10 Best Amazon Scrapers Tested: What Actually Works in 2026

Amazon generated in net sales last year, with over 60% of units sold by third-party sellers. That is a staggering amount of product, pricing, and review data — and every ecommerce team, FBA seller, and market researcher wants a piece of it.

The problem? Scraping Amazon in 2026 is genuinely difficult. I've spent years building AI-powered data tools at Thunderbit, and even our team respects how aggressively Amazon defends its pages. CAPTCHAs, browser fingerprinting, dynamic rendering, rate limiting — the anti-bot stack is layered and evolving. Reddit threads are full of users saying things like and So I wanted to cut through the noise. My team and I dug into 10 Amazon scrapers — from no-code Chrome extensions to enterprise APIs — and evaluated them on what actually matters: success rate, speed, cost, review pagination, anti-bot handling, and whether a non-developer can realistically use them. This guide covers every angle, whether you write Python for fun or just want a spreadsheet of competitor prices by lunchtime.

No-Code vs. API vs. DIY: Which Type of Amazon Scraper Do You Actually Need?

Before you pick a tool, pick a category. Most "best Amazon scraper" roundups assume you're a developer shopping for an API. That's a bad assumption. FBA sellers, ecommerce ops teams, and marketers are searching for these tools too — and they don't want to manage proxy rotation or parse raw JSON.

This is the framework I recommend:

Most Amazon scraper lists are still API-centric. They don't give business-user, no-code workflows the same analytical treatment. If you're a solo FBA seller or a marketing analyst, you shouldn't have to learn about headless browsers just to get a list of competitor prices. That's why this guide covers all three categories equally.

My advice: decide which bucket you're in before you compare tools. A Chrome extension that exports to Google Sheets in two clicks is not competing with an enterprise API that delivers NDJSON to Snowflake. They solve different problems for different people.

What to Look for in the Best Amazon Scrapers in 2026

I evaluated every tool across 10 criteria. These aren't abstract — they map directly to the reasons Amazon scraping jobs fail, credits get wasted, or business decisions get made on bad data.

Success Rate and Anti-Bot Handling

This is the single most important metric. A cheap scraper that breaks under real volume is worse than useless — it wastes your time and gives you false confidence in incomplete data.

Amazon's anti-bot systems are layered: browser fingerprinting, CAPTCHA walls, dynamic rendering, rate limiting, and more. benchmarked 11 scraping APIs across 15 protected websites. Amazon's average success rate at 2 requests per second was — not bad overall, but the variance between tools is huge, especially on review pages.

Vendor self-reported success rates and independent benchmarks often tell different stories. found success rates ranging from 96% (Bright Data) down to 11% (Decodo) on review extraction specifically. The tool that looks great on product pages can completely fall apart on reviews.

Speed and Response Time

Speed matters when you're monitoring thousands of ASINs or refreshing a large catalog. Typical response times across the tools I tested range from about 2 to 12 seconds per request. reported times from ~3 seconds (Scrape.do, Decodo) to ~12 seconds (ScraperAPI).

The pattern is consistent: tools that return richer, more structured output tend to be slower. Bright Data, for example, often returns hundreds of structured fields per product but takes 10+ seconds. Decodo and Zyte are faster but less granular.

Cost per 1K Requests at Different Tiers

Pricing in this space is a mess. Some tools charge per request, some per result, some per credit, some per "protected request." And the unit cost changes dramatically at 10K, 100K, and 1M request tiers.

The fairest way to compare is to look at what you actually pay per 1,000 successful results at your expected volume. I'll break this down tool by tool below, but the range is wide: from free tiers to well above $3 per 1K requests, depending on the tool and workload.

Free Tier and Freemium Options

Many users want to test before committing. Several tools offer meaningful free tiers — Thunderbit, ScrapingBee, Apify, and Zyte all let you try before you buy. If you're just doing one-off research, a free tier might be all you need.

Endpoint Coverage, Pagination, and Output Formats

Not every tool covers the same Amazon page types. The core endpoints are:

• Product detail pages (PDP)
• Search results
• Reviews
• Seller pages
• Bestsellers
• Offers / buy box / variation pages

Output formats matter too. JSON is great for pipelines, but business users want CSV, Excel, or direct export to Google Sheets, Airtable, or Notion. Thunderbit is the strongest on direct business-tool exports; Bright Data is the strongest on cloud/data-platform delivery.

And then there's the review pagination problem — which I'll cover in depth below, because it's the single biggest frustration users report.

Geo-Targeting and Marketplace Coverage

Amazon's product visibility, availability, and pricing vary by country and sometimes by ZIP code. If you're an international seller or tracking prices across Amazon US, UK, DE, JP, and others, you need a tool that supports marketplace-level (and ideally ZIP-level) geo-targeting. , , and all document this capability.

The 10 Best Amazon Scrapers at a Glance

Below is the most comprehensive comparison table I could build from current vendor docs, independent benchmarks (, , ), and hands-on research. Where public data is incomplete, I've noted it.

Note: Success rates are drawn from , , and benchmarks where available. Vendor self-reported numbers are noted separately in individual sections.

1. Thunderbit

is the tool we built at our company, so I'll be upfront about that — but I'll also be specific about what it does and doesn't do.

Thunderbit is an AI-powered Chrome extension designed for business users who need Amazon data without writing code. You install the extension, navigate to any Amazon product page, search results page, or reviews page, and click "AI Suggest Fields." The AI reads the page and proposes column names and data types. You click "Scrape," and the data lands in a structured table you can export to Excel, Google Sheets, Airtable, Notion, or download as CSV/JSON.

For popular Amazon pages, Thunderbit also offers — pre-built configurations that work in a single click. There are templates for , , and .

What makes Thunderbit genuinely different from API tools:

• Subpage scraping: You can enrich a list of product URLs by having Thunderbit visit each product detail page and append specs, reviews, or other data — all without code.
• Pagination scraping: Thunderbit handles both click pagination and infinite scroll, so you can extract full review sets instead of just the first page. This is documented in .
• Field AI Prompt: During scraping, you can add instructions like "categorize this review as positive/negative/neutral" or "extract the main complaint." The exported spreadsheet already contains labeled, structured insights — not just raw text.
• Scheduled scraping: Describe the interval in natural language, input your URLs, and click "Schedule." Useful for recurring price monitoring.
• Browser scraping mode: Because Thunderbit runs in your real browser session, it naturally handles many anti-bot measures that trip up API-based tools. There's also a cloud scraping option for larger jobs.

Free data exports to Excel, Google Sheets, Airtable, and Notion are included — no paywall for getting your data out.

Who Should Use Thunderbit

• FBA sellers doing one-off competitor or review research
• Ecommerce ops teams monitoring prices without engineering support
• Marketers who need review exports and quick sentiment analysis
• Anyone who values spreadsheet-ready output over API plumbing

Pros and Cons

Pros:

• Lowest setup friction in the list — install, click, export
• AI field suggestions reduce guesswork
• Built-in data labeling and translation during extraction
• Pagination + subpage scraping fit real ecommerce workflows
• Free exports to business tools

Cons:

• Browser-centric product — not designed for heavy backend data pipelines
• No public third-party Amazon success-rate benchmark yet
• Thunderbit Open API exists for developers, but the core product is aimed at non-coders

2. Bright Data

is the heavyweight in this space. It has the largest proxy network (), a dedicated Amazon Scraper API with 437+ pre-built endpoints, and enterprise-grade delivery options.

In , Bright Data scored success on product pages and returned per product — far more than any other tool tested. On reviews, it hit . That depth is unmatched.

Bright Data also offers Amazon Datasets — pre-collected, structured data you can purchase without running your own scraping jobs. Output delivery goes to JSON, NDJSON, CSV, webhook, S3, Snowflake, Azure, and GCS. Async jobs support up to .

Pricing is pay-per-success (no charge for failed requests), starting around on pay-as-you-go, with a one-week free trial including 1K requests.

Pros and Cons

Pros:

• Deepest structured output in any public benchmark
• Enterprise compliance (GDPR, CCPA, ISO 27001)
• No-code scraper interface available alongside the API
• Pay-per-success pricing

Cons:

• Higher per-request cost than budget options
• Slower response times (~10s+ in some benchmarks)
• Complexity can overwhelm solo operators or small teams

3. Oxylabs

is a premium API option with a strong proxy infrastructure (100M+ IPs) and dedicated Amazon endpoints for product, search, pricing, sellers, and bestsellers. Its OxyCopilot AI assistant lets you set up API calls using natural language — a nice touch for developers who want to move fast.

placed Oxylabs among the top performers, and gave it 92% success at about 4 seconds. Oxylabs also offers a product variation scraper for color/size/model combinations and multi-format output (JSON, HTML, Markdown, screenshots in one call).

Pricing starts around for JS-free calls, with a trial covering up to 2,000 results.

Pros and Cons

Pros:

• Strong benchmark performance
• Product variation scraper is a unique feature
• Multi-format output in a single call

Cons:

• Dedicated amazon_reviews source was due to Amazon's review access changes
• Not the most beginner-friendly interface

4. ScraperAPI

focuses on simplicity and reliability. It handles proxy rotation and CAPTCHA solving behind the scenes, and its Structured Data Endpoint returns clean JSON for Amazon products, search results, reviews, and bestsellers.

In , ScraperAPI hit on product pages, though at a slower ~11.8 seconds average. The async reviews endpoint explicitly supports pageNumber, which is important for review pagination.

ScraperAPI also offers a DataPipeline feature — a low-code batch scraping tool with templates for common Amazon jobs.

Pricing: , then $49/month at the Hobby tier for 100,000 API credits.

Pros and Cons

Pros:

• Very high success rate in public benchmarks
• Async review endpoint with explicit pagination support
• DataPipeline for low-code batch jobs

Cons:

• Slower than some premium options
• Credit multipliers for premium proxy tiers can increase effective cost

5. Decodo

(formerly Smartproxy) is the budget-friendly pick for product and search-centric Amazon scraping. It supports dedicated Amazon endpoints for , and offers across 21 Amazon marketplaces.

In , Decodo hit on product pages. But here's the catch: gave Decodo just on review extraction. That's a massive gap.

Pros and Cons

Pros:

• Fast and affordable for product/search scraping
• Strong geo-targeting (ZIP-level)
• Good endpoint breadth

Cons:

• Very weak on review extraction in independent benchmarks
• Not the right tool if reviews are core to your workflow

6. ScrapingBee

is a beginner-friendly API with a clean onboarding experience and on signup. It covers Amazon product and search endpoints, with geo parameters including .

Pricing starts at , with Amazon requests costing 5 credits (light) or 15 credits (JS-heavy).

Pros and Cons

Pros:

• Easy to get started
• Generous free tier for testing
• Good geo-targeting

Cons:

• Narrower endpoint coverage than Bright Data or Oxylabs
• No dedicated reviews endpoint documented publicly

7. Nimbleway

is less of a classic scraper and more of an agentic data platform. Its strongest Amazon evidence is around amazon_pdp and amazon_serp agents, with built-in residential proxies, structured output, and strong localization.

gave Nimble but at a slower ~13 seconds. Pricing examples include and rates around .

Pros and Cons

Pros:

• Strong localization and geo-targeting
• Agentic approach can handle complex workflows
• 7-day free trial

Cons:

• Higher price point
• Narrower Amazon endpoint catalog than some API-first tools

8. Zyte

is a generalized web data platform with ecommerce parser add-ons. It supports Amazon extraction through generic entities like product, productList, productNavigation, and SERP.

Zyte was the fastest in some benchmarks — in Proxyway's general test — and competitive at scale (~$0.20/1K at high volume). It offers for 30 days.

But gave Zyte just on reviews, so its Amazon-specific story is stronger on product pages than on review extraction.

Pros and Cons

Pros:

• Fast response times
• Cost-efficient at enterprise scale
• Broad web platform (not just Amazon)

Cons:

• Review extraction is weaker than product page scraping
• Requires more technical setup than no-code options

9. ZenRows

positions itself around dedicated Amazon scraper APIs for , layered on top of a broader scraping browser and universal scraper API.

Pricing starts at with a . Vendor materials emphasize anti-bot bypass, JavaScript rendering, and structured outputs.

Pros and Cons

Pros:

• Broad Amazon endpoint coverage
• Good documentation
• Anti-bot bypass and JS rendering

Cons:

• Public benchmark signals are more mixed than Bright Data or Oxylabs
• Higher entry price than some competitors

10. Apify

is the most flexible option here because it's not one scraper — it's a platform with many Amazon-specific actors, each with different pricing, quality, and capabilities. You can find actors for products, reviews, sellers, bestsellers, and niche use cases in the .

returned about 5,946 out of 6,000 URLs, implying ~99.1% success. Several actors explicitly address Amazon's review cap by using filter fan-out or alternative traversal — though still pop up in production.

Pricing: , then platform plans from $49/month plus actor-specific costs.

Pros and Cons

Pros:

• Broadest task flexibility
• Community actors for niche Amazon workflows
• Good for developers who want to customize

Cons:

• Quality varies by actor
• Less turnkey than dedicated Amazon APIs
• Can be slow for large-scale runs

The Review Pagination Test: Can These Amazon Scrapers Get All Your Reviews?

Most "best Amazon scraper" posts skip this section entirely. It's the one that matters most to FBA sellers and product researchers.

Most Amazon scraping tools only return the first page of reviews (typically 10 reviews) unless you explicitly handle pagination. Users on forums describe this as their top frustration: "Most APIs I tried only return the first 10 reviews" and "I need something that can collect hundreds or even thousands of reviews."

It got worse in late 2024. a progression from ~100 reviews per page 10 in August 2024, to only page 5 in September, to non-logged-in review pages being blocked by November 2024. its dedicated amazon_reviews source because extensive review data became tied to logged-in access. that many providers return only 10–30 reviews by default.

This is how each tool handles it:

If review analysis is central to your workflow, pay close attention to this table. The difference between "first page only" and "full pagination" is the difference between 10 reviews and 500+.

Which Amazon Scraper Is Best for Your Use Case?

Generic tool lists don't help you decide. Your workflow should drive your choice.

Price and Stock Monitoring

Scheduled scraping, high reliability, cost-efficiency at scale — that's the job.

• Bright Data — enterprise depth, cloud delivery, pay-per-success
• Decodo — fast, affordable product/search scraping
• Thunderbit — scheduled scraper with natural-language intervals, direct spreadsheet output

Review Analysis for FBA Sellers

Full review pagination, ASIN-based scraping, and AI-powered sentiment analysis are non-negotiable here.

• Thunderbit — AI labeling + subpage scraping + pagination; exported data is already categorized
• Bright Data — best structured review output in independent benchmarks
• Apify — custom pagination logic and workaround-heavy use cases

Product Catalog and Data Enrichment

You need broad endpoint coverage, bulk export, and structured output.

• Bright Data — deepest structured fields ()
• Oxylabs — strong API coverage and reliability
• ScraperAPI — structured endpoints with simpler economics
• Thunderbit — spreadsheet-native enrichment for business teams

One-Off Competitive Intelligence

No-code, fast setup, free or low cost.

• Thunderbit — free tier, Chrome extension, 2-click workflow
• ScrapingBee — clean API on-ramp for simple product/search pulls
• Apify — customizable without building from scratch

The Anti-Bot Reality: Why Amazon Scraping Fails (and How These Tools Handle It)

Most roundup posts gloss over this: no tool has a 100% success rate on every Amazon page type at all times. If someone tells you otherwise, they're selling you something.

Amazon's defenses in 2026 include:

• Rate limiting — too many requests from the same IP and you're blocked
• CAPTCHA walls — especially on review pages and search results
• Browser fingerprinting — Amazon can detect headless browsers and datacenter IPs
• Dynamic rendering — page content loads via JavaScript, breaking simple HTML parsers
• Localization and delivery-context variance — prices and availability change by location and login state
• Review access restrictions — review pages increasingly require logged-in sessions or internal request paths

Amazon as protected by in-house defenses and notes that bot resistance has "toughened significantly." rate limiting, CAPTCHAs, and browser fingerprinting as key blockers. And says scraper bots account for of web traffic on average.

Each tool takes a different approach:

• Bright Data, Oxylabs, Decodo: Large residential proxy networks, auto-rotation, CAPTCHA solving, JavaScript rendering
• ScraperAPI, ScrapingBee, ZenRows, Zyte: Proxy rotation and anti-bot bypass built into the API layer
• Nimble: Residential proxies with agentic workflow support
• Apify: Actor-dependent; some actors use advanced browser emulation, others are simpler
• Thunderbit: Browser scraping mode operates within the user's real browser session, naturally handling many fingerprinting and CAPTCHA challenges that trip up API-based tools. Cloud mode adds proxy infrastructure for larger jobs.

, , and all use different methodologies, test different page types, and measure at different request rates. That's why you'll see different success rates for the same tool depending on the source. I've cited the benchmark source for every number in this article so you can judge for yourself.

From Scrape to Insight: Turning Raw Amazon Data into Actionable Summaries

Something I've noticed after years of building data tools: users don't just want raw data. They want to know what customers love and hate about a product. They want a categorized breakdown of reviews, not a 10,000-row spreadsheet of unstructured text.

Forum users describe the ideal tool as one that "scrapes the reviews and gives you a summarized breakdown of positives and negatives." Yet almost no Amazon scraper roundup covers the end-to-end workflow from extraction to analysis.

The workflow I recommend:

1. Scrape: Extract all reviews for an ASIN with full pagination (not just the first 10).
2. Structure: Output as a clean table with columns: review text, star rating, date, verified purchase.
3. Analyze: Use AI to label sentiment, extract themes, and summarize top pros/cons.

Thunderbit can handle all three steps in a single flow. The Field AI Prompt feature lets you add instructions like "categorize this review as positive/negative/neutral" or "extract the main complaint" directly during scraping. The exported spreadsheet already contains labeled, structured insights — not just raw text. For review analysis, this is a genuine differentiator versus API tools that only return raw JSON you then need to process separately.

If your tool doesn't have built-in AI labeling, you can still pair any scraper's structured output with ChatGPT or Claude for post-scrape summarization. The key is to get clean, paginated, structured data out first — and then layer on analysis.

Side-by-Side Comparison: All 10 Best Amazon Scrapers

For quick reference, the full comparison with pricing context at different tiers:

Which Amazon Scraper Should You Pick?

My quick-reference cheat sheet:

• Best no-code for business teams: Thunderbit
• Best overall for scale and data depth: Bright Data
• Best premium API balance: Oxylabs
• Best simple structured API: ScraperAPI
• Best budget-friendly for product/search: Decodo
• Best beginner-friendly API: ScrapingBee
• Best localized enterprise workflows: Nimble
• Best enterprise cost efficiency and speed: Zyte
• Best Amazon endpoint breadth among developer APIs: ZenRows
• Best for custom workflows and actor flexibility: Apify

My honest advice: match your tool to your skill level, volume, and use case. If you're not writing code and you want Amazon data in a spreadsheet today, start with . If you're building a production pipeline that refreshes 100K ASINs nightly, Bright Data or Oxylabs are built for that. And if you want maximum flexibility and don't mind configuring actors, Apify gives you the most room to experiment.

Test on your actual Amazon page types before committing budget. Product pages, search results, and review pages each have different success profiles — and the tool that aces one may struggle on another.

Happy scraping — and may your data always be clean, structured, and ready for the next decision.

FAQs

1. Is it legal to scrape Amazon product data?

Scraping publicly available Amazon data is generally considered lower-risk legally, but Amazon's own prohibit data mining, robots, and similar extraction tools. The strongest modern precedent is , where the court held that logged-off scraping of public data was permissible. However, the 2026 shows higher risk for logged-in or agentic access. Always review Amazon's current terms and consult legal counsel for your specific use case.

2. How do you scrape all Amazon reviews, not just the first page?

Most tools only return the first 10 reviews by default. To get full review sets, you need a tool that supports pagination — either through click-based page traversal (like Thunderbit's ), async API loops with explicit page numbers (like ScraperAPI), or custom actor logic (like Apify). Amazon tightened review access in late 2024, so this is now one of the biggest differentiators between tools. See the review pagination benchmark table above for a tool-by-tool breakdown.

3. Can I scrape Amazon without coding?

Yes. Thunderbit is a Chrome extension that lets you scrape Amazon product pages, search results, and reviews with AI-powered field suggestions and — no code required. Apify also offers a no-code marketplace, though it's less turnkey for business users. If you want data in a spreadsheet without touching an API console, no-code tools are the way to go.

4. How much does it cost to scrape Amazon at scale?

The range is wide: from free tiers (Thunderbit, Apify, ScrapingBee, Zyte) to well above $3 per 1K requests at enterprise scale. Bright Data charges around $2.5/1K on pay-as-you-go; Oxylabs starts at ~$0.50/1K for JS-free calls; Decodo and ScrapingBee offer low-cost entry points. Review scraping and JS-heavy flows cost more than plain product-page fetches. See the pricing comparison table above for tool-by-tool details.

5. What output formats do Amazon scrapers support?

Common formats include JSON, CSV, and Excel. Thunderbit also exports directly to . Bright Data supports delivery to S3, Snowflake, Azure, and GCS. Apify offers JSON, CSV, Excel, XML, and HTML. For business users, the ability to export directly to a spreadsheet or workflow tool — without writing a parser — is often the deciding factor.

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