Benchmarked the Top 5 Web Walmart Scrapers
We benchmarked the top Walmart scraper APIs to understand how they perform under real scraping workloads. Our test included 200 Walmart URLs from both product and search pages, with two request batches per URL, totaling 2,000 requests across all providers.
Compare how well each provider handles large-scale Walmart data extraction workloads:
Best Walmart scraping tools overview
Walmart scraper APIs benchmark results
To evaluate Walmart scraping providers, we compared vendors across two primary dimensions: the number of extracted data fields and median response time.
The average number of fields reflects how much structured information a scraper can retrieve from a Walmart product page. Providers that extract more fields typically capture richer product metadata such as specifications, seller information, fulfillment options, and review statistics.
The median response time is the time it takes a provider to return results for a scraping request. Lower response times indicate faster infrastructure and more efficient anti-bot handling.
For more definitions, see methodology.
Cost comparison of top Walmart scraper APIs
Review of the best Walmart scraping APIs
Bright Data performed strongly in the benchmark, providing one of the highest average field counts while maintaining relatively low median response times. This indicates a strong balance between data completeness and scraping speed.
The platform relies on large proxy pools, automated anti-bot handling, and dynamic rendering to access structured product information that is often embedded in JavaScript or JSON payloads.
Because of this balance between speed and completeness, Bright Data tends to work well for large-scale product intelligence use cases. These include catalog monitoring, competitive price tracking, and marketplace analytics pipelines where both response speed and data completeness matter.
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Visit WebsiteOxylabs performs strongly on data completeness, returning around 620 extracted fields per request in the benchmark. Median response times are slightly slower than those of the fastest providers but remain competitive, placing the vendor near the high-coverage segment of the chart.
The API typically returns detailed product attributes, including product specifications, seller information, ratings, category taxonomy, and variant details. This level of detail can be particularly useful for teams building product databases or performing detailed competitor analysis.
Oxylabs is therefore often used in applications where catalog completeness is more important than extremely low latency, such as product enrichment pipelines, retail analytics platforms, or market intelligence tools.
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Visit WebsiteDecodo produced the most extracted fields in the benchmark, averaging over 650 per request. Response times remain relatively fast, around three seconds, indicating that the provider emphasizes data richness while still maintaining efficient scraping performance.
Decodo extracts data from multiple sources on Walmart pages, including DOM elements and embedded JSON structures. As a result, the responses contain very detailed product information that can support advanced analytics or large product catalog ingestion.
The benchmark results position Decodo as a strong option for organizations that prioritize deep product metadata and structured outputs, especially when building comprehensive datasets from Walmart’s marketplace.
Apply SCRAPE30 for 30% offZyte shows a different tradeoff in the benchmark results. It provides some of the fastest response times, typically around one to two seconds, but returns significantly fewer data fields compared with other vendors.
Zyte focuses on speed and lightweight extraction rather than returning extensive product metadata. In practice, the output generally includes core attributes such as product titles, prices, availability information, and ratings rather than the full set of product specifications.
Typical use cases include rapid price monitoring or real-time product tracking systems where responses must be retrieved quickly.
Apify appears in the benchmark as the lowest-cost solution but also shows the slowest response times and lower field coverage.
However, Apify operates under a different model compared with most scraper APIs. Instead of offering a single standardized scraping endpoint, it provides customizable scraping actors that developers can modify or extend.
It is often used by developers who want to run customizable scraping workflows or experiment with specialized data extraction pipelines rather than relying solely on pre-structured API responses.
Data fields extracted from Walmart via scraping APIs
Product pages
Check which data fields each provider supports:
Notes:
- ✅ indicates that the provider supports the data field. The provider does not support the indicated data field (❌). Let’s use an example to clarify ✅s and ❌s: For this product, Bright Data offers product specifications field including brand, or age range. Since Apify doesn’t offer this information, the above chart shows ❌ under Apify.
- “Top Reviews” are the most prominent reviews accessible.
- All benchmarked APIs provide the following data points:
- Product page: Title, URL, price, currency, image URL, review count, availability, breadcrumb, rating.
- Search page: Title, URL, brand, price, currency, image url, category name, product ID.
Search pages
Walmart scraper benchmark methodology
We included 200 URLs from both the Walmart product and the Walmart search pages for each domain. If a web scraper consistently returns successful results over 90% of the time for a specific page type (e.g., Walmart search pages), and the results’ correctness is validated via random sampling of 10 URLs, we list that provider as a scraping API for that page type.
For more details, see our web scraping API benchmark methodology.
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