
- Increase concurrency graduallyMeasure error mix, target throttling, latency distribution, and data quality—not only accepted connections.
- Normalize total economicsInclude subscription, compute, proxy, storage, AI credits, retries, engineering time, monitoring, and maintenance per accepted record.
Trade-offsPros and Cons
Apify
Pros
- Complete programmable workflow
- Large Actor marketplace
- Custom JS/Python code
- Native schedules and storage
- Strong integration surface
Cons
- More concepts to learn
- Multi-part cost model
- Actor quality/pricing varies
- Unused monthly usage expires
- Paid overage needs controls
ScrapingAnt
Pros
- 10K-credit recurring Free tier
- HTML, Markdown, text, or AI JSON
- Failed requests documented as free
- Provider-advertised unlimited concurrency
- Low $19 paid entry point
Cons
- Bring scheduling and storage
- Rendered residential costs 125× base
- AI cost depends on text length
- Concurrency docs retain a 409 limit error
- Proxy Mode requires SSL verification off
FAQCommon Questions
Is Apify or ScrapingAnt cheaper?
Does ScrapingAnt charge for failed requests?
Ant-credits-cost header, and define your own content-validity checks.Does ScrapingAnt really allow unlimited concurrency?
Can ScrapingAnt replace an Apify Actor?
How many pages do 100,000 ScrapingAnt credits cover?
Which is better for AI agents and RAG?
Final verdictChoose Based on Workflow Ownership
Choose Apify when you want one platform to host the crawler, custom logic, schedules, storage, and delivery. Its broader ecosystem and orchestration make it our overall winner for building a reusable production data workflow.
Choose ScrapingAnt when your own application remains the pipeline and you need managed Chrome, rotating proxies, clean Markdown, or prompt-to-JSON extraction. It is especially attractive for simple API integration, RAG workloads, and bursty retrieval.
The practical winner is the service with the lower total cost per accepted record on your targets. Test both with identical validation and retry rules before committing.
Disclosure: This article contains affiliate links. We may earn a commission if you purchase through them, at no extra cost to you. Pricing and limits change; verify checkout and test your targets. Provider-reported service figures were not independently benchmarked.
Sources & comparison methodology
Research checked September 17, 2026. We reviewed current public pricing and documentation, compared only like units, labeled provider claims, and removed unsupported performance charts from the old article. No paid checkout, contract review, or controlled cross-provider benchmark was performed.
Price bars show monthly commitment, not equivalent capacity. Credit charts and request-capacity tables are arithmetic based on documented modes, not predicted output. The radar is an explicitly editorial fit visualization.






