You found an Actor on Apify Store for a popular mapping platform, kicked off a 1,000-record job, and watched $7 in compute units disappear. When the results came back, 200 rows were malformed. The Actor's maintainer hadn't committed in four months.
Apify is a powerful platform — 4,000+ community-built Actors, the Crawlee SDK, built-in scheduling, and cloud storage. For developers comfortable writing JavaScript and configuring scrapers from scratch, it remains one of the most complete options in the market. But Apify's strength is also its ceiling: it's built around pre-scripted extraction logic. When your task requires a browser that can think — logging into authenticated portals, navigating dynamic flows, handling multi-step authenticated workflows — the Actor model runs out of road.
Here are six alternatives, each designed for a different piece of the problem. And one that handles the whole thing.
Quick decision framework:
| Tool | Best for | Pricing model | AI output | Code required | Agent capable |
|---|---|---|---|---|---|
| Firecrawl | LLM data pipelines | Per page | Native markdown | Optional | No |
| TinyFish | Authenticated + multi-step | Per step | Structured JSON | No (natural language) — API, SDK, or MCP | Yes |
| Bright Data | Anti-bot at scale | Per request + bandwidth | Via scrapers | Yes | No |
| Scrapy | High-volume static crawling | Free (self-hosted) | DIY | Yes (Python) | No |
| ScraperAPI | Proxy + rendering layer | Per request | Raw HTML | Yes | No |
| Octoparse | Non-technical visual scraping | Per month | CSV/JSON | No | No |
| Crawl4AI | Open-source LLM output | Free (self-hosted) | Markdown | Yes | No |
| n8n | Workflow automation | Per month | Via nodes | Low-code | No |
| Browse AI | Visual monitoring + extraction | Per month | Structured | No | No |
| Gumloop | AI agent workflows + scraping | Per month | Via LLM | No | Yes |
Before picking a replacement, define what you actually need. Most teams switch for one of four reasons — and the right alternative is different for each:
1. Predictable pricing. Apify bills by compute unit — memory × runtime. If you use community Actors, you don't control Actor efficiency, so costs are hard to predict. Look for tools with per-page, per-step, or bandwidth pricing that maps directly to your workload.
2. AI-native output. If your pipeline feeds a language model, raw HTML is a processing burden. Tools like Firecrawl and Crawl4AI output clean markdown natively, cutting LLM token consumption significantly. Not all scrapers do this.
3. No-code or low-code automation. If you don't have engineers to maintain custom Actors, tools like Octoparse, n8n, Browse AI, or Gumloop let you build scraping workflows visually. Different value proposition from developer-focused tools.
4. Agent-level intelligence. Static scraping fails when the target requires login, navigation decisions, or interaction with dynamic content. Only agent-based platforms (TinyFish, Browser Use) handle this category natively.
Three friction points push teams elsewhere.
Pricing you can't predict. Apify bills by compute unit — memory (GB) multiplied by runtime (hours). The actual cost depends on Actor efficiency, memory allocation, and run duration. You control maybe one of those three variables when using community-built Actors. A $49/month plan can quietly become $200+ when a poorly optimized Actor chews through memory on retry loops.
Community Actor quality is uneven. The Store has 4,000+ Actors, which sounds great until you realize maintenance depends on individual contributors. Some Actors haven't been updated in months. When a target site changes its DOM, your scraper breaks and you're waiting on someone else's fix — or forking it yourself.
No native AI agent capability. Apify Actors follow scripted logic: go to URL, extract selectors, return data. That works for known, stable sites. But when the task requires judgment — a CAPTCHA appears, a form layout changes, or you need to navigate an authenticated multi-step checkout — scripted extraction can't adapt. You'd need to layer Playwright, an LLM, proxy management, and retry logic on top. At that point, you're building your own agent platform.
Apify still wins when you need a well-maintained Actor for a popular platform, when the target structure is stable, or when you want Crawlee's open-source SDK on managed infrastructure.
Switch from Apify when: Your output goes directly into an LLM and you're spending engineering time stripping HTML before embedding.
If your end goal is feeding web content into an AI model, Firecrawl removes a step most other tools make you handle yourself. Every scrape outputs clean markdown natively, which cuts LLM token consumption by roughly 67% compared to raw HTML. No post-processing, no parsing layer.
The platform covers three core workflows: /scrape for single pages, /crawl for full-site extraction, and /agent for multi-step data gathering powered by Spark models. Structured extraction via /extract lets you define output schemas with natural language prompts or Pydantic models, so you get exactly the JSON shape you need. Framework integrations with LangChain and LlamaIndex are built in.
Pricing: Free tier gives 500 lifetime credits (they don't refresh). Hobby starts at $16/month for 3,000 credits. Standard is $83/month for 100,000 credits. One credit equals one page, but advanced features stack: JSON mode adds 4 credits, Enhanced adds 4 more. Check Firecrawl's current pricing for advanced extraction features.
Where it falls short: Independent testing by Proxyway put Firecrawl's success rate on protected sites at roughly 34% at 2 requests per second. For sites behind aggressive anti-bot systems — enterprise-grade protection systems — you'll burn credits on retries. Social media platforms (Instagram, YouTube, TikTok) are explicitly restricted. The open-source version uses AGPL-3.0 licensing, and the self-hosted setup doesn't include the managed cloud infrastructure of the hosted product.
Best for: Teams building RAG pipelines, content indexing, or any workflow where the output needs to be LLM-consumable. If your targets are documentation sites, blogs, or marketing pages, Firecrawl is hard to beat on output quality per dollar.
Switch from Apify when: Your task requires login, multi-step navigation, or decisions based on page content — anything where scripted Actor logic breaks when the page changes.
Here's the question worth asking before you pick any scraping tool: does your task end at "extract data from a page"? Or does it actually look more like "log into this portal, navigate to the pricing page, check which products changed, and return structured results"?
If it's the second one, you don't need a better scraper. You need an agent.
TinyFish is a web agent platform that runs AI agents on remote browsers at scale. You describe a goal in natural language, and the platform handles login, navigation, infrastructure-level handling, dynamic page interaction, and structured data return — all through a single API call. No assembling Playwright + proxy service + LLM + retry logic. No maintaining CSS selectors that break when a site updates its layout.
The platform runs on four layers that work together: Search API finds URLs, Fetch API extracts content, Browser API handles dynamic interaction via CDP, and Web Agent completes multi-step tasks. One API key, one credit pool, one dashboard.
Pricing: Pay-as-you-go at $0.015 per step. Starter plan is $15/month with 1,650 steps included. Pro is $150/month for 16,500 steps. Search and Fetch are free on all plans — rate-limited by plan tier. Every plan also includes remote browser, residential proxy, and all LLM inference — no surprise line items. Workflows never hard-stop mid-execution on overage; they continue at the overage rate. Free trial: 500 steps, no credit card required.
Performance numbers: Cold start under 250ms. 89.9% accuracy on the Mind2Web benchmark (97.5% on easy tasks, 81.9% on hard — vs. OpenAI Operator at 61.3%). 50 concurrent agents on Pro. A 50-portal pricing task that takes 45+ minutes manually completes in 2 minutes 14 seconds (internal testing).
Where it's honest: If you're scraping 10,000 static product pages from a major e-commerce platform, Apify has a well-maintained Actor that's cheaper and more direct. If you need 150 million residential IPs for geo-distributed data collection, Bright Data is purpose-built for that. TinyFish's sweet spot is where the task requires browser intelligence at scale — authenticated sites, multi-step workflows, sites with strict automation requirements.
Start with 500 free steps and test against your own target sites: tinyfish.ai. Available via REST API, Python/Node SDK, CLI, and MCP server for Claude Code and Cursor.
For more on how TinyFish approaches the full web infrastructure problem: Why AI Agents Need a Unified Web Infrastructure
Switch from Apify when: Getting blocked is your primary failure mode — you need 150M+ IP diversity and enterprise-grade infrastructure, not scraping logic.
If your bottleneck is getting blocked, Bright Data has the biggest network in the industry: 150 million+ IPs spanning residential, datacenter, mobile, and ISP proxies across every geography. Their Web Scraper API includes 230+ pre-built scrapers for popular targets, with built-in CAPTCHA solving and geo-targeting down to city level.
Independent benchmarks consistently rank Bright Data among the highest for success rates on protected sites. With $300M+ in annual recurring revenue and enterprise clients across every vertical, the platform is built for teams running millions of pages per month against heavily defended targets.
Pricing: Entry-level scraping starts around $1 per 1,000 requests, but actual costs depend on proxy type, bandwidth, and which scraping products you use. Pricing is modular — proxy fees, scraper fees, and bandwidth are separate line items. For teams running at scale, this granularity offers control. For smaller teams, it can feel overwhelming.
Where it falls short: Pricing complexity is the consistent complaint. You need to understand the difference between residential, datacenter, and ISP proxies, estimate bandwidth consumption, and pick the right scraper product — all before running your first job. The platform is built for enterprise buyers with procurement teams, not solo developers looking for quick answers.
Best for: Enterprise data teams running high-volume collection on protected targets, especially where geo-targeting, IP diversity, and regulatory compliance matter. If you're scraping millions of pages monthly and getting blocked is a bigger cost than the tool itself, Bright Data is table stakes.
For a detailed comparison with TinyFish's approach: TinyFish vs Bright Data
Switch from Apify when: You have Python engineers, need full extraction control, and are scraping stable, public site structures at high volume where Apify's compute pricing adds up.
If you have Python engineers and want total control, Scrapy remains the default. A decade of production use, a massive ecosystem of middleware and plugins, and the ability to handle thousands of requests per second on your own infrastructure.
Scrapy is free. Your costs are compute, proxies (if needed), and engineering time. For teams scraping structured, stable sites at high volume — price feeds, product catalogs, job listings — the economics are hard to beat. The community is large enough that most edge cases have a StackOverflow answer.
Where it falls short: No JavaScript rendering out of the box (you'll need Splash or Playwright integration). No infrastructure-level handling. No AI capabilities. No managed infrastructure. Every spider you write is a spider you maintain, and when a target site changes its layout, you're the one fixing it. For teams without dedicated scraping engineers, the maintenance burden compounds fast.
Best for: Cost-sensitive teams with Python developers who need to scrape known, stable targets at high volume. Scrapy is also the right choice when you need complete control over every aspect of the crawl — request scheduling, deduplication, retry policy, output format.
Switch from Apify when: You already have extraction logic written and the only problem is getting blocked — you don't need Apify's Actor marketplace, just reliable outbound infrastructure.
ScraperAPI sits between "raw proxy provider" and "full scraping platform." You send an HTTP request, they handle proxy rotation, JavaScript rendering, CAPTCHA solving, and header management. DataPipeline endpoints let you schedule recurring scraping jobs without managing cron or infrastructure.
Pricing: Starter plan at $29/month; Scale at $199/month. Simple pages consume 1 credit; requests with geo-targeting, JavaScript rendering, or premium proxies can consume 5 to 25 credits each. The math gets harder to predict as you add parameters.
Where it falls short: ScraperAPI returns raw HTML. You still need to write parsing logic to extract structured data. There's no markdown output, no AI-driven extraction, no agent capability. It's a very good proxy + renderer, and that's the boundary.
Best for: Teams that already have working parsers and just need reliable outbound infrastructure. If you've built your extraction logic in Python or Node and the only problem is getting blocked, ScraperAPI solves that specific problem cleanly.
Switch from Apify when: Your team isn't technical enough to configure Actors from scratch, and your targets have predictable layouts that a point-and-click tool can handle.
Octoparse offers a point-and-click visual editor for building scrapers without writing code. For non-technical users who need to extract data from sites with predictable layouts — product listings, job boards, directory pages — the drag-and-drop interface is genuinely accessible.
The platform includes 460+ templates for popular sites, scheduled extraction, and cloud execution on paid plans.
Pricing: Standard plan starts at $83/month. But the base price understates the real cost: residential proxies run $3/GB, CAPTCHA solving costs $1 per thousand, and the visual editor is Windows-only (Mac and Linux users need a workaround). API access requires the Professional plan at $209/month or higher.
Where it falls short: JavaScript-heavy sites (SPAs, infinite scroll) are unreliable in the visual editor. The template library is smaller than Apify's Actor marketplace. At scale, users report performance slowdowns. The Windows-only editor locks out a significant portion of the developer community.
Best for: Non-technical teams doing low-to-medium volume scraping on structurally simple sites. If your use case fits within the template library, Octoparse delivers without requiring any code.
Switch from Apify when: You need LLM-ready output, Apache 2.0 licensing (no AGPL obligations), and have the DevOps capacity to run your own infrastructure.
Crawl4AI is gaining traction as the Apache 2.0 alternative to Firecrawl's AGPL. It runs on Docker with Playwright support, delivers LLM-ready output, and integrates with multiple LLMs via LiteLLM (OpenAI, Anthropic, local Ollama models). Adaptive crawling auto-learns selectors, cutting crawl times on structured sites according to their documentation.
Pricing: Free software. Real costs are compute and proxies, typically $50–300/month depending on volume and target difficulty.
Where it falls short: You're responsible for all infrastructure — Docker deployment, proxy management, monitoring, and scaling. There's no managed service, no support team, no dashboard. The "bring your own everything" model is powerful for teams with DevOps capacity and a liability for teams without it.
Best for: Engineering teams with data sovereignty requirements, budget constraints, and the DevOps capacity to run their own crawling infrastructure.
If your team doesn't have engineers to maintain custom Apify Actors, a different category of tools handles scraping as part of broader workflow automation:
n8n (open-source, self-hostable) — Visual workflow builder where scraping is one node in a larger pipeline. Connect HTTP requests, HTML extraction, and data transformation without writing Python. Thousands of community templates for common scraping tasks. Self-hosted version is free; cloud plans from $24/month. Best for technical-but-not-developer teams who want automation without Apify's Actor complexity.
Browse AI — Point-and-click scraper that trains on what you want to extract. You show it once, it monitors and extracts going forward. Handles login flows for sites you authenticate to manually first. Strong for monitoring use cases (price tracking, job listings, competitor pages). Pricing from $19/month.
Gumloop — AI agent platform with web scraping built in. Drag-and-drop flows connect scraping, LLM processing, and external tools. In-product AI assistant (Gummie) builds workflows from natural language descriptions. No-code for most use cases; custom scripts available. Pricing from $37/month. Used by teams at Shopify, Instacart, and Webflow.
These tools trade raw flexibility for speed of setup. They're not the right choice if you need custom extraction logic, scale to millions of pages, or developer-level control. But if Apify's Actor model is too complex for your team's technical level, they're worth evaluating before you build something custom.
TinyFish gives you 500 steps free — no credit card, no commitment. Point it at your real target sites and see if an AI agent handles the workflow that your current scraping setup can't.
Scrapy is completely free and open-source, with the largest Python scraping community. Crawl4AI is the best free option if you need LLM-ready output with Apache 2.0 licensing. Both require self-hosting and engineering resources.
TinyFish is purpose-built for AI agent workflows — it runs agents on remote browsers at scale, handling authentication, navigation, and dynamic content through a single API call. Browser Use is the strongest open-source option if you want to run agents locally.
For certain workflows, yes. Firecrawl excels at turning web pages into clean markdown for LLM consumption, with native integrations into LangChain and LlamaIndex. But Firecrawl doesn't have Apify's marketplace of pre-built scrapers for specific sites, and it lacks Apify's scheduling and data storage features. Many teams use both: Firecrawl for content extraction and Apify for site-specific structured data.
They solve different problems. Bright Data is proxy and data infrastructure — 150M+ IPs, geo-targeting, anti-detection. Apify is a scraping platform with pre-built tools and a developer ecosystem. Teams that need both IP infrastructure and scraping logic often combine Bright Data's proxies with Apify's Actors or their own Crawlee scripts.
Scrapy is free (open-source). Firecrawl's Hobby plan starts at $16/month. TinyFish offers pay-as-you-go at $0.015/step with no monthly commitment, plus 500 free steps to start.
If your task is "go to this URL and extract these fields" — that's scraping. Tools like Firecrawl, Apify, or Scrapy handle this well. If your task is "log into this portal, navigate through several pages, make decisions based on what you see, and return structured results" — that's an agent task. TinyFish is built for the second category.
No credit card. No setup. Run your first operation in under a minute.
