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Bright Data is the largest web data infrastructure company in the world. 150M+ residential IPs. $300M+ in annual revenue. Customers across every Fortune 500 sector.
And yet: every year, more engineering teams find themselves asking "is there something that handles the whole thing?"
Bright Data gives you access infrastructure — the largest proxy network commercially available. TinyFish gives you workflow automation — describe a task in natural language, get structured JSON back. The right choice depends on whether your bottleneck is getting through the door, or what happens after you're inside.
The core difference in one sentence: Bright Data is a web data infrastructure platform built around the world's largest proxy network; TinyFish is a web agent platform that uses AI to complete multi-step workflows via a single API call.
Bright Data is a full web data platform:
TinyFish takes a different approach:
IP network breadth. 150M+ residential IPs across 195 countries is genuinely unmatched. For geo-specific data collection — pricing verification across 50 countries, ad compliance monitoring, content localization checks — this infrastructure has no direct substitute. TinyFish includes residential proxy routing in 7 countries (US, GB, CA, DE, FR, JP, AU). For niche geographies, Bright Data is the clear choice.
Pre-built scrapers for known sites. If your target is Amazon, Google Shopping, LinkedIn, or any of 120+ supported platforms, Bright Data's pre-built collectors are production-ready. No prompt engineering, no AI reasoning overhead — just structured data from known schemas. This is faster and more reliable than an agent for these specific sites at scale.
Raw proxy access for existing code. If you already have Playwright or Puppeteer scripts and just need better proxies, Bright Data integrates without changing your codebase. TinyFish requires switching to the agent paradigm — you can't plug TinyFish's proxies into your existing scraper.
Volume at scale. Bright Data handles hundreds of millions of requests daily. For bulk data collection on known targets, their infrastructure is battle-tested at a level few platforms match.
New or unknown sites. Bright Data's pre-built scrapers cover 120+ sites. The web has millions. When your target isn't on the supported list, you're back to building your own scraper — choosing proxies, writing selectors, handling JS rendering, managing retries. TinyFish handles any site from a natural language description. For teams whose targets are fixed and well-supported, Bright Data's pre-built approach is more reliable. For teams whose targets shift frequently, TinyFish's flexibility matters.
Dynamic, multi-step workflows. Bright Data's Scraping Browser gives you a cloud browser with proxy access — powerful for developers who want to write their own orchestration logic. The tradeoff: login flows, conditional navigation, form filling, and multi-page sequences are your code to write and maintain. TinyFish's agent handles the full sequence in one call. The first gives you control; the second gives you speed to production.
Pricing structure. Bright Data's modular pricing (per GB, per request, per CPM) gives sophisticated buyers the ability to optimize cost per workload but forecasting spend across multiple products requires careful modeling. TinyFish charges per step with all infrastructure included. Simpler to forecast, less opportunity to optimize components independently.
AI integration models. Bright Data's MCP server lets AI agents orchestrate their existing tool suite — proxies, unlockers, scrapers — via function calls. This works well for teams building custom agent pipelines who want best-in-class access infrastructure underneath. TinyFish's AI is built into the execution engine itself: the agent perceives pages, decides actions, and adapts mid-workflow without external orchestration. The difference is whether AI sits on top of your tools (Bright Data) or is the tool (TinyFish).
Bright Data's pricing is modular — each layer billed separately:
Ranges based on Bright Data's publicly listed pricing, third-party buyer data (Vendr), and independent reviews as of Q1 2026. Actual rates vary by volume, contract terms, and negotiation. Enterprise buyers typically negotiate 20–40% below list.
At high volume with negotiated rates, Bright Data can be extremely cost-effective per request. At lower volume across multiple products, costs compound quickly.
| Plan | $/mo | Steps Included | Per Step Overage | Concurrent Agents |
|---|---|---|---|---|
| Pay-as-you-go | $0 | Pay per use | $0.015 | 2 |
| Starter | $15 | 1,650 | $0.014 | 10 |
| Pro | $150 | 16,500 | $0.012 | 50 |
| Enterprise | Custom | Custom | Custom | Custom |
One line item. Browser, proxy, LLM, anti-bot — all included per step.
Scenario A — Amazon product extraction, 10,000 pages. Using Bright Data's pre-built scraper: ~$10–50 depending on tier. Fast, reliable, structured output. TinyFish web agent doing the same: estimated 10–50K steps at $0.015/step = $150–750. Bright Data wins on known targets at scale — this is the scenario pre-built scrapers were built for.
Scenario B — 100 multi-step workflows across diverse insurance portals. Each workflow: log in, navigate to the claims dashboard, extract structured data. Bright Data path: build and maintain a custom scraper per site (proxy config + selector logic + parsing + maintenance). That's significant engineering time before you touch the data. TinyFish: 100 natural language task descriptions × ~10–20 steps per workflow (based on TinyFish internal benchmark data for mid-complexity multi-step tasks; simpler flows run 10 steps, more conditional ones run 20) × $0.015 = ~$15–30. Plus the engineering time is near-zero.
Bright Data is cheaper per page when the site is supported and the workflow is simple. TinyFish is cheaper per workflow when the task is complex and the sites are diverse.
Teams typically look for Bright Data alternatives for three reasons:
If any of these applies to your situation, TinyFish is worth testing on your actual workflow before committing to a proxy-first approach. If your bottleneck is purely geographic coverage or volume on known sites, Bright Data remains the strongest option.
| Factor | Choose Bright Data | Choose TinyFish |
|---|---|---|
| Target sites | Known, supported (Amazon, Google, LinkedIn, etc.) | Unknown, diverse, or frequently changing |
| Task complexity | Simple extraction from known schemas | Multi-step workflows with conditional logic |
| Geographic needs | 195+ countries, maximum IP diversity | 7 countries, included in step price |
| Pricing model | Modular, optimize per component | Flat per step, predictable |
| Existing infrastructure | You have scrapers, need better proxies | Starting fresh or cutting scraper maintenance |
| Volume | Hundreds of millions of requests | Thousands to tens of thousands of workflows |
| Engineering resources | Team available to build and maintain scrapers | Minimal — describe tasks, get results |
Bright Data and TinyFish aren't competing for the same workflow. They operate at different layers of the same problem.
The split that works in practice: use Bright Data's pre-built scrapers for your high-volume, known-target data collection (Amazon, Google, LinkedIn) — these are its strongest use case, production-ready, and faster than any AI agent for those schemas. Use TinyFish for the long tail: the 40 insurance portals, the 200 competitor pricing pages, the authenticated dashboards that don't have a pre-built collector.
The teams that benefit most from running both typically have one or two high-volume known-site pipelines that Bright Data handles cheaply, plus a growing set of one-off or irregular workflows where building and maintaining custom scrapers doesn't make economic sense.
The teams that should just pick one: if the overwhelming majority of your data needs come from Bright Data's 120+ supported sites — meaning you rarely need to scrape anything outside that list — the complexity of adding another platform isn't worth it. If your needs are mostly diverse, dynamic sites with workflow logic, TinyFish alone is cleaner.
If your workflow is "extract product data from Amazon at scale" — Bright Data is probably the right tool today.
If your workflow is "visit 50 different supplier portals, log in, navigate to the inventory page, and pull structured data" — that's TinyFish's native use case. 500 free steps, no credit card required.
Both. Bright Data started as a proxy network and has since built a full web data platform: pre-built scrapers for 120+ sites, a cloud-based scraping browser, SERP API, and MCP integration for AI agent frameworks. The proxy network remains the core infrastructure layer that everything else builds on.
Not directly. Bright Data offers 150M+ IPs in a static dedicated pool (and up to 400M+ monthly rotating IPs) across 195 countries. TinyFish currently supports residential proxy routing in 7 countries (US, GB, CA, DE, FR, JP, AU). For geo-specific data collection across many countries, Bright Data has no equivalent.
It depends on what "scale" means for your workload. For high-volume extraction from Bright Data's 120+ supported sites, their pre-built scrapers offer significantly better per-page economics. For diverse multi-step workflows across sites that aren't pre-supported, TinyFish's all-inclusive step pricing avoids the cost complexity of combining multiple Bright Data products — and eliminates the engineering time of building custom scrapers.
Bright Data's MCP server connects their proxy and scraping tools to AI agent frameworks, letting AI agents orchestrate Bright Data's APIs via function calls. This is useful for teams building custom agent pipelines who want best-in-class access infrastructure underneath. TinyFish's AI is built into the execution engine itself — the agent reasons about each page interaction in real time, rather than being an orchestration layer above separate tools.
Not directly. TinyFish includes its own residential proxy infrastructure in the per-step price. For targets that require IPs from specific countries outside TinyFish's 7-country coverage, you'd need to use Bright Data directly with your own scraping code.
If your targets aren't in Bright Data's 120+ supported scraper list, if your workflows involve multi-step interactions rather than simple extraction, or if scraper maintenance overhead is becoming a cost center, it's worth testing a web agent approach. TinyFish is a practical alternative for teams in those situations. Bright Data remains the strongest choice for geographic coverage depth and high-volume collection on supported sites.
No credit card. No setup. Run your first operation in under a minute.
TL;DR: TinyFish is now an n8n community node. Drop it into any workflow, point it at a URL, tell it what you want, and get clean JSON back. The web just became another input in your automation pipeline.
