Most-Used Scraping Actors Right Now (October 2026)
Last updated: October 21, 2026 · Data snapshot: October 21, 2026 (trailing 30-day window) · Weekly refresh
Table 1 — Top 20 by 30-day run volume
Table 2 — Runs-per-user: where scraping looks like an API, not a tool
Actors with ≥50 monthly users, ranked by runs per user. High intensity = few users hammering it in production (API-like); low intensity = many casual users.
| Actor | ^Runs/30d | ^Users/30d | ^Runs/user (intensity) |
|---|---|---|---|
| danek/twitter-scraper | 5,856,421 | 451 | 12,985 |
| curious_coder/onlyfans-scraper ↗ | 639,925 | 57 | 11,227 |
| epctex/pinterest-scraper ↗ | 1,208,731 | 227 | 5,325 |
| web_wanderer/yelp-reviews-scraper ↗ | 1,280,813 | 264 | 4,852 |
| scraping_solutions/linkedin-profile-comments-reactions-scraper-no-cookies ↗ | 201,681 | 56 | 3,601 |
Key findings
- apify/instagram-scraper is the most-run scraper on the platform: 18,171,771 runs in 30 days (25,239/hour) for 55,041 monthly active users.
- The market is winner-take-most: the top 10 Actors absorb 42.0% of the 222,295,388 monthly runs we observed; the top 20 absorb 57.6%.
- Social-media scrapers dominate: 15 of the top 20 target social platforms.
- Usage intensity is wildly bimodal. danek/twitter-scraper averages 12,985 runs per user — essentially an API serving a few production pipelines — while popular tools like apify run 330 runs/user.
- List pricing does not track volume: #1 by usage bills PAY_PER_EVENT, and the most expensive top-20 Actor charges $4.00/1k.
How we measure
Cohort: Actors scanned from the public Apify Store API (popularity-sorted top 3,957, 3,032 scraping-related matches) on 2026-10-20. For each Actor we take publicActorRunStats30Days: TOTAL, SUCCEEDED, FAILED, ABORTED, TIMED-OUT over the trailing 30 days. Failure rate = FAILED / TOTAL — a run the user cancelled (ABORTED) or that exceeded its timeout budget (TIMED-OUT) is not counted as a failure; both are small relative to TOTAL in this cohort.
Ranking uses TOTAL runs over the trailing 30 days from the public Store API. "Users" = distinct accounts that started a run in the same window. Runs/user is a rough intensity proxy (one user may run many small jobs, or one huge job may contain many internal runs).
Failures have many causes (bad input, target changes, platform incidents) — a high failure rate is a signal, not a verdict. Small-sample Actors (under ~1,000 runs) are excluded from rankings. License: CC BY 4.0 — cite ScraperBench with the data snapshot date.
Conclusion
If you are choosing infrastructure by popularity, the data says: social media scraping is a solved, hyper-scaled problem on the Apify Store (Instagram/TikTok tooling alone accounts for tens of millions of runs a month), and popularity is a reasonable proxy for maintenance — the top 20 all sit at or below ~2% failure. The inverse signal is intensity: Actors with extreme runs-per-user are de-facto production APIs with fragile single-vendor dependence — check their maintenance recency in our abandonment report before you build on one.