Best Amazon Data Providers of 2026: Complete Comparison

In this article, you will learn:

• What Amazon data is, why it is so important, and the main obstacles in retrieving it.
• Why counting on an Amazon data provider helps you avoid all those issues.
• The main aspects to evaluate when selecting such a provider.
• A full comparison of the seven best Amazon data providers.

Let’s dive in!

TL;DR: Summary Table with the Best Amazon Data Providers

For a quick overview, explore and compare the top Amazon data providers in the following summary table:

Amazon Data: The Why, What, and How

Before comparing Amazon data providers, you must understand why Amazon data matters, what it includes, and how challenging it is to get.

Why Amazon Data Is So Important

Amazon processes roughly 12.9 million orders per day across more than 25 local marketplaces (e.g., Amazon.com, Amazon.de, Amazon.fr, etc.). That corresponds to ~8,900 orders per minute, which is not surprising considering the total number of products is estimated to be around 600 million.

That activity translates into approximately $518,000 in revenue every minute, with product sales alone reaching over $31 million per hour, and total hourly revenue (including services) exceeding $72 million.

Those purchases are driven by 310+ million customers worldwide, including around 255 million users in the U.S. alone. Crucially, over 60% of all units sold on Amazon come from third-party, independent sellers. That makes Amazon seller data pivotal for understanding the real dynamics of not just Amazon as a retailer, but the broader e-commerce ecosystem built on top of it.

These numbers alone highlight why Amazon data is a foundational asset for e-commerce and market intelligence. Access to this information enables businesses to support a wide range of strategic and operational decisions, including:

• Optimizing product pricing and promotional strategies.
• Monitoring competitors, sellers, and market positioning.
• Identifying the most effective timing for discounts and sales campaigns.
• Understanding which product images, titles, and descriptions drive the highest conversion rates.
• Measuring how reviews, ratings, and customer sentiment influence sales performance.

The insights derived from Amazon data extend far beyond individual use cases, informing product strategy, demand forecasting, brand performance tracking, competitive intelligence across the entire e-commerce lifecycle, and many others.

Types of Amazon Data

At a very high level, Amazon data can be grouped into three main categories:

• Product data: Includes names, ASINs, descriptions, images, prices, variations, categories, and reviews. Important for analyzing trends, optimizing listings, tracking prices, and monitoring product performance.
• Seller data: Covers seller profiles, ratings, fulfillment methods, inventory levels, and pricing strategies. Useful for competitor analysis, marketplace positioning, and identifying top-performing sellers.
• Marketplace analytics: Aggregated data on sales trends, best-sellers, search rankings, and category-level demand. Helps with forecasting, pricing strategy, and market opportunity identification.

As you can see, each offers unique insights for e-commerce, market research, and business strategy.

Challenges of Retrieving Data from Amazon

Collecting Amazon data presents several challenges. The main ones include:

• Anti-bot measures: Amazon actively detects automated requests and blocks or throttles them to prevent scraping.
• CAPTCHAs: Frequent verification challenges require solving mechanisms to prove human activity, especially via the notoriously difficult Amazon CAPTCHA.
• IP blocking and rate limits: Excessive requests from a single IP can trigger temporary or permanent bans, asking for mechanisms to rotate your IP.
• Dynamic page structures: Amazon pages have varying HTML layouts, making automated data parsing complex and requiring AI or advanced solutions that can handle all edge cases.

Why You Need an Amazon Data Provider

Amazon data is unquestionably extremely valuable. At the same time, it is arduous to retrieve reliably and at scale. Thus, the most recommended way to gather it is through a dedicated Amazon data provider.

An Amazon data provider is a service that collects, structures, and delivers all types of Amazon data for analysis, research, and automation. These providers handle all the challenges associated with data retrieval, giving you direct access to the data you need.

In detail, these solutions make Amazon data available in two primary ways:

• Amazon datasets: Pre-collected, structured datasets containing historical and regularly updated Amazon data. These are ideal for market analysis, trend research, or training machine learning models that require consistent snapshots over time.
• Amazon scraping solutions: Tools to retrieve fresh data directly from Amazon product, seller, or search result pages. Using an Amazon scraper is best suited for use cases that rely on up-to-date information, such as price monitoring, tracking stock availability, or conducting rapid competitor analysis.

To maintain a complete and accurate view of the market, most organizations combine both approaches:

• Datasets for historical context and large-scale analysis.
• Scraping solutions for real-time intelligence, even in specialized AI agents or AI-built platforms.

Criteria to Select and Compare Amazon Data Providers

Online, you will find a wide range of Amazon data providers, but not all of them are worth exploring. To identify the best options, you should compare providers across several common aspects, such as:

• Coverage: The types of Amazon data available, such as products, prices, reviews, and seller information.
• Infrastructure: The scalability of the provider, including uptime metrics, success rates, and overall reliability.
• Data freshness: Whether the provider offers static information through an Amazon dataset library or dynamic, real-time data via web scraping Amazon solutions.
• Technical requirements: The skills and technical components needed to access and use the data.
• Compliance: Adherence to GDPR, CCPA, and other relevant data privacy regulations.
• Pricing: The provider’s pricing structure and billing models.

Top 7 Amazon Data Providers

Time to inspect the best Amazon data providers, carefully selected, ranked, and analyzed according to the criteria presented earlier.

Note: If you are interested in Amazon scraper providers, refer to the list of the best Amazon web scraping services.

1. Bright Data

Bright Data started as a proxy provider and has grown into a leading web scraping and data solutions company. Compared to other Amazon data providers, it stands out due to its enterprise-ready, highly scalable, AI-ready infrastructure that supports over 20,000 clients, including several Fortune 500 companies.

When it comes to Amazon data, Bright Data offers Amazon datasets in JSON, CSV, and Parquet formats, with flexible, record-based pricing.

The data is clean, validated, continuously updated, and ready for LLM ingestion, enabling you to gain rich intelligence. It includes detailed product information such as pricing, reviews, ratings, brand names, product categories, sellers, ASINs, images, and more.

For rapid insights, you can access fresh data via dedicated Amazon scraping solutions:

• Amazon Scraper: Collect ASINs, seller names, merchant IDs, titles, URLs, images, category trees, brands, descriptions, sizes, colors, styles, availability, arrival times, initial and final prices, models, features, ratings, and reviews.
• Amazon Price Scraper: Extract pricing data from any Amazon domain to stay ahead of the competition.
• Amazon Seller Scraper: Collect seller data including titles, names, brands, descriptions, initial prices, currencies, availability, and more.
• Amazon ASIN Scraper: Retrieve ASINs from publicly available Amazon products across all domains and URLs.

Each of the above products is available either via an API endpoint, which can be integrated into scripts, AI agents, or data pipelines, or through a no-code scraping solution, perfect for non-technical users.

The Bright Data Amazon scrapers offer 99.99% uptime and a 99.99% success rate, with unlimited scalability thanks to a proxy network of over 150 million IPs and a powerful anti-bot toolkit for CAPTCHA solving and anti-scraping avoidance.

Together, these offerings make Bright Data arguably the best Amazon data provider on the market!

➡️ Ideal for: AI training and market research.

Coverage:

• 641.2+ million Amazon records available across datasets.
• Amazon product data: titles, descriptions, brands, categories, ASINs, availability, currency, images, and pricing.
• Amazon reviews data: review text, ratings, authors, rating scale, product associations (ASIN).
• Amazon seller data: seller IDs, seller names, URLs, feedback, ratings, return policies, and detailed seller profiles.
• Amazon bestseller products and product search datasets.

Infrastructure:

• Dataset marketplace with pre-collected, validated, and structured Amazon data, offering scalable delivery without the need for customer-managed infrastructure.
• Infinitely scalable Amazon Scraper API for data extraction and dataset downloads, powered by a proxy network of over 150 million IPs.
• Integrations and data delivery to Snowflake, Amazon S3, Google Cloud, Azure, SFTP, webhooks, email, and Pub/Sub.
• 99.99% availability.
• 99.99% success rate.
• AI-optimized data, enabling simplified integration with AI agents, pipelines, and workflows.
• 24/7 support and managed data acquisition options.
• Standard SLAs for regular users and custom SLAs for enterprises.

Data freshness:

• Continuously verified, enriched, and refreshed datasets.
• Configurable refresh frequencies: one-time, biannual, quarterly, or monthly.
• Option to receive only new or updated records via Smart Data Updates.
• Possibility to access terabytes of historical data, including from Amazon, via Archive API.
• Separate Amazon Scraper API available for collecting fresh, up-to-date data directly from Amazon web pages without blocks.

Technical requirements:

• Ability to work with structured data formats: JSON, NDJSON, CSV, XLSX, Parquet.
• Familiarity with cloud storage platforms (AWS, GCP, Azure) or Snowflake for data delivery.
• No-code scraping options for using the Amazon Scraper API with no technical requirements.
• Code examples in Python, Node.js, cURL, Java, Ruby, PHP, and Go for simplified integration.
• Managed data retrieval service to get custom Amazon data with no technical expertise needed.

Compliance:

• GDPR and CCPA compliant.
• ISO-certified infrastructure.

Pricing:

• Amazon datasets start from $250 per 100K records.
• Amazon Scraper API starts at $1.50 per 1K records.

2. Axesso – Data Service

Axesso Data Service is a European provider of automated web scraping and data extraction services, specializing in delivering structured product data from major e-commerce platforms. For Amazon, the company sells datasets covering products, reviews, sellers, deals, search results, and price history. Additionally, it equips you with a fully managed API infrastructure for web scraping.

➡️ Ideal for: Dynamic pricing analysis.

Coverage:

• 250M+ Amazon product entries, 500M+ Amazon reviews data entries, 250K+ Amazon seller data entries.
• Amazon product, deals, reviews, search, seller, price history datasets, with 25+ fields included in each dataset.

Infrastructure:

• Fully managed dataset and API infrastructure.
• Supports 20M+ API calls per day by 1,000+ active users
• 99.95% API uptime.

Data freshness:

• Historic data, with weekly updates.
• Real-time data via an Amazon web scraping API.

Technical requirements:

• Ability to work with structured data formats like CSV, JSON, and Excel.
• API integration skills required for programmatic access and file downloads.
• Cloud analytics knowledge for querying data via Google Analytics Hub.

Compliance: Undisclosed.

Pricing:

• Free trial available for all APIs, including up to 100 requests per month.
• Amazon deals dataset: From €50 per month.
• Amazon products dataset: €0.50 per 1K records.
• Amazon reviews dataset: €0.20 per 1K records.
• Amazon search dataset: €0.50 per 1K records.
• Amazon seller dataset: €1.50 per 1K records.
• Amazon API: Starts at €30 per month.

3. Datarade

Datarade is a global B2B data marketplace and platform that connects companies seeking data with providers offering datasets and APIs. It simplifies the process of finding, comparing, and sourcing specific information across hundreds of categories, including over 104 providers for Amazon data. These aspects make it one of the most popular dataset websites.

➡️ Ideal for: Versatile Amazon data analysis use cases that vary depending on the selected provider.

Coverage:

• Depends on the chosen data provider.
• Available data may include Amazon seller data, product data, customer reviews, pricing, and more.

Infrastructure:

• Depends on the Amazon data provider and their underlying platform capabilities.

Data freshness:

• Changes based on the selected data provider.
• Options may include historical (static) datasets as well as regularly updated data with hourly, daily, weekly, or near–real-time refresh rates.
• Some providers also offer fresh (dynamic) data via Amazon web scraping solutions.

Technical requirements:

• Vary significantly depending on the data provider.
• May include familiarity with APIs, data formats, or cloud storage.

Compliance:

• Depends on the chosen provider and may include adherence to regulations such as GDPR and CCPA.

Pricing:

• Changes according to the preferred data provider and their pricing and billing model.

4. Jungle Scout

Jungle Scout is an all-in-one cloud platform built for Amazon sellers. It provides data-driven tools for product research, listing optimization, competitor analysis, and business management, helping businesses find, launch, and scale profitable products on Amazon. It is perfect for gaining insights into sales trends, demand, and profitability.

➡️ Ideal for: Competitive intelligence, brand management, and campaign and advertising optimization.

Coverage:

• Amazon product data covering 600M+ tracked products.
• Includes both 1P (first-party) and 3P (third-party) Amazon data.

Infrastructure:

• Cloud-based platform serving 1M+ Amazon sellers and brands worldwide.
• Built to ingest and process millions of Amazon data points at scale.

Data freshness:

• Continuously updated Amazon intelligence.
• Access to historical Amazon data, including 10+ years of third-party data.

Technical requirements:

• Low technical barrier, as most insights are accessed through web-based dashboards.

Compliance: Undisclosed.

Pricing:

• Jungle Scout Catalyst: Designed for new and growing sellers.
  • Starts at $49/month.
  • Includes a 7-day risk-free trial with a money-back guarantee.
• Jungle Scout Cobalt: Built for emerging, established, and enterprise brands.
  • Custom pricing based on brand size, data requirements, and selected features.

5. Real Data API

Real Data API is a web scraping and data extraction service. It provides ready-to-use datasets, as well as APIs to collect publicly available data from websites like e-commerce platforms. Its Amazon offerings include product details, pricing, stock, seller information, and customer reviews, supporting both historical and up-to-date data delivery.

➡️ Ideal for: Pricing optimization.

Coverage:

• Product information: Product name, brand, category, ASIN, description.
• Pricing and offers: Original price (if discounted), discount percentage, stock availability, seller information, Buy Box winner.
• Customer reviews and ratings: Overall rating, total number of reviews, individual review ratings, review sentiment analysis, review highlights.
• Sales and performance metrics: BSR (Best Seller Rank), estimated monthly sales, number of questions and answers, conversion rate, sales trends.
• Additional insights: Product images and videos, shipping & delivery information, competitor price comparison, prime eligibility, bundled offers.
• Product metadata and attributes: Product dimensions and weight, material and ingredients, color and style options, warranty and return policy, manufacturing date, and expiry date.

Infrastructure:

• Scalable solutions capable of handling large data volumes.
• Offers RESTful APIs for simplified data access.
• Cloud storage integrations with AWS S3, Google Cloud, and Azure.

Data freshness:

• Historic data with scheduled automated updates and instant delivery.
• Fresh data via an Amazon data scraping solution.

Technical requirements:

• Knowledge of data formats (CSV, JSON, Excel) and cloud access.
• Understanding of RESTful APIs.

Compliance:

• Ensured adherence to Amazon’s terms of service.

Pricing:

• Sample dataset provided with product details, pricing, ratings, and seller info.
• Undisclosed pricing (you must contact their sales team).

6. Actowiz Solutions

Actowiz Solutions is a global provider of enterprise web crawling and data extraction services, specializing in transforming large volumes of unstructured website and app data into clean, structured, and actionable datasets. For Amazon, it supports structured data and APIs covering product listings, pricing, sellers, customer reviews, bestsellers, and inventory.

➡️ Ideal for: Sentiment analysis.

Coverage:

• Amazon product listings dataset: Product name, category, brand, UPC/EAN, titles, bullet points, descriptions, attributes, images, product variations (color, size, pack sizes).
• Amazon pricing dataset: Current price, discounted price, MRP, historical price trends, Buy Box price, shipping cost
• Amazon seller dataset: Seller names, ratings, performance metrics, Buy Box ownership history, fulfillment type (FBA, FBM, Prime eligible).
• Amazon customer reviews dataset: Ratings, review text, verified purchase, reviewer profile (anonymized), helpful votes, sentiment classification.
• Amazon bestsellers and trends dataset: Top-selling products by category, Amazon bestseller rank history, seasonal trends (Black Friday, Prime Day, festive sales).
• Amazon Inventory and stock dataset: Availability status (in stock, out of stock, preorder), delivery timeframes, regional availability differences.

Infrastructure:

• Webhook/queue delivery and bulk export options.
• Python and Node.js SDKs, a CLI scraper, and a Postman Collection for quick integration.

Data freshness:

• Amazon dataset library with daily, weekly, or monthly updates
• Real-time data available via an Amazon scraper.

Technical requirements:

• Ability to work with CSV, JSON, or Parquet exports.
• Understanding of RESTful APIs and integration with tools like Zapier, Make, or Postman.
• Proficiency in Python or Node.js for using the official SDKs.

Compliance: Undisclosed.

Pricing:

• Provides sample datasets with product titles, price, stock, and reviews for testing.
• Pricing details are not explicitly listed (you must contact them to request a demo or discuss opportunities).

7. Kaggle

Kaggle operates as a community platform for data scientists and machine learning practitioners to learn, compete, and collaborate. It hosts data science competitions, provides access to public datasets, offers interactive notebooks, and fosters discussions. For Amazon, it features over 3,000 free datasets and nearly 13,600 notebooks analyzing this data. As an example, explore a public Notebook for analyzing Amazon best-selling products built over a free Bright Data dataset.

➡️ Ideal for: Academic research, AI/ML experimentation, and proof-of-concept projects.

Coverage:

• Multiple Amazon-related datasets published by the community, including product data, customer reviews and ratings, sales and delivery data, and more.

Infrastructure:

• Data is hosted and distributed via the Kaggle platform.
• Access is provided through direct dataset downloads or via Kaggle Notebooks for in-browser analysis and experimentation.

Data freshness:

• Static datasets uploaded at a specific point in time.

Technical requirements:

• Ability to work with common data science tools and formats, especially Jupyter Notebook.

Compliance: Undisclosed.

Pricing: Free.

Conclusion

In this blog post, you first understood what Amazon data is, why it is valuable, the challenges of retrieving it, and how to simplify the process using a reliable Amazon data provider.

Those services give you access to Amazon product data, seller data, reviews, and more—either through static datasets or web scraping solutions to collect data yourself. Among the top providers, Bright Data stands out as the best choice.

Its infrastructure is the most robust, and its Amazon data offerings are the most comprehensive, including Amazon datasets with over 641.2M records and several specialized scrapers: Amazon Scraper, Amazon Price Scraper, Amazon Seller Scraper, and Amazon ASIN Scraper.

Sign up for a free Bright Data account today to explore our Amazon data solutions!

FAQ

How to get Amazon data?

To get Amazon data, you can use basically two approaches:

• Utilizing an Amazon web scraper: Whether you build it yourself or use a ready-made Amazon scraping service or API, this method allows you to collect up-to-date information directly from Amazon product pages.
• Relying on pre-collected Amazon datasets: This includes historical data that providers have gathered, bought, or scraped in the past, ready for immediate use.

What is an Amazon dataset?

An Amazon dataset is a structured collection of Amazon-related data, typically in CSV, JSON, Parquet, or Excel formats. It generally includes product details, pricing, reviews, seller information, sales metrics, and other relevant information.

How to scrape Amazon?

To scrape Amazon, you can either connect to an online Amazon Scraper API or build a custom web scraper. Under the hood, the process for web scraping Amazon usually follows this roadmap:

1. The scraper connects to the target Amazon page.
2. The page is rendered in a browser automation tool, or its HTML is parsed using an HTML parser.
3. Amazon data scraping logic is applied to retrieve the information of interest.
4. The scraped data is returned in the desired format.

Keep in mind that real-world scraping is complex due to IP blocks, CAPTCHAs, browser fingerprinting, and other anti-scraping techniques.

How to scrape Amazon product data?

To scrape Amazon product data, follow the general scraping procedure outlined earlier, but target specific product pages. The main challenge is that each product page may have a different structure, so your scraper must handle multiple edge cases to be robust. For detailed guidance, refer to our guide on scraping Amazon product data using Python.