Apify vs ScrapingAnt: Which Web Scraping Platform Is Better?

By  |  Updated: September 25, 2026  |  ~20 min read

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.

Quick verdict

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.

$19Entry paid price for both Apify Starter and ScrapingAnt Enthusiast
10KRecurring monthly credits on ScrapingAnt’s card-free Free plan
10Credits for ScrapingAnt’s default rendered datacenter request
125Credits for rendered Chrome with a residential proxy

Apify vs ScrapingAnt web scraping platform comparison

Table of Contents

At a glanceApify vs ScrapingAnt Comparison

CategoryApifyScrapingAntEdge
Core productProgrammable Actor/cloud automation platformManaged browser, proxy, Markdown, and AI extraction APIDepends on architecture
Free access$5 recurring monthly platform usage10,000 recurring monthly API credits; no cardScrapingAnt for testing volume
First paid plan$19/month + pay as you go$19/month for 100,000 creditsTie on commitment
Ready-made tools70,000+ Store tools advertised; listing-specific quality/pricingGeneral, Markdown, and AI extraction endpoints; no comparable scraper marketplaceApify
Custom logicHosted JavaScript/Python Actors and crawler frameworksRequest parameters, custom JavaScript snippet, or prompt-defined extractionApify
Browser renderingActor-controlled Playwright/Puppeteer/CrawleeFresh managed Chrome by default; selector waits and custom JSControl vs convenience
Structured outputActor-defined datasets and schemasPlain-English field description to typed JSON; Markdown/text endpointsScrapingAnt for generic AI extraction
Scheduling/storageNative schedules, datasets, key-value stores, queuesBring a scheduler and durable storage; integrations can trigger callsApify
Concurrency5/32/128/256 concurrent Actor runs by public planWebsite advertises no concurrency cap; error docs still define HTTP 409 for exceeded limitConfirm sustained-volume policy
Billing unitDollars fund compute, proxies, transfer, storage, and Actor events/resultsCredits by request mode plus character-based AI extraction costScrapingAnt is easier to scenario-model

The deciding differenceEnd-to-End Platform vs Focused Web-Data API

Choose Apify

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.

Choose ScrapingAnt

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.

PlanMonthly priceIncluded valueExecution/supportNotable limits
Apify Free$0$5 usage5 concurrent runs; community$0.20/CU; 16 GB max Actor RAM
Apify Starter$19 + overage$19 usage32 runs; chat$0.20/CU; 64 GB RAM
Apify Scale$199 + overage$199 usage128 runs; priority chat$0.16/CU; 256 GB RAM
Apify Business$999 + overage$999 usage256 runs; account manager$0.13/CU; 512 GB RAM
ScrapingAnt Free$010,000 creditsSelf-serviceRecurring monthly; no card
ScrapingAnt Enthusiast$19100,000 creditsEmail; docs-only integrationNo expert assistance listed
ScrapingAnt Startup$49500,000 creditsPriority email; code snippetsExpert assistance listed
ScrapingAnt Business$2493 million creditsPriority email; debug sessionsCustom pools/anti-bot; account manager
ScrapingAnt Business Pro$5998 million creditsPriority email/debug sessionsCustom pools/anti-bot; account manager
ScrapingAnt Custom$699+10 million+Priority/dedicated; onboardingContract-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.

Apify Starter$19
Ant Enthusiast$19
Ant Startup$49
Apify Scale$199
Ant Business$249
Ant Business Pro$599
Ant Custom$699+
Apify Business$999

ScrapingAnt request-credit multipliers

Documented credits per successful API request

Before AI extraction’s character-based charge. Bars share a 0–125-credit scale.

1Simple + datacenter
2Browser raw source
10Rendered DC / Google
25Simple residential
50Browser, altered source mode
125Rendered residential

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 planSimple datacenter (1)Default rendered datacenter (10)Simple residential (25)Rendered residential (125)
Free — 10K10,0001,00040080
Enthusiast — 100K100,00010,0004,000800
Startup — 500K500,00050,00020,0004,000
Business — 3M3,000,000300,000120,00024,000

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.

Separate product warning: ScrapingAnt also sells standalone datacenter and residential proxies billed by bandwidth. Those proxy plans, pools, country coverage, and per-GB prices are not the same as Web Scraping API credits. This comparison uses the API plans unless explicitly stated.

Capability mapFeatures and Developer Experience

CapabilityApifyScrapingAnt
Getting startedRun a Store Actor or build from JavaScript/Python templatesCall /v2/general, /v2/markdown, or /v2/extract
Browser controlFull crawler/browser code and custom dependenciesManaged Chrome, JS snippet, selector wait, cookies, headers, timeout
Proxy routingDatacenter, residential, SERP, Unblocker; Actor-specific configDatacenter/residential API modes, country selection, automatic rotation
OutputActor-defined records plus dataset exportsHTML, page source, Markdown, plain text, or AI-extracted JSON
SchedulingNative schedules, tasks, webhooks, API triggersNo comparable native scheduler documented; use Make, n8n, GitHub Actions, cron, or your app
StorageDatasets, key-value stores, request queuesResponse delivery; customer supplies durable storage/history
Agent accessApify MCP and Actor ecosystemMCP with HTML, Markdown, and text tools; same API credits
Integration modesREST API, webhooks, SDKs, integrations, MCPREST API, proxy port, MCP, Make, n8n, GitHub Action, Python/JS clients
Managed serviceCustom solutions and professional servicesCustom scraping engagements and contract plans

Editorial product-fit profile

Qualitative decision aid based on documented product scope—not a performance benchmark.

Apify and ScrapingAnt product-fit radar Apify is stronger in ecosystem, orchestration, storage, and extensibility. ScrapingAnt is stronger in retrieval simplicity and generic AI extraction. Ready ecosystemAPI simplicity AI extractionBuilt-in storage OrchestrationExtensibility

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

  1. Create a representative target setInclude static, rendered, protected, geo-sensitive, long-text, paginated, and known-failure pages.
  2. Match the output schemaChoose an Apify Actor or custom parser and a ScrapingAnt extraction mode that produce the same required fields.
  3. Record actual meteringCapture Apify’s itemized run usage and ScrapingAnt’s Ant-credits-cost response header.
  4. Validate contentReject block pages, consent screens, empty browser shells, duplicates, stale values, missing fields, and AI hallucinations.
  5. Increase concurrency graduallyMeasure error mix, target throttling, latency distribution, and data quality—not only accepted connections.
  6. 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?
Both start at $19, but their units differ. ScrapingAnt can be inexpensive for simple datacenter requests and costly for rendered residential or AI extraction. Apify cost depends on resources, proxies, storage, transfer, and Actor pricing. Compare cost per validated record.
Does ScrapingAnt charge for failed requests?
Its current product pages and documentation say unsuccessful/error responses cost zero credits. Inspect the response and Ant-credits-cost header, and define your own content-validity checks.
Does ScrapingAnt really allow unlimited concurrency?
The homepage and a current migration guide say there is no cap, but the error reference still documents HTTP 409 for exceeding a concurrent-request limit. Confirm sustained-volume terms and load-test before relying on unlimited throughput.
Can ScrapingAnt replace an Apify Actor?
It can replace page retrieval and sometimes parsing through Markdown or AI extraction. Your application still normally needs URL discovery, scheduling, validation, durable storage, and downstream orchestration.
How many pages do 100,000 ScrapingAnt credits cover?
At documented base modes: up to 100,000 simple datacenter requests, 10,000 default rendered datacenter requests, 4,000 simple residential requests, or 800 rendered residential requests. AI extraction adds character-based credits, and usable-record counts depend on validation.
Which is better for AI agents and RAG?
ScrapingAnt is convenient for direct Markdown/text through MCP or API. Apify offers a broader ecosystem of Actors, custom processing, storage, and agent integrations. Choose based on whether you need a retrieval tool or an orchestrated data pipeline.

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.

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