Bright Data’s 150M+ proxy network makes it an industry leader, but unpredictable pay-per-GB pricing, $500+ minimums, and 10.6-second response times drive teams to explore alternatives.

We’ve tested alternatives across web scraping APIs and proxy infrastructure, evaluating each on AI-ready outputs, pricing transparency, performance, and ease of setup.

Bright Data (formerly Luminati Networks) is a web data platform that combines three core capabilities: proxy networks, web scraping tools, and ready-to-use datasets.

Quick feature overview:

• 150+ million proxy IPs across 195 countries (residential, datacenter, mobile, ISP)
• Web scraping tools: Scraping Browser, Web Unlocker, SERP API, 120+ pre-built scrapers
• Datasets: 5B+ pre-collected records from LinkedIn, Amazon, Zillow, and 120+ domains
• Pricing: $10.50/GB (residential proxies), $1.50-$2.50 per 1K requests (Web Scraper API)

While Bright Data delivers exceptional proxy infrastructure and comprehensive web data solutions, several persistent issues drive developers and businesses to explore alternatives:

Bright Data’s pay-per-GB pricing structure makes cost forecasting nearly impossible. A website serving 500KB pages costs dramatically different than one delivering 3MB rendered files, and you won’t know which until you’re already paying.

The Web Scraper API compounds this issue. The platform charges a flat $1.50 per 1,000 requests for standard domains and $2.50 for premium targets, regardless of actual page complexity. A static HTML page that competitors scrape for $0.10-$0.20 per 1K costs the same $1.50 as a JavaScript-heavy protected site requiring rendering and premium proxies.

Residential proxies start at $10.50/GB on pay-as-you-go plans, significantly higher than alternatives offering comparable networks at $2-7/GB. When combined with datacenter proxy costs ($0.80/IP) and Web Scraper API fees, monthly bills can spike unexpectedly based on factors outside your control.

For teams operating on fixed budgets or building cost-sensitive applications, this lack of transparency becomes a dealbreaker.

Bright Data targets Fortune 500 companies with infrastructure and pricing to match. While this delivers exceptional scale for enterprises, it creates immediate barriers for startups, small businesses, and individual developers.

No genuine free tier exists for meaningful testing. The platform requires custom sales contact for pricing, and minimum commitments often start at $500+/month before you can properly evaluate if the service works for your specific use case.

Compare this to Bright Data competitors like Firecrawl offering:

• Generous free tiers (500-1,000 credits monthly)
• Self-service signup with transparent pricing
• Pay-as-you-grow models starting at $20-50/month
• No sales calls required

For developers who need a few hundred thousand requests monthly, or startups testing product-market fit, Bright Data’s enterprise positioning forces them to pay premium rates before knowing if the infrastructure fits their needs.

While Bright Data’s technical infrastructure performs well, support quality varies dramatically based on which representative you reach.

One G2 reviewer described the experience:

“I had some difficulty getting my account fixed after an API key expired. The first person I talked to didn’t give me a solution, and then I didn’t hear from anyone for days. I opened a new ticket and the second person resolved my issue within 20 minutes.”

Another user experienced significant delays affecting their business operations:

“On my most recent problem reports, the fixes took about 9 days, which is a little longer than we’d like. In this case we were able to work around it with our customer, but if we could keep that down to a few days in the future, it would cause us less discomfort.” - Source

The gap between 20-minute and 9-day resolution times creates unpredictability that’s unacceptable for production systems. When your scraping operations drive business-critical decisions or customer-facing features, unreliable support becomes a significant operational risk.

Bright Data’s comprehensive feature set—spanning proxy networks, web scrapers, datasets, and browser APIs—creates a paradox: the tools are powerful but difficult to use effectively.

Session management frustrates users. One reviewer noted:

“My main frustrations are with the platform’s session management. The timeout period for a session is quite short, which can be inconvenient. Additionally, logging into the platform using a code doesn’t always work smoothly or reliably.”

The UI isn’t intuitive. Another user highlighted basic usability issues:

“A point of frustration is the inability to easily create custom datasets directly, as I did not see a create custom dataset button; I have to search, which seems inefficient.” - Source

For teams that need to get data quickly without navigating complex dashboards, multiple configuration panels, and unclear workflows, simpler alternatives deliver faster time-to-value.

Despite offering 120+ no-code scrapers, gaps in coverage force users to build custom solutions even for common scraping tasks.

One enterprise user explained:

“I find the range of tools provided by Bright Data somewhat limited. There are specific platforms that I would like to explore further, but it seems that Bright Data does not currently offer pre-made frameworks for those within its suite. This requires us to develop our own custom solutions, which can be a risk.”

This creates a resource trap. You’re paying premium prices for infrastructure that still requires significant engineering time to customize. Teams expect pre-built solutions to work out-of-the-box, not serve as starting points requiring modification.

Modern scraping APIs and platforms increasingly offer automatic adaptation to website changes, reducing maintenance overhead. Bright Data’s approach often requires manual intervention when target sites update their structure.

Bright Data’s architecture predates the AI revolution. The platform returns HTML and JSON that require extensive post-processing before feeding into language models, chatbots, or RAG systems.

Research shows that markdown output reduces token consumption for AI models by an average of 67% compared to raw HTML. Without native markdown conversion or LLM-ready formatting, teams building AI applications face:

• Higher LLM API costs from processing bloated HTML
• Additional parsing layers adding complexity and failure points
• Slower processing times due to unnecessary token overhead
• Manual cleanup of navigation elements, ads, and boilerplate

While Bright Data offers powerful infrastructure, it wasn’t designed for the “feed data directly to Claude/GPT” workflows that define modern AI development. Alternatives purpose-built for AI deliver structured, clean markdown that integrates seamlessly with LangChain, LlamaIndex, and custom LLMs without intermediate processing steps.

Independent testing shows Bright Data’s Web Scraper API averages 10.6 seconds per request across multiple domains. When scraping thousands of pages, that delay translates to hours of additional runtime compared to platforms delivering sub-5-second performance.

The scale creates its own problems. One user noted:

“The online filtering feature can be slow sometimes due to the amount of data.”

File management becomes challenging at scale:

“This might not be an issue on their side but files are large and difficult to download locally.” - Source

For teams running high-volume extraction operations where time equals money, or for real-time data applications where delays impact user experience, performance becomes a critical factor in vendor selection.

For teams building AI-powered applications, running production scrapers at scale, or simply wanting transparent pricing without enterprise sales processes, these limitations make exploring alternatives worthwhile.

These four Bright Data alternatives handle proxies, rendering, and anti-bot measures automatically, delivering comparable or better performance than Bright Data’s Web Scraper API at more transparent price points.

While Bright Data built its reputation on proxy infrastructure, Firecrawl is purpose-built for modern web scraping, specifically optimized for AI and LLM applications that need clean, structured data.

The fundamental difference: Bright Data delivers HTML and JSON, requiring post-processing. Firecrawl outputs clean markdown natively, reducing token consumption by 67% and eliminating parsing layers.

Firecrawl completes fresh scrapes in 2-5 seconds, including JavaScript rendering. Bright Data averaged 10.6 seconds per request - more than 2x slower.

“Moved our internal agent’s web scraping tool from Apify to Firecrawl because it benchmarked 50x faster with AgentOps,” - Alex Reibman on X.

Firecrawl’s /agent endpoint uses AI to navigate and gather data from even the most complex websites, finding data in hard-to-reach places and discovering data anywhere on the internet. It accomplishes in a few minutes what would take a human many hours.

const result = await firecrawl.agent({
  url: "https://example.com",
  prompt:
    "Find all products, extract name, price, availability, then get full specs from each product page",
});

The agent handles navigation and extraction autonomously. No selectors, no pagination logic - just describe what you want.

Firecrawl accepts plain English:

from firecrawl import FirecrawlApp

app = FirecrawlApp(api_key='fc-YOUR_API_KEY')

result = app.extract_url('https://example.com/products', {
    'prompt': 'Extract product names, prices, and availability',
    'schema': {
        'type': 'object',
        'properties': {
            'products': {
                'type': 'array',
                'items': {
                    'properties': {
                        'name': {'type': 'string'},
                        'price': {'type': 'number'},
                        'available': {'type': 'boolean'}
                    }
                }
            }
        }
    }
})

When websites change their CSS classes, Firecrawl’s extraction continues working while Bright Data’s selectors break.

Unlike Bright Data’s unpredictable pay-per-GB model, Firecrawl charges 1 credit per successful scrape regardless of page size or rendering needs.

One user noted the economic impact: “Firecrawl is impressive, saving us 2/3 the tokens and allowing gpt3.5turbo use over gpt4. Major savings in time and money.”

• n8n: Build scraping workflows visually
• Zapier & Make: Connect to 6,000+ apps
• LangChain/LlamaIndex: Single-line scraping in AI pipelines
• Flowise/Langflow: Pipe data into AI agents

While Firecrawl is API-native, it integrates seamlessly with no-code and low-code platforms. As one reviewer explained, “Firecrawl has been an absolute game-changer for my web scraping projects. As someone who just started integrating it with n8n, I was impressed by how seamless the setup process was.”

Choose Firecrawl if you:

• Build AI applications (chatbots, RAG, ML models)
• Need LLM-ready markdown without post-processing
• Work with JavaScript-heavy sites
• Want sub-5-second response times
• Need complex workflows handled by AI agent
• Want transparent, predictable pricing
• Prefer testing without sales calls

Start scraping with Firecrawl’s free tier.

Apify is a full-stack web scraping platform that combines a powerful API with a marketplace of 4,000+ pre-built scrapers called Actors, offering broader coverage than Bright Data’s 120 no-code scrapers.

The core difference is architectural: Bright Data offers officially maintained scrapers for 120 domains. Apify’s community-driven marketplace provides 4,000+ Actors covering virtually every popular website.

Apify’s Actor marketplace eliminates building scrapers from scratch. Need to scrape Instagram, TikTok, LinkedIn, Amazon, or Google Maps? There’s already an Actor handling site-specific anti-bot measures and pagination.

Popular Actors:

• Instagram Scraper - posts, profiles, hashtags, stories
• LinkedIn Scraper - company data, jobs, profiles
• Google Maps Scraper - business listings with reviews
• Amazon Product Scraper - details, prices, reviews
• Twitter/TikTok Scrapers - content and user data

Bright Data’s 120 scrapers are officially maintained but cover fewer platforms. Apify’s community model provides 33x more options, though quality varies by Actor.

Unlike Bright Data’s fixed infrastructure, Apify lets you build, host, and run custom scrapers on their cloud. Code locally or in their Web IDE using Node.js or Python, then deploy to scalable infrastructure with automatic proxy rotation and browser management.

This means you can:

• Start with a marketplace Actor
• Customize it for your needs
• Deploy to Apify’s cloud
• Scale without managing servers

Choose Apify if you:

• Need pre-built scrapers for specific platforms (Instagram, TikTok, LinkedIn)
• Want broader coverage (4,000 vs 120 scrapers)
• Prefer API-first architecture
• Need lower entry price ($49 vs $500+)
• Want to deploy custom scraping logic to the cloud
• Building workflows with Zapier, Make, or n8n

Apify’s marketplace model delivers more coverage at lower cost, but requires evaluating individual Actor quality before production use.

ScrapingBee offers a developer-friendly scraping API with transparent pricing that puts you in control. Unlike Bright Data’s unpredictable pay-per-GB model, ScrapingBee uses opt-in credit multipliers where you explicitly enable features and know exactly what they’ll cost.

The critical difference: Bright Data charges $1.50-$2.50 per 1,000 requests regardless of complexity. ScrapingBee’s parameters are disabled by default - you opt in explicitly, and credit multipliers apply only when enabled.

ScrapingBee’s credit system eliminates surprise costs:

• Base request: 1 credit
• With JavaScript rendering: 5 credits (5x)
• Premium proxies: 10 credits (10x)
• Both JS + premium: 25 credits (25x)

You enable these explicitly per request. No scenario where a technical change multiplies your costs without warning.

Simple targets cost $0.10-$0.20 per 1K, while protected sites with full parameters run $2.50-$2.90 per 1K. Average cost: $0.80 per 1K vs Bright Data’s $1.50 minimum.

ScrapingBee uses headless Chrome for JavaScript rendering, handles CAPTCHA solving and browser fingerprinting automatically, and rotates through 40M+ IPs with 50+ country targeting - all controlled through simple API parameters.

Choose ScrapingBee if you:

• Want transparent, predictable pricing
• Prefer opt-in parameters vs forced static rates
• Need developer-friendly API integration
• Budget-conscious small to medium projects
• Want to avoid $500+ minimum commitments

Scrape.do positions itself as a performance-first web scraping API with aggressive caching and transparent opt-in pricing.

Like ScrapingBee, Scrape.do disables all parameters by default. You opt in explicitly:

• Base request: 1 credit ($0.12 per 1K)
• JavaScript rendering: 5x multiplier
• Premium proxies: 10x multiplier
• Both combined: 25x multiplier

Simple targets cost $0.12 per 1K (12x cheaper than Bright Data’s $1.50), while fully protected sites run $2.90 per 1K. Average: $0.80 per 1K - nearly half of Bright Data’s $1.50 minimum.

Choose Scrape.do if you:

• Prioritize speed (4.7s vs 10.6s average)
• Want transparent pricing without surprise spikes
• Need cost-effective scraping ($0.80 vs $1.50 per 1K)
• Prefer genuine free tier for testing (1,000 requests/month)
• Budget-conscious high-volume operations

If you specifically need Bright Data’s proxy network capabilities rather than web scraping tools, here are the best alternatives for raw proxy infrastructure.

Oxylabs operates 175M+ proxy IPs across 195 countries, delivering the highest success rates and fastest response times among premium proxy providers.

Key advantages:

• Fastest proxy response times (0.6s average)
• Highest success rate tested (99.95%)
• Lower residential proxy costs ($8/GB vs $10.50/GB)
• Premium customer support with dedicated account managers

Drawbacks:

• Still enterprise-focused with $75 minimum
• Pay-per-GB model creates similar unpredictability
• Complex pricing structure requiring sales contact

• Need premium proxy infrastructure with best-in-class performance and willing to pay enterprise rates.

IPRoyal takes a different pricing approach with unlimited bandwidth on datacenter proxies at flat per-IP rates, eliminating the budget unpredictability that plagues pay-per-GB models.

Key advantages:

• Unlimited datacenter bandwidth at $1.57/IP monthly
• Flat pricing eliminates surprise billing spikes
• Lower residential proxy costs ($7/GB vs $10.50/GB)
• Good ecommerce performance (Shopify, moderate protection sites)

Drawbacks:

• Smaller IP pool (32M vs 150M+)
• Lower success rate (98.2% vs 99.17%)
• Performance can degrade under heavy load

• Cost predictability matters more than having the absolute largest proxy pool. Ideal for high-volume datacenter proxy operations where unlimited bandwidth prevents surprise charges.

Decodo (formerly Smartproxy) delivers the fastest proxy response times tested while costing 80% less than Bright Data for residential proxies.

Key advantages:

• Fastest response times (0.54s average)
• 80% cheaper residential proxies ($2.20/GB vs $10.50/GB)
• Comparable success rates (99.68% vs 99.17%)
• Intuitive dashboard, quick setup
• Unlimited concurrent sessions

Drawbacks:

• Smaller IP pool (115M vs 150M+)
• Fewer management tools than enterprise solutions
• Minor throttling during ultra high-demand events

Want premium performance without enterprise pricing. Best for mid-market businesses needing reliable proxies with transparent billing at accessible price points.

For most teams, proxy infrastructure alone isn’t the bottleneck. Modern web scraping requires handling JavaScript rendering, CAPTCHA solving, and data extraction - capabilities where purpose-built scraping APIs like Firecrawl outperform raw proxy solutions regardless of IP pool size.

Bright Data built its reputation on enterprise proxy infrastructure, and those proxies perform well. But the web scraping API underperforms (10.6s vs sub-5s competitors), pricing targets only large organizations, and the platform wasn’t designed for modern AI workflows requiring markdown-ready data.

If you’re looking for a web scraping solution rather than raw proxy infrastructure, Firecrawl eliminates these pain points entirely. No proxy management, no surprise billing spikes, no 10-day support delays. Just clean, reliable web scraping with automatic proxy routing, JavaScript rendering, AI-powered agents, and transparent pricing.

For proxy-specific needs, Decodo delivers 80% cost savings with the fastest response times, while Oxylabs provides premium performance for enterprise budgets.

Test Firecrawl’s Playground to see the difference before committing to anything. No signup required.

1. What is the best alternative to Bright Data for AI applications?

Firecrawl is purpose-built for AI workflows, delivering native markdown output that reduces LLM token consumption by 67%. Unlike Bright Data’s HTML/JSON requiring post-processing, Firecrawl integrates directly with LangChain, LlamaIndex, and custom models.

2. Why are users switching from Bright Data to other tools?

Users cite unpredictable pay-per-GB pricing ($10.50/GB residential), $500+ minimums, slow 10.6s response times, inconsistent customer support (9-day resolution times), and lack of AI-optimized outputs. Alternatives offer transparent pricing and faster performance.

3. Is Bright Data good for web scraping?

Bright Data’s proxies excel, but its Web Scraper API underperforms with 10.6s response times versus competitors’ sub-5s speeds. Purpose-built scraping APIs like Firecrawl deliver 2-5s response times with automatic proxy management and AI-ready markdown output.

4. What’s the cheapest alternative to Bright Data?

Scrape.do offers the lowest cost at $0.80 per 1K requests average versus Bright Data’s $1.50 minimum. Firecrawl provides better value with transparent 1-credit-per-page pricing, AI-native features, and a generous free tier for testing.

5. Which alternative has the fastest response times?

Decodo delivers 0.54s for proxies (fastest tested). For complete web scraping solutions, Firecrawl averages 2-5s with automatic JavaScript rendering, while Scrape.do achieves 4.7s - both significantly faster than Bright Data’s 10.6s average.

6. Can I use web scraping APIs for AI and LLM applications?

Yes. Firecrawl is specifically designed for AI applications, outputting clean markdown that integrates seamlessly with LangChain, LlamaIndex, and RAG systems. Bright Data returns HTML/JSON requiring extensive post-processing, increasing development time and token costs.

7. Does Firecrawl replace the need for Bright Data’s proxy infrastructure?

Completely for web scraping. Firecrawl includes automatic proxy management with basic, stealth, and auto modes plus location targeting built-in. You don’t need to purchase, configure, or manage separate proxy infrastructure - everything works through simple API parameters.