Edges vs Apify
Stop stitching actors. One API, one SLA, one vendor for LinkedIn.
Who this comparison is for
You built LinkedIn workflows on Apify because the marketplace had actors for everything. Now half your infra debt is "which actor are we using for this SN search, and is it still maintained by the original author?"
At a glance
The axes that matter when you’re picking between us.
| Topic | Edges | Apify |
|---|---|---|
| Product shape | Opinionated LinkedIn API with a single contract and roadmap owner. | Actor marketplace: different authors, different quality, different update cadences. |
| Vendor accountability | One company accountable when LinkedIn changes or actions break. | Apify hosts the platform; individual actor authors maintain the LinkedIn logic. |
| Time to production | Integrate documented endpoints once. Ship. | Evaluate actors, test edge cases, handle actor-specific errors, compose workflows. |
| Fully-loaded cost | Per-action credits + Edges team owns reliability. | Actor fees + proxy spend + your engineering time on actor babysitting. |
| LinkedIn-specific features | Sales Navigator, schedule-mode timing Actions, engagement — all first-class. | Varies by actor — may require stitching 3–5 different actors for one workflow. |
| Support | Direct support from Edges with SLA on enterprise tier. | Apify support for the platform; LinkedIn actor issues often route to the author. |
Pick the right one
Choose Edges when
LinkedIn is production-critical and you want one vendor owning reliability — not a rotating cast of marketplace actor authors with varying update schedules, quality, and availability.
Consider Apify when
You scrape dozens of sites beyond LinkedIn, marketplace flexibility outweighs vendor consolidation, and you're comfortable composing and maintaining actors across publishers.
Migration
Map your current Apify calls or automations to Edges actions using the Library and the documentation. Ask support for the OpenAPI spec and it drops straight into Postman, Hoppscotch, or any code generator. Share your integration outline and we can suggest parity endpoints and credit estimates. Messaging, invites, and inbox sync are documented on the LinkedIn messaging API page.
FAQ
Is Apify cheaper than Edges?
On sticker price, sometimes. On fully-loaded cost — engineering time, proxy spend, actor maintenance, incident response — Edges usually wins once LinkedIn volume is meaningful. Model your own numbers including engineering hours.
What breaks when a LinkedIn actor's author stops updating it?
Your pipeline. The author-maintenance dependency is invisible until something breaks — a common reason teams consolidate on a dedicated vendor.
Does Edges cover the same LinkedIn surfaces as the top Apify actors?
Yes, and usually more — profiles, companies, Sales Nav searches, lead lists, schedule-mode extracts, engagement actions — all through one consistent API. Map your current actors to our Library actions during evaluation.
Can we use Apify for non-LinkedIn scraping and Edges for LinkedIn?
Absolutely. This is a very common split — Apify for the long tail of sites, Edges for LinkedIn where reliability matters most.
How do we handle session management with Edges?
It depends on the action. Reads run on a managed session pool — no cookies, no LinkedIn login in your app. Messaging and engagement need a connected identity: pass a cookie or log in with email + password, then call in `direct` mode. We handle session health, rate limits, and ramp-up on that seat.
What's the migration path from Apify to Edges?
Per-workflow. Pick one critical workflow (e.g. SN search → enrichment), rewrite against Edges, dual-run for a sprint, cut over. Repeat until you're consolidated.
Build on Edges
Credits-based pricing, SOC 2 Type II, and a growing catalog of LinkedIn actions — see Pricing and Enterprise for scale.
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Edges is not related to LinkedIn and is not an official LinkedIn product.