Scrape.do vs Apify: Pricing, Extraction and Workflow Features Compared

Platform Overview and Quick Comparison

The key distinction is where the collection job lives. With Scrape.do, your client requests data and your application usually owns validation, persistence and recurring execution. With Apify, an Actor can own the crawl, parser and output dataset while the platform runs it. A Store Actor can reduce custom coding, but its actual quality, pricing and input requirements depend on the listing.

STRONG FIT: RETRIEVAL FOR AN EXISTING APPLICATION

Scrape.do

Scrape.do provides proxy routing, managed anti-bot handling and JavaScript rendering through API requests. Its current Ready APIs add parsed output for supported sites, so it is broader than an HTML-only gateway. See our Scrape.do review for a detailed product walkthrough.

• Credit-based managed retrieval
• Rendering and browser interactions
• Supported structured Ready APIs
• Independent async request pool

Show Pros & Cons Explore Scrape.do Plans

STRONG FIT: COMPLETE HOSTED COLLECTION WORKFLOWS

Apify

Apify runs ready-made or custom Actors with cloud resources, platform storage and scheduling. It can host a complete pipeline or expose the result through its API. Our Apify review explains Actors, storage and usage billing.

• Ready-made and custom Actors
• JavaScript and Python development
• Tasks, schedules and webhooks
• Datasets, queues and key-value stores

Show Pros & Cons Explore Apify Plans

Quick Verdict: Which Platform Fits Your Project?

Neither recommendation establishes a measured performance winner. First define the permitted targets, required fields, freshness, location, volume and delivery destination. Then choose which parts you want to maintain yourself. A low-priced retrieval response has limited value if you still need substantial extraction work; a hosted Actor has limited value if its schema or behavior does not fit the job.

Pricing: Plans, Credits and Workload Costs

All prices below are public USD offers. Taxes, negotiated terms and account-specific charges are excluded. Compare minimum spend separately from actual usage and accepted output. Scrape.do credits are a response-billing unit; Apify prepaid dollars cover applicable usage. They cannot be treated as equivalent numbers of pages.

Scrape.do advertises core proxy, rendering, browser-interaction and targeting features across plans. Higher tiers add volume, concurrency and support capabilities: Business lists teams and dedicated support; Advanced lists custom WAF strategies, SLA and Slack support. Requests stop when monthly credits are exhausted unless you upgrade or buy more credits. Confirm rollover, extra-credit validity and annual allocation rather than assuming all unused balances persist.

Annual Scrape.do pricing: calculate the actual discount

The public annual totals are $290 for Hobby, $990 for Pro, $2,490 for Business and $6,990 for Advanced. These equal ten monthly payments for twelve months, or a 16.67% saving against twelve monthly payments. The monthly equivalents are $24.17, $82.50, $207.50 and $582.50, paid annually. The page’s broader “up to 20%” wording should not replace those totals. Annual switching is arranged through support; confirm invoice, renewal and allocation timing.

The subscription includes the listed prepaid usage; it is not the subscription plus the same allowance charged again. Monthly prepaid usage expires rather than rolling over. Annual billing advertises a 10% discount, and the current subscription guidance permits annual prepaid usage across the annual period. Some older help text still lists 32 GB for Starter; this comparison follows the current pricing table’s 64 GB and recommends checking the account if that capacity is important.

Scrape.do: turn credits into realistic response capacity

At full utilization, Hobby’s calculated price is $0.116 per 1,000 credits. Multipliers turn that into $0.116 per 1,000 ordinary datacenter responses, $0.58 for rendered datacenter, $1.16 for residential/mobile and $2.90 for rendered residential/mobile. These are theoretical capacities, excluding special domains and parser rejection. A job needing 100,000 rendered residential responses at 25 credits would consume 2.5 million credits; Hobby is therefore too small even though it advertises 250,000 credits.

Named domains can have automatic profiles or higher costs. Current examples include Google at 10 credits, LinkedIn at 30, Air Canada at 75 and Shopee at 100; some targets require support. Amazon has a one-credit route through a structured API, which can change the response type expected by an existing HTML parser. Reconcile using Scrape.do-Request-Cost and the remaining-credit header rather than assuming the default mode covers every site.

Apify: distinguish Actor events from resource usage

A pay-per-usage Actor charges platform resources without a separate developer fee. A pay-per-event Actor defines billable events such as starts or delivered results. Many event prices include resources, while some charge resources separately. Read the live listing: adding compute and proxy charges already included in an event price double-counts the cost. Dataset access after a run can still incur platform usage.

Apify’s rental retirement documentation sets October 1, 2026 as the full sunset, with remaining rentals moving to usage pricing. Some public overview pages retain rental wording. Do not forecast a new job using an old monthly rental fee without checking the actual listing and account. Similarly, a marketplace result price is not a universal platform price for all targets.

One compute unit equals 1 GB of allocated RAM for one hour. A 2 GB, 30-minute run therefore uses one CU: $0.20 at Starter’s rate. Allocating more memory can help a browser-heavy job but increases the compute rate; faster completion may or may not offset that increase. Other meters can dominate the invoice, so optimize using itemized run usage.

These are platform meters, not charges that must all apply to every Actor. Included datacenter IP counts also differ by plan, and Free-plan Apify Proxy is limited to use within Apify. Review the Actor’s proxy configuration and pricing model before adding a proxy estimate to an event-based quote. Storage time and operations are additional considerations; record counts alone do not establish operation counts because batching affects usage.

The donut assumes one CU at $0.20, 0.25 GB residential traffic at $8/GB, 10,000 dataset write operations at $0.005 per 1,000 and 0.10 GB external transfer at $0.20/GB. The sum is $2.27, before any separate Actor event fee or other meters. Thirty identical runs would cost $68.10. With Starter’s $19 prepaid usage, that simplified case uses the included $19 plus $49.10 additional usage; it does not add another $19 to $68.10.

Compare cost per accepted record

Use total provider charges divided by accepted records, multiplied by 1,000. Then add the engineering cost that matters to your team: parser maintenance, orchestration, storage and incident handling. A hypothetical $29 retrieval job yielding 8,000 accepted records costs $3.63 per 1,000 accepted records before your downstream costs. That is a planning example, not measured Scrape.do output or evidence that the illustrative Apify run performs the same job.

Extraction, Storage and Workflow Features

Scrape.do now includes structured endpoints

The Ready API catalog covers supported ecommerce, search, maps and travel targets with target-specific JSON. Amazon, Walmart, Google Search, Google Shopping, YouTube and Google Maps are examples. Validate the particular endpoint’s fields, pagination and geographic behavior; catalog breadth does not guarantee that every variation of a site is supported. The catalog’s 1–10-credit headline also has exceptions, including a Gemini row at 25 credits.

Generic rendered returnJSON exposes browser network/XHR/Fetch information; it is not a universal parser for arbitrary product fields. Markdown output is a conversion format, not proof that a page contains complete or correct records. Choose a Ready API when its schema fits, and keep a parser for other targets when your application needs structured fields.

Apify provides the workspace around extraction

Datasets hold structured items, key-value stores hold arbitrary objects and request queues coordinate crawl requests. Actors can be launched manually, through API calls, saved tasks, schedules, webhooks or other Actors. This supports a broader pipeline, including transformations and downstream delivery, but those components still need configuration and validation.

Retention is not the same as a permanent backup. Named storage objects can be exempt from automatic retention deletion while unnamed objects follow plan rules; paid retention is configurable, and Free has special recent-run rules. Confirm retention and ongoing storage charges, export governed data to your own destination when required, and test recovery rather than relying on a successful run alone.

Performance and Concurrency: Compare the Right Units

This article does not claim a measured response-time, success-rate or uptime advantage. Scrape.do’s advertised network and success figures are provider claims, while Apify results depend on the Actor, code and resources. A marketplace count or proxy pool total does not establish the quality of your target-specific output.

Requests, Actor runs and browser workers are different limits

Scrape.do Hobby permits 10 simultaneous main requests plus a separate three-slot async pool. Both consume the same subscription credits. Apify Starter permits 32 simultaneous Actor runs within its total RAM limit, and each Actor can have its own internal request/browser concurrency. Thirty-two runs are not thirty-two retrieval slots, and ten retrieval slots are not ten requests per second. Duration, retries, target limits and configured resource use determine throughput.

Use the same permitted targets, required schema, region, volume and time windows. Separate the Ready API from generic HTML tests and compare the exact Actor you intend to deploy. Start at low concurrency, use finite timeouts and retry limits, and repeat the pilot across several windows before making a recurring commitment.

Rendering, Proxy Routing and Anti-Bot Handling

Scrape.do advertises managed proxy rotation, header/user-agent handling, CAPTCHA handling and browser rendering. Use the least expensive mode that produces valid output on a permitted target. Turning on rendering or residential routing by default can consume substantially more credits, while turning it off on a dynamic page may omit the content you need.

Ordered browser actions can include clicks, fills, scrolling and waits. Prefer a specific readiness condition over a long blind delay. Resource blocking can reduce transferred work but can also remove scripts or requests needed to populate fields. Sticky sessions help related requests share context, but the documented session closes after five minutes of inactivity and can be replaced on failure. It is not a permanently reserved IP.

Country and postal targeting have configuration requirements; postal/ZIP controls need the relevant residential setting and country code. Validate the rendered currency, language and location as well as the reported IP. A mobile user agent is not proof of a mobile-carrier exit address, and broad network coverage does not establish live availability in a particular city.

On Apify, the chosen Actor controls browser strategy, proxy groups, sessions and retries, potentially using platform proxy or unblocker services. A third-party Actor can implement these well or poorly. Inspect its inputs, maintenance history and sample output, then measure resource usage on a capped run. Neither platform changes your authorization to access a target, and neither makes a permanent “never blocked” guarantee established by this comparison.

Developer Integration and Operational Design

Keep credentials and execution limits deliberate

Call either service from a backend rather than exposing tokens in a public browser bundle. Store credentials in environment variables or a secret manager, redact them from logs and use separate credentials where practical. Client timeout should leave enough time for the service response; retry only bounded, appropriate failures. Record each job’s identifier and billing metadata so a failed delivery does not trigger uncontrolled duplicate work.

Scrape.do’s synchronous request uses its API token and target parameters; async uses an X-Token header, job submission, polling or webhooks. The async pool is independent of main concurrency, but not of credits. Async results are temporary: retrieve before the returned expiry information and save to your own storage. A webhook receiver should validate the expected event, handle duplicate delivery and persist completion state before launching downstream work.

Apify’s APIs and JavaScript/Python clients support runs and datasets, but method names and return shapes are version-specific. Match the installed SDK to its documentation. A wait duration governs how long the caller waits; a runtime limit governs the job itself. A maximum item count is not a universal spend cap, and an event-charge limit does not necessarily cover all resource meters. Review the actual billing model before assuming a limit protects the whole invoice.

Combining both platforms is possible

An Apify Actor can use an external HTTP retrieval service such as Scrape.do when its code and network access allow it. This can combine hosted orchestration with managed retrieval, but it creates two bills and two sets of limits. Avoid paying for redundant browser/proxy work around an already rendered response. Keep the external key isolated and compare the combined cost against a single-platform design before adopting it.

Use Cases and Practical Tradeoffs

For ecommerce, define product variants, currency, availability and timestamps; a price without location context can be misleading. For search data, define locale, pagination, rank and organic/ad distinctions. For AI-ready content, evaluate text completeness and provenance, not only whether Markdown was returned. For recurring datasets, establish stable identifiers and deletion/update handling before increasing collection volume.

A maintained endpoint or Actor can shorten initial development, but your output contract should remain under your control. Keep representative validation fixtures, track schema drift and reject incomplete records explicitly. An automated job that completes successfully can still deliver a dataset that no longer meets the business requirement.

Support, Trials, Cancellation and Security

Try the actual workload within the free allowance

Scrape.do advertises 1,000 monthly free credits with no credit card required and core features available. At a standard 25-credit rendered residential cost, that supports only 40 billable responses, before domain-specific differences. Apify Free includes $5 monthly usage; how far it goes depends on the Actor, resources and event charges. These free offers are useful for checking setup and a small output sample, not proving a production workload.

Support depends on plan and product

Scrape.do tiers list email, priority email, dedicated and Slack support at increasing levels. Apify moves from community support on Free to chat, priority support and an account manager on paid tiers. SLA and enterprise commitments need a contract-specific check. We did not test support timing, and testimonials or advertised response averages are not independent comparisons. Ask a concrete question about your target, billing or failure handling during the pilot.

Control renewal and overage

Scrape.do’s subscription terms describe automatic renewal and cancellation through the account or support. Initial refunds have a three-day window and apply to unused credits under conditions; successful used credits are excluded and payment commissions may be deducted. Renewal-related exceptions have their own timing and conditions. The no-card Free offer should not be confused with a separate trial that requests payment details or converts automatically.

Apify paid plans can continue into overage after prepaid usage, subject to configured limits. The help documentation warns that estimated spend may deviate by up to 10%, so an account limit should not be treated as a precise real-time invoice ceiling. Check the Console’s meaning of prepaid spend, allowed overage and maximum limit. Overage invoicing can also occur before month end at applicable thresholds; do not assume every charge waits for a single monthly invoice.

Actor permissions are part of the integration

Review third-party Actor code and permissions when it handles credentials or sensitive data. Apify’s schedule documentation says scheduled runs receive an unscoped run token, regardless of the token scope used to create the schedule. A restricted setup token therefore does not establish restricted runtime access. Plan account/data isolation around the actual runtime behavior, and review trusted code before scheduling it.

Apify documents SOC 2 Type II compliance, but this article does not audit its report or certify individual Actors. Neither provider’s security statements remove your responsibility for lawful collection, secrets, retention and data quality. The IETF Robots Exclusion Protocol specifies robots.txt handling and states that its rules are not access authorization. Review target permissions, contractual terms and privacy requirements alongside technical access.

Strengths and Limitations

The expandable provider cards summarize these tradeoffs. Neither platform gets an invented numerical “ease of use” or “value” score here. Those judgments depend on whether you already have a pipeline, whether a supported endpoint matches your schema, and how much custom work the job requires.

An Evidence-Based Decision Matrix

If both pass your output checks, compare the full monthly cost and operational effort. If one fails the required schema or access permissions, a cheaper nominal unit rate does not compensate. If a feature is essential, request proof for the selected endpoint or Actor rather than relying on a general product feature list.

Purchase and Migration Checklist

Choose Scrape.do when your application mainly needs managed retrieval or a matching Ready API. Choose Apify when the project benefits from hosted Actors, custom crawling, platform storage and scheduling. In both cases, scale from measured output and current billing rather than an advertised success percentage.

For another platform comparison, read Octoparse vs Scrape.do. Our ScraperAPI vs Apify comparison and ScrapingAnt review provide additional API and workflow context.

Frequently Asked Questions