Apify Review: Pricing, Actors, Features & Real Costs

Apify at a glance

What are Apify Actors?

An Actor is a cloud program packaged to accept structured input, run a job, and return data or perform an automation. Some Actors crawl a specific website; others are general browser, HTTP, AI, transformation, or integration tools. You can run an Actor manually, through a saved task, on a schedule, from another Actor, via webhook, or through the API.

The Store removes much of the initial engineering when a maintained Actor already matches the target. It does not eliminate due diligence. Community developers control their own code and pricing, and a site change can affect a scraper. Review the maintainer, update history, input/output schema, issue handling, pricing section, and sample run before treating a Store listing as production infrastructure.

Archived provider screenshot from the supplied image list. Current pricing and capabilities are described from official pages checked for this review.

Apify features and workflow components

For developers, the platform’s API and SDKs are the connective tissue. A typical run receives input from a key-value store, takes URLs from a request queue, writes records to a dataset, and signals completion through a webhook. The MDN Fetch API guide is a useful neutral reference for the request/response foundation beneath many custom HTTP workflows.

Apify pricing plans

Apify uses a prepaid-usage model. Each subscription price is also the included platform credit for that billing period: $5 on Free, $19 on Starter, $199 on Scale, and $999 on Business. Paid plans continue into pay-as-you-go overage when enabled within billing limits. Free usage stops when the $5 credit is exhausted. Monthly credits expire; they do not roll into the next monthly period.

Proxy and managed-access rates

Selected storage and transfer prices

How Actor pricing actually works

Two Actors performing similar tasks can have different billing logic. The platform pricing page describes pay-per-event and pay-per-usage models, and Apify documentation still records rental Actors during the scheduled retirement period. Always inspect the Actor’s own Pricing tab.

Store discounts are shown by subscription tier rather than one universal percentage: Starter receives Bronze, Scale Silver, and Business Gold treatment where applicable. The exact Actor price and discount belong to that Actor’s live pricing page.

Estimating the real cost of Apify

For pay-per-usage Actors, compute is memory multiplied by run duration. A run using 2 GB for 30 minutes consumes 1 CU. At $0.20/CU that compute portion is $0.20; at $0.16 it is $0.16. Add residential traffic, external transfer, storage, and operations. For pay-per-event Actors, begin with event charges and add platform use only if the Actor says it is separate.

This example is arithmetic, not an Apify quote or benchmark. A real run can use different memory, time, traffic, storage, event charges, retries, and discounts. The lesson is that a cheap CU does not make proxy-heavy scraping cheap, and a low event rate can still become costly if it bills every returned item.

A practical Apify evaluation workflow

1. Define the permitted target and output. Write down required fields, refresh schedule, geography, acceptable error rate, retention and deletion rules.
2. Compare Actors, not only names. Check the developer, maintenance history, issues, input schema, output sample, pricing model and whether platform use is included.
3. Cap a small run. Limit pages, items, depth, duration, memory and retries. Use the free credit only for representative testing.
4. Validate output. Measure complete, schema-valid, deduplicated records. A run marked “succeeded” does not guarantee useful data.
5. Inspect billing. Record event charges, CUs, proxy GB, transfer, storage, and operations. Forecast from actual consumption.
6. Secure integrations. Use the narrowest practical token access, rotate credentials, and avoid exposing secrets in Actor input or logs.
7. Add schedules and webhooks. Prevent overlapping jobs, handle duplicate delivery, and make downstream processing idempotent.
8. Set monitoring and budget controls. Alert on run failure, empty datasets, schema drift, unusually high traffic and approaching platform limits.

Performance, reliability and security

The old article used universal success, uptime, response-time and accuracy figures without a reproducible test. Those claims have been removed. Apify performance depends on the Actor, target, browser engine, memory, proxy, concurrency, request policy, output size and developer maintenance. A marketplace-wide speed score would hide those differences.

On security, current documentation states that Apify is SOC 2 Type II compliant and describes tenant isolation, secret and data protection, a shared-responsibility model, vulnerability disclosure, and a Trust Center. That is meaningful evidence, but teams should still request the applicable report, review subprocessors and retention, configure scoped access, and assess their own Actor code.

What Apify is good for

Apify is often overkill for a one-off static page that a short local script can fetch reliably. It becomes more valuable when a job needs managed execution, recurring schedules, browser rendering, proxy routing, reusable storage, or a maintained Store Actor.

Apify alternatives and comparison

Compare Apify with the kind of tool your team actually wants. A visual desktop scraper, a request API, and a programmable cloud marketplace solve different operational problems. Our best web scraping tools guide provides a broader selection framework, while the proxy provider guide focuses on raw network access.

Apify FAQ

Should you use Apify?

Choose Apify when the value of a ready-made Actor or a managed Actor runtime outweighs the complexity of multi-part usage pricing. It can shorten the path from an idea to a scheduled, API-accessible data workflow, and it gives developers a strong base for custom automation without assembling compute, queues, storage, proxy routing and event delivery separately.

Start with the Free plan and one constrained, representative run. Confirm the Actor pricing model, inspect itemized usage, validate output, test failure handling, and calculate cost per accepted record. Move to Starter, Scale or Business when the workload needs its concurrency, memory, proxy rates, support, Store discount or training—not simply because the included credit is larger.