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Apify vs Clay

An independent, review-free comparison compiled by the SaaSTracker editorial team. Both products are profiled in full, and neither can pay for placement here.

The short answer

Editorial assessment

Apify compared with Clay

Complementary rather than competing, though the boundary blurs. Clay is a spreadsheet-shaped enrichment environment that fans a list of companies or people out across dozens of data providers and AI prompts; Apify is where the raw list comes from when no provider has it. The common pattern is an Apify Actor producing a scraped source list, pushed into Clay for enrichment, scoring, and CRM sync. Clay does include a scraping capability, so light needs can stay in one tool, but sustained crawling at volume is cheaper and more controllable on Apify.

Choose Apify if

Growth, RevOps, and data teams that need custom web data at a scale a manual list build cannot reach, and that want ready-made scrapers for the common sources with an escape hatch into custom code when a target is unusual. Also strong for anyone wiring web data into an AI agent through MCP.

Choose Clay if

GTM engineers and data-savvy teams building automated, multi-provider enrichment and personalization pipelines.

Side by side

13 attributes
AttributeApifyClay
CategoryGTM EngineeringData
Starting priceFree with $5 of monthly platform credit; paid plans from $29 per month ($26 billed annually) (free plan available)Free plan; paid from $149/mo (free plan available)
Pricing modelPrepaid platform credit with usage metered against it. Each plan includes a monthly credit allowance equal to its price, consumed by compute units (memory multiplied by run time), proxy bandwidth, storage operations, and data transfer. Rented or paid Store Actors carry their own fees on top, set by the Actor's developer as a monthly rental, a per-event charge, or a per-result charge. Seats are not the pricing axis; usage is.Credit-based monthly tiers; provider calls and Claygent runs consume credits (only on successful hits for waterfalls). Feature gates (CRM write-back, webhooks) sit at tier boundaries.
Free plan$5 of platform credit per month, community support, limited trial access to rented Actors, and access blocked rather than billed once credit is spent100 credits/month, core table features.
Free trialFree plan with no credit card required, plus limited trials on most paid Store Actors14 days (Pro features)
Best forGrowth, RevOps, and data teams that need custom web data at a scale a manual list build cannot reach, and that want ready-made scrapers for the common sources with an escape hatch into custom code when a target is unusual. Also strong for anyone wiring web data into an AI agent through MCP.GTM engineers and data-savvy teams building automated, multi-provider enrichment and personalization pipelines.
Setup timeMinutes for a first Store Actor run: sign up, pick an Actor, fill the form, export a CSV. A scheduled pipeline with proxy configuration, webhooks, and a downstream destination is a half day. A custom Actor is a normal software project, measured in days, and its length depends on how hard the target defends itself rather than on Apify.First enriched table in an hour via templates; a production pipeline (sources, then waterfalls, then scoring, then delivery) typically takes 2-4 weeks to harden.
Learning curveLow to run existing Actors, moderate to operate the platform well. The two things that take time are understanding the cost model well enough to predict a bill, and learning which proxy and browser settings a given target requires. Writing Actors requires working JavaScript or Python.The steepest in this report, genuinely a skill. Templates, the academy, and a large creator ecosystem (courses, agencies) flatten it substantially.
PlatformsWeb console, REST API, JavaScript and Python API clients, Apify CLI, Docker-based Actor runtime, Hosted MCP serverWeb app, Chrome extension, REST API
ComplianceGDPR, SOC 2 Type II, CCPASOC 2 Type II, GDPR program
Founded20152017
HeadquartersPrague, Czech RepublicNew York City, US
OwnershipIndependent, venture-backedVenture-backed (private)

Strengths and limitations

Apify

Strengths

  • The Store is the moat: for most common data sources, someone has already built, debugged, and now maintains the scraper, which collapses a two-week project into an afternoon of configuration.
  • Real infrastructure underneath, with proxies, headless browsers, storage, scheduling, and retries handled rather than left as an exercise.
  • Genuinely usable free tier with $5 of monthly credit, no credit card, and full API and MCP access, so evaluation costs nothing.
  • Crawlee is open source and runs anywhere, which meaningfully limits lock-in for teams writing their own crawlers.

Limitations

  • Compute-unit billing is hard to predict before you run a job, because cost is memory multiplied by time and both depend on how the target site behaves that day.
  • Included platform credit expires monthly with no rollover, so buying a tier for occasional heavy months means paying for unused capacity in the quiet ones.
  • Store Actor quality is uneven; some are abandoned, some break silently when a target site changes markup, and the run-success statistics on the Actor page are the only pre-purchase signal.
  • Paid Actors add a second billing layer on top of platform credit, and the total cost of a workflow is not visible from any single number on the pricing page.

Clay

Strengths

  • Waterfall coverage decisively beats any single data provider.
  • Claygent turns open-web research into a scalable, auditable pipeline step.
  • Deep native integrations across the modern outbound stack (sequencers, CRMs, signals).
  • Template/creator ecosystem compounds, proven workflows are one click away.

Limitations

  • Real learning curve, tables, waterfalls, and prompt design reward (effectively require) a technical operator.
  • Credit economics are powerful but unforgiving without active management.
  • Not a proprietary data source; quality ceilings are its providers'.
  • Enterprise governance (SSO, roles, audit) only matures at top tiers.

Pricing compared

Apify

Prepaid platform credit with usage metered against it. Each plan includes a monthly credit allowance equal to its price, consumed by compute units (memory multiplied by run time), proxy bandwidth, storage operations, and data transfer. Rented or paid Store Actors carry their own fees on top, set by the Actor's developer as a monthly rental, a per-event charge, or a per-result charge. Seats are not the pricing axis; usage is.

  • Free$0
  • Starter$29
  • Scale$199
  • Business$999

Judged against building the same thing yourself, Apify is inexpensive: a residential proxy pool, headless browser fleet, retry logic, and storage would cost more than $29 a month in engineering attention alone, before any infrastructure. Judged against a fixed-price scraping tool, it is harder to compare, because you are buying capacity rather than a defined output, and the honest answer for month one is that you cannot forecast the bill precisely. The mitigation is straightforward: run the job once at a small limit, read the usage breakdown, multiply. Teams that do this usually find the real cost of a recurring list build lands in the tens of dollars a month, and teams that skip it are the ones who write reviews about unpredictable pricing.

Clay

Credit-based monthly tiers; provider calls and Claygent runs consume credits (only on successful hits for waterfalls). Feature gates (CRM write-back, webhooks) sit at tier boundaries.

  • Free$0
  • Starter$149
  • Explorer$349
  • Pro$800
  • EnterpriseCustom

Clay's effective price is workflow-dependent: well-designed tables deliver coverage and personalization no single vendor matches at any price, while naive configurations burn credits alarmingly. Teams treating credit design as part of the craft consistently report it as the stack's highest-ROI line item.

Editorial verdict on each

Apify

Apify is the most complete web scraping platform a small team can buy without a sales call, and its real asset is the Store: for the sources most go-to-market teams need, someone has already written and is still maintaining the scraper, which is the difference between a two-week engineering project and an afternoon. Underneath it, the proxy pool, browser fleet, storage, and scheduling are the parts people underestimate until they have tried to build them, and Crawlee being open source keeps the lock-in honest. The MCP server has made it one of the more useful data sources to hand an AI agent. The cost of all this is a billing model you have to learn: compute metered by memory times time, credit that expires monthly, and a second layer of fees on paid Actors that no headline price reflects. Budget an hour to measure one representative job before committing, set a spending limit on day one, and check an Actor's success rate before you depend on it. Do those three things and it is very good value; skip them and you will write one of the reviews about unpredictable pricing.

Read the full Apify profile

Clay

Momentum

Clay is the most consequential product in this report: it moved the center of outbound gravity from databases and sequencers to the orchestration layer between them, and its valuation sprint reflects substance, not froth. The costs are honest, a real learning curve and credit economics that punish sloppiness, but teams that invest in the craft get coverage, research, and personalization nothing else assembles. If your outbound has an engineer, this is their instrument.

Read the full Clay profile

Apify profile last reviewed 2026-08-23; Clay last reviewed 2026-08-22. Pricing is compiled from public sources and can change without notice. See our methodology.