Best Amazon Scraper APIs in 2026: Tested and Ranked

Amazon is the single most scraped website in the world. Not because it's easy — it's one of the hardest — but because the data it holds is commercially valuable in a way that almost no other web property matches. Real-time product prices, BSR rankings, Buy Box ownership, seller profiles, review sentiment, deals and lightning deals. For price monitoring tools, competitive intelligence platforms, affiliate marketers, and market research teams, Amazon data is foundational.

General-purpose scraping tools are struggling to keep up with complex anti-bot measures, while dedicated solutions are offering deeper, more structured insights. Amazon's infrastructure makes this especially true. AWS WAF, Imperva, and Amazon's own custom bot detection layer combine into one of the most sophisticated anti-bot stacks any scraper encounters. A tool that passes Cloudflare easily can fail entirely on Amazon.

This article covers every meaningful Amazon scraper API in 2026 — what each returns, what it costs, where it breaks down, and which fits your use case. ScrapeBadger's Amazon Scraper API is on this list and we're direct about how it compares.

Why Amazon Is Technically Harder Than Most Targets

The best Amazon scraper API must deliver on three core fronts: reliable anti-bot evasion, predictable pricing, and structured data output.

Anti-bot evasion is the constraint that separates tools on this list. Amazon runs:

AWS WAF — Amazon's own Web Application Firewall sitting in front of their infrastructure. Operates at the network edge and evaluates requests before they reach any application layer. Datacenter IPs and known scraping tool fingerprints are rejected here.

IP reputation and rate limiting — Amazon's scale means they've observed more scraping IP addresses than any other target. Residential proxies are mandatory. The geo-matching requirement makes it harder: a request from a UK residential IP hitting amazon.de might return different pricing than the actual German market prices, making country-matched proxies a requirement for accurate data, not a nice-to-have.

JavaScript rendering — Amazon product pages load content dynamically. A+ content, review summaries, frequently-bought-together data, and variant pricing often require JavaScript execution to appear in the response. Tools that return raw HTML without rendering miss fields that appear populated in the browser.

TLS fingerprinting — the same JA3/JA4 fingerprinting layer covered in the ScrapeBadger Cloudflare bypass guide. Amazon's infrastructure checks TLS profiles against known browser signatures. Python's requests library fails here before any application data is exchanged.

The practical consequence: success rates on Amazon vary more between providers than on almost any other target. Success required not just a 200 status code but validated HTML content — pages that returned challenge screens were counted as failures. A provider with 95% reported success that counts challenge pages as successes has a real success rate considerably lower.

What Data Amazon Exposes Programmatically

Before comparing tools, understand the full data model. A production Amazon data pipeline needs:

Product detail pages — title, price, original price, Buy Box winner, all seller offers, ASIN, brand, availability, BSR (Best Sellers Rank) across categories, star rating, review count, A+ content, product specifications, dimensions and weight, variants (size, colour, style) with per-variant pricing and availability.

Search results — organic product listings with titles, prices, ratings, sponsored indicators, and ASINs. Critical for category monitoring and keyword-based competitive analysis.

Reviews — reviewer name, rating, title, body, verified purchase status, helpful votes, and date. The review data that drives sentiment analysis, product research, and competitive intelligence.

Seller offers — the complete list of sellers offering a product, their prices, condition, fulfillment type (FBA vs FBM), and shipping estimates. This is where price intelligence gets specific: who owns the Buy Box right now, who's close to winning it, and what the full competitive offer landscape looks like.

Bestsellers, new releases, and deals — category-level intelligence that shows which products are trending, which are newly launched, and which are running time-limited promotions.

Seller profiles — seller rating, total feedback count, recent feedback breakdown, and storefront listings. Essential for marketplace intelligence and competitor seller analysis.

The 7 Best Amazon Scraper APIs in 2026

1. ScrapeBadger — Best Overall Amazon Scraper

ScrapeBadger's Amazon Scraper API launched with 14 dedicated endpoints covering the complete Amazon data model — search, product detail, offers, reviews, bestsellers, new releases, deals, category browsing, and full seller intelligence including storefront and feedback.

What Makes It the Right Choice

The endpoint depth is the headline differentiator. Most Amazon scrapers cover product pages and search results. ScrapeBadger covers the full Amazon data surface: product detail with variants and A+ content, the complete offers list (not just the Buy Box winner), paginated reviews with filters, bestseller and new release lists by category, current deals including lightning deals, category browsing, seller profiles, seller storefronts, and buyer feedback per seller. The full endpoint reference is at docs.scrapebadger.com/amazon/overview.

20 marketplace coverage — every major Amazon domain from amazon.com through amazon.eg, with country-matched residential proxies on every request. Country-matching matters specifically for pricing accuracy: when you query amazon.de, requests route through German residential IPs to return the prices German customers actually see. This is the only way to get accurate local market pricing rather than the prices Amazon shows international visitors.

AWS WAF bypass via Chrome TLS impersonation + origin warmup — ScrapeBadger's anti-bot approach for Amazon specifically uses Chrome TLS impersonation (the same infrastructure underlying the Imperva bypass and Cloudflare bypass), fresh residential sessions, and origin warmup — a session pre-warming technique that builds trust history before hitting high-value product pages. Cold sessions on product detail pages fail at higher rates than warmed sessions; origin warmup addresses this automatically.

Zero credits for failed requests — as covered in the ScrapeBadger data quality article, charging for failed requests creates a misaligned incentive where the provider has no financial motivation to maintain success rates. ScrapeBadger charges nothing for failures — credits are used only when a request returns the data you asked for.

Multi-product platform advantage — teams monitoring Amazon prices often need to combine that data with Google Shopping prices (via the ScrapeBadger Google Shopping endpoint), Google Trends demand signals for the same category, and competitor product pages scraped directly. All of this runs under one ScrapeBadger API key with unified billing. No second vendor for SERP data, no third vendor for general scraping.

For AI agent workflows, the MCP integration exposes every Amazon endpoint as a native tool call. An agent doing product research can query Amazon product data, cross-reference Google Shopping prices, check Google Trends category interest, and pull competitor landing page data — in a single reasoning workflow.

Pricing — flat per-endpoint credit pricing. Product detail costs 10 credits, search 5 credits, offers 8 credits, reviews 10 credits, seller profile 3 credits. Failed requests: 0 credits. Credits never expire, no subscription required. Free trial at scrapebadger.com/amazon-scraper.

Best for: Teams needing the complete Amazon data model across multiple marketplaces; price intelligence platforms; AI agent developers; teams using ScrapeBadger for other data sources who want Amazon added to the same integration.

2. Bright Data — Enterprise Grade, Full Amazon Suite

Bright Data's Amazon scraper sits on their 400M+ IP residential network with pre-built parsers for product pages, search, reviews, offers, and seller profiles. Bright Data leads with a 98.44% average success rate in independent benchmarks, with 400M+ residential IPs across 195 countries.

The data quality is hard to argue with. On Amazon specifically — one of the hardest targets — Bright Data's IP pool size and quality translates directly to success rates that smaller proxy networks struggle to match.

The cost and complexity are the constraints. Web Scraper IDE starts at $499/month. Billing across proxy network, scraper IDE, and dataset layers is complex, and Amazon scraping specifically requires their premium proxy tier to achieve the success rates advertised. Bright Data's Amazon Scraper API is priced at $1.50 per 1,000 records.

Best for: Enterprise teams with formal compliance requirements (ISO 27001, SOC 2) and budgets where the cost premium is irrelevant relative to data reliability.

3. Oxylabs — Reliable Enterprise Infrastructure

Oxylabs Web Scraper API is widely regarded as a reliable, enterprise-ready solution thanks to its extensive proxy network and stable unlocking performance on Amazon and various e-commerce targets. It delivers consistent results even in scenarios where anti-bot protections are strong.

Oxylabs covers product detail pages, search results, seller offers, and reviews with structured JSON output. OxyCopilot (their AI code generation assistant) reduces initial integration time for teams new to Amazon scraping APIs.

Product variation support handles products with multiple options. Each variation returns its own ASIN, price, and availability data. PDP, search, seller offers, best sellers, and category pages all have dedicated endpoints with consistent response structure.

The pricing model uses bandwidth-based billing for parts of their infrastructure, which creates cost unpredictability for Amazon scraping where product page sizes vary. Mid-premium pricing at $4–8/GB depending on tier.

Best for: Enterprise teams already using Oxylabs proxy infrastructure; teams where OxyCopilot's code generation accelerates integration.

4. Decodo — Speed-First at Competitive Pricing

Decodo delivers a near-perfect success rate and excellent response time on Amazon, with their Web Scraping API rolling up specialized scrapers into one product. It includes several endpoints for Amazon, listings, and prices. The tool integrates as a real-time API, proxy, or SDK, providing instructions in eight coding languages. Output comes in autoparsed JSON, HTML, Markdown, or screenshot.

For sub-5s price monitoring, Decodo at 3.88s median response time is one of the speed-first choices. For real-time dashboards where data freshness is the primary constraint, that response time matters. Many Amazon price monitoring use cases don't need sub-second response — but some do, and Decodo's infrastructure is specifically optimised for speed.

Best for: Real-time price monitoring pipelines where response latency is a primary constraint; teams that want proxy and API infrastructure from one provider.

5. ScraperAPI — Simple Integration, Variable Cost Structure

ScraperAPI offers a straightforward Amazon integration with dedicated endpoints for product pages, search results, and seller offers. ScraperAPI focuses on reliability over features, offering a straightforward API that handles proxy rotation and CAPTCHA solving automatically. The API uses a credit-based pricing model where different proxy tiers cost different amounts. Standard requests use 1 credit, premium proxies cost 10 credits, and ultra-premium (required for heavily protected pages) costs 30–75 credits. GitHub

The credit multiplier for Amazon specifically is significant. Amazon requires premium or ultra-premium proxies — which consume 10–75x more credits per request than standard. A plan that looks affordable at the headline credit count becomes considerably more expensive when every Amazon request burns 10–75 credits.

Best for: Developer teams who want a simple HTTP-based integration without platform complexity; teams already using ScraperAPI for other targets who want Amazon added without a second vendor.

6. Zyte — Fastest Response Times

Zyte at 2.58s median response time is the fastest Amazon scraper in published benchmarks. Pricing at $3.00 per 1,000 results on pay-as-you-go, or $150/month for 150 credits.

Zyte's speed advantage comes from their infrastructure architecture — they operate a large network of browser instances specifically optimised for response time rather than breadth of data coverage. For use cases where time-to-data is the critical metric, Zyte is the benchmark.

The data depth is narrower than Bright Data or ScrapeBadger's full endpoint suite. Core product data, search results, and basic review access cover the majority of use cases, but seller intelligence and the deeper Amazon data model are less comprehensively covered.

Best for: Use cases where sub-3s response time justifies the cost; latency-sensitive production applications.

7. Apify — Community Actors, Research-Suitable

Apify's marketplace includes multiple Amazon scraper Actors from community contributors. Some are well-maintained with strong documentation; quality varies by contributor.

The platform's visual interface and scheduling tools make it accessible for non-technical teams. For batch research jobs where a day or two of downtime when Amazon changes its structure is acceptable, community Actors are a practical option.

Best for: Researchers and analysts running batch Amazon data collection; non-technical teams who want a dashboard rather than an API integration.

Side-by-Side Comparison

What Amazon Data Is Actually Used For

Price Monitoring and Competitive Intelligence

The dominant use case. E-commerce sellers, brands, and retailers monitor competitor pricing across ASINs to inform their own pricing strategy. At scale — 10,000+ SKUs monitored daily — this requires an API with reliable sub-10s response times, per-request pricing that doesn't compound across failed requests, and accurate marketplace-specific prices from country-matched proxies.

As covered in the ScrapeBadger price tracking bot tutorial, the architecture for production price monitoring includes schema validation on every response, change detection that fires alerts only on meaningful price moves, and freshness tracking that prevents stale data from entering repricing pipelines.

Buy Box Intelligence

The Buy Box — Amazon's featured seller for a given product — drives the majority of Amazon sales. Winning or losing the Buy Box has immediate revenue consequences. Monitoring which seller owns the Buy Box for your key ASINs, and what pricing strategy is winning it, requires the offers endpoint that returns the complete competitive offer landscape, not just the current Buy Box winner.

ScrapeBadger's /v1/amazon/products/{asin}/offers endpoint returns every seller currently offering a product — pricing, condition, fulfillment type, and Buy Box ownership status — structured for direct ingestion into repricing tools.

Market Research and Trend Analysis

BSR (Best Sellers Rank) data from product pages, combined with bestseller and new releases endpoints, gives a real-time picture of category momentum. Tracking BSR changes over time for a product or category reveals which items are gaining sales velocity before that signal shows up in any other data source.

The deals endpoint exposes which products Amazon is actively promoting with lightning deals and coupons — a signal of both seller strategy and inventory management worth tracking for competitive analysis.

Seller Intelligence

Understanding who the significant sellers are in a category, how their customer feedback evolves over time, and what their full product catalog looks like is the layer of marketplace intelligence most tools don't reach. ScrapeBadger's three seller endpoints — profile, storefront, and feedback — make this available programmatically across all 20 Amazon marketplaces.

AI Agent Product Research

An AI agent doing product sourcing, competitive analysis, or market entry research needs live Amazon data to reason from rather than training data that's months out of date. The MCP server exposes every ScrapeBadger Amazon endpoint as a native tool call to Claude, Cursor, and any other MCP-compatible agent. Setup at docs.scrapebadger.com/mcp/overview.

How to Choose

If you need the complete Amazon data model — seller intelligence, deals, new releases, variants, A+ content — alongside other data sources (Google Shopping prices, SERP rankings, Maps reviews): ScrapeBadger covers everything under one integration. The full endpoint reference covers every field and credit cost before you commit.

If enterprise compliance certification is a hard requirement: Bright Data is the only option with ISO 27001 and SOC 2. The cost premium is real and the billing complexity is real, but for regulated industries the certifications are non-negotiable.

If response latency is the primary constraint and your use case is core product data only: Zyte's 2.58s median response time and Decodo's 3.88s are the speed-first options. Accept narrower data coverage in exchange for speed.

If you want the simplest possible integration: ScraperAPI's HTTP-based approach requires minimal setup. Factor in the credit multiplier for Amazon's premium proxy requirements before comparing costs.

Start with ScrapeBadger's free trial — 1,000 credits, no credit card, no subscription. Test against your specific ASINs, categories, and marketplaces before making any infrastructure decision. The full API documentation at docs.scrapebadger.com/amazon/overview covers every parameter, response field, and code example in Python, Node.js, and cURL.