Actor execution platform · verified 2 September 2026
Monocrawl vs Apify
A maintained social-data product versus a platform for building and running web-automation Actors.
Product boundary
Choose Apify for custom extraction, Actor hosting, datasets, and workflow automation. Choose Monocrawl when supported sources should share one maintained contract with Research and Monitors above it.
The boundary decision
Do you need finished data—or somewhere to run code?
Monocrawl supplies a maintained social-data contract. Apify supplies the runtime, Store, and storage primitives for Actor workloads.
Monocrawl
Choose Monocrawl to consume normalized data
You need supported social and public-web sources to share one envelope, entity model, credit ledger, evidence-linked Research, and subject Monitors.
Apify
Choose Apify to build or run automation
You need a Store Actor or custom program, controllable resources and schedules, and run-scoped datasets beyond a curated API surface.
What changes in the application
The Actor is the integration boundary
Apify standardizes execution and output storage. Each Actor still defines its inputs, fields, and consumption.
- 01
Choose the capability
Use the catalogue’s platform endpoint.
- 02
Call one contract
Send the same key and receive the same outer envelope.
- 03
Reuse normalized entities
Add a supported source without adopting another Actor schema or lifecycle.
- 04
Move up the stack
Create a saved Research report or recurring subject Monitor in the same product.
- 01
Find or build an Actor
Evaluate a Store Actor and publisher, or deploy private code on a runtime you control.
- 02
Read its contract and price
Inspect its input/output schemas, version, documentation, and billing model.
- 03
Run and observe it
Send JSON, choose synchronous or asynchronous execution, and monitor status, resources, and failures.
- 04
Retrieve and map output
Read and normalize the default dataset, then connect schedules, webhooks, or downstream Actors.
Request anatomy
An Actor call introduces a run and dataset boundary
Apify standardizes execution APIs. The Actor ID and JSON body select the program; longer jobs are read from the run dataset.
GET /v1/reddit/search?query=standing+desk X-API-Key: mn_live_… → Monocrawl envelope + normalized item fields
POST https://api.apify.com/v2/actors/{actorId}/runs
Authorization: Bearer …
Content-Type: application/json
{ /* Actor-specific JSON input */ }
→ data.id + data.defaultDatasetId
GET /v2/datasets/{datasetId}/items?format=jsonSimplified documented patterns only. `{actorId}` and `{datasetId}` are placeholders; the workloads and responses are not presented as equivalent.
Product boundary
Finished social data versus execution primitives
Both can return public-web data. Apify asks your team to choose or build the extraction program and operate its run and dataset lifecycle.
Pricing
A platform plan is not an Actor price
Apify combines prepaid usage, resource rates, and Actor-specific pricing. Estimate from a test run because compute, proxies, storage, transfer, retries, and Store charges vary by workload.[6][7][8]
Monocrawl
One balance; endpoint prices are published in credits and current pack values come from the live pricing configuration.
Platform plans
As verified on 2 September 2026: Free includes $5 prepaid usage; Starter is $19/month at $0.20/CU; Scale is $199/month at $0.16/CU; Business is $999/month at $0.13/CU.
Store pricing
An Actor page can charge pay per event or only the platform resources it consumes. Legacy rentals remain in a documented sunset until 1 October 2026.
Do not compare
One CU is 1 GB of allocated RAM for one hour; it is not one record. Proxy traffic, storage operations, data transfer, retries, and post-run dataset reads can also affect cost.
Current Monocrawl Hobby pack: £15 for 3,000 credits. This value is rendered from the pricing configuration, not comparison copy.
Where each model earns its keep
Standardization on one side, programmability on the other
The right choice follows from how much of the extraction runtime your team wants to own.
Choose the maintained data layer
Monocrawl removes the runtime boundary
- A canonical social/web contract instead of Actor-specific input and output models.
- No Store selection, Actor versioning, runtime sizing, or dataset lifecycle to own for supported capabilities.
- Research and subject Monitors are product workflows rather than pipelines assembled from execution primitives.
- One endpoint credit ledger makes the supported surface easier to quote inside an application.
Choose the programmable runtime
Apify makes the runtime the product
- Custom Actors can run arbitrary scraping, browser automation, data processing, and multi-step workflows.
- Public and private Actors let teams buy a maintained component or own the implementation and runtime.
- Datasets, schedules, webhooks, resource controls, and monitoring form a capable automation platform.
- REST, API clients, CLI, and MCP support applications, developers, and agents through several integration modes.
Leaving an Actor workflow
Moving a supported social workload off Actors
Treat this as a program-and-schema migration, not a token swap. Keep the Actor live until representative records and operations match the application.
- 01Inventory Actor IDs and versions, task inputs, schedules, webhooks, exports, monitors, proxies, and pricing models.
- 02Map Actor inputs and outputs to supported Monocrawl endpoints; never assume Store Actors share a schema.
- 03Reprice actual run usage, Actor events, proxies, transfer, storage, retries, and dataset reads.
- 04Dual-run representative inputs; compare fields, pagination, freshness, failures, retention, and completion time.
- 05Retain Apify for custom programs, arbitrary sites, browser automation, and work outside Monocrawl’s supported surface.
Operating ownership
Which team owns the extraction layer?
Monocrawl fits teams that want supported sources to behave like product APIs. Apify fits teams prepared to select, build, and operate the programs themselves.
Consume a maintained data product
- Application teams consuming several supported social or public-web sources
- Builders who want normalized entities without selecting and operating Actors
- Products that also need saved research or recurring subject monitoring
- Teams that prefer one endpoint ledger for the supported surface
Operate a programmable extraction stack
- Engineers building custom scraping or browser-automation programs
- Teams that deliberately want to choose each Store Actor and its trade-offs
- Data pipelines that need scheduled runs, datasets, webhooks, and composition
- Developers distributing or monetizing their own web automation
Actor decisions
Questions to settle before replacing an Actor
The important questions are scope, schema, scheduling, and full-run cost—not whether both products can return JSON.
Is Monocrawl a replacement for all of Apify?+
No. Apify is a general Actor runtime and marketplace for scraping, browser automation, processing, and custom workflows. Monocrawl can replace only the supported social/public-web portion whose coverage and fields match the application.
Does Apify normalize all Store Actor output?+
Apify standardizes execution and dataset access, but Actors define their own input and output schemas. Treat each as a separate contract unless its documentation proves otherwise.
Does Apify have schedules and monitoring?+
Yes. Apify documents cron schedules, run-status and run-metric alerts, and dataset-field-statistic alerts. These monitor jobs and outputs; a Monocrawl Monitor is a saved subject workflow for new findings.
Which one is cheaper?+
There is no generic answer. Monocrawl prices supported endpoints in credits. Apify can combine subscriptions, Actor events or platform usage, compute, proxies, storage, transfer, retries, and dataset reads. Test the exact Actor against the same completed workload.
Actor evidence
How the Actor model was verified
Apify mechanics and prices come from its documentation and dated pricing pages. Actor-specific evidence is not generalized across the Store. Checked 2 September 2026.
Actor model, JSON input, optional structured output, runtimes, schemas, storage, public/private status, and composition. · Direct
REST run/status/dataset routes, five-minute synchronous route, webhooks for longer work, API clients, CLI, and MCP. · Direct
Run datasets, append-only rows, schemas, API access, export formats, and default retention behavior. · Direct
Cron-based scheduled Actor/task runs and scheduled input configuration. · Direct
Run-status and metric charts, threshold alerts, and dataset-field-statistic alerts with email, Slack, or Console notifications. · Direct
Dated subscription, prepaid usage, CU, concurrency, proxy, storage, transfer, expiry, and overage terms. · Direct; table verified 2026-09-02
Actor-specific pay-per-event and pay-per-usage models, included-usage caveats, cost-estimation guidance, and rental sunset dates. · Direct; catalog is in a documented transition
Compute-unit definition and workload factors that affect resource consumption. · Direct
Marketplace limits
What cannot be generalized across the Store
Contracts and economics vary by publisher and are in a pricing transition, so marketplace-wide counts, schemas, quality, and unit costs stay out.
- No stable count of Store Actors or social-specific Actors was used.
- No uniform Store-wide schema, quality, maintenance, uptime, or SLA was assumed.
- No generic per-record price or total-cost advantage was invented for an Actor workload.
- No one pricing model was projected across the Store while legacy rental Actors complete their documented 2026 sunset.
Test the boundary
Compare Monocrawl with the Actor you would actually run
Use one representative source, payload, and schedule. Price the complete Actor run—including proxies, storage, and dataset reads—before choosing a layer.