10 Best SERP APIs & SerpApi Alternatives (Benchmark)

Finding a reliable SERP API is frustrating when every provider claims to be the “fastest” or “cheapest.” We benchmarked the leading SERP providers using 18,000 live requests across Google, Bing, and Yandex.

While our full analysis covers the extensive market, 5 providers consistently outperformed the rest in our speed and data richness tests. Here are the proven market leaders based on our data:

Key takeaways from our SERP API benchmark

Richest data: Bright Data 

Our scatter plot analysis shows that Bright Data is in a league of its own, returning over 220 data fields on average. This includes granular details like rich snippets, map coordinates, and ad extensions.

Most SERP APIs return basic fields like titles, URLs, and descriptions (~80 fields).

Speed champion: Zyte 

While the industry average response time hovers around 4-5 seconds, our data identified a clear outlier. Zyte consistently clocked in under 1.5 seconds.

If your project can tolerate standard latency (3-5s), providers like Oxylabs and Decodo offer a more cost-effective balance without sacrificing stability.

Best balance: Oxylabs and Decodo

Throughout our 3-month stress test, which included 18,000 requests, Oxylabs and Decodo demonstrated the highest consistency.

While some competitors had faster “best case” times, they suffered from occasional timeouts.

Want to see the full scatter plot and speed charts? Jump to detailed benchmark analysis.

10 best SERP APIs for scraping Google

Bright Data SERP API is the most powerful tool. In our tests, it returned 2x as many data fields (maps, coordinates, rich snippets) as the industry average. It is the go-to choice if you need deep, structured data rather than just simple titles and URLs.

Performance:

• Benchmark speed: 5.58s (Avg)
• Data richness: ~220 Fields (Market Leader)

Pros:

• Unmatched data depth: Captures granular details that others miss.
• Massive scale: Built-in proxy network handles millions of requests.
• Global coverage: Targets any country, city, or coordinate.

Cons:

• Learning curve: The dashboard is feature-rich and can be overwhelming for beginners.

Pricing:

• Starting price: $500/mo (PAYG available)
• Free trial: 7 Days (Business email required)

In our test, Oxylabs proved to be the most stable provider. While it doesn’t top the chart for raw speed (like Zyte) or data depth (like Bright Data), it delivered consistent results with near-zero failure rates.

It strikes the perfect balance for large-scale projects where reliability is more critical than millisecond speed.

Performance:

• Benchmark speed: ~4.12s (Stable)
• Data richness: ~100 Fields (Balanced)

Pros:

• Unified schema: Switch from Google to Bing scraping by changing just one parameter.
• Granular targeting: Scrape SERP data down to specific cities or coordinates.

Cons:

• Google-centric: While it covers others, its features are heavily optimized for Google.

Pricing:

• Pricing: $1.60 / 1k results (PAYG)
• Free trial: 2,000 Searches (No Credit Card)

Decodo is the best low-cost alternative. In our tests, it delivered performance very close to that of the premium providers (only ~0.4s slower than Oxylabs) at a fraction of the cost.

Decodo’s search engine endpoints include the Google Search Scraper and the Bing Search API. The SERP API supports Google in-depth and Bing (results, snippets, and rankings). All billing is a pay-on-success model.

Performance:

• Benchmark speed: ~4.5s (Consistent)
• Data richness: ~95 Fields (Standard)

Pros:

• Cost-effective: One of the cheapest entry points in the market ($29).
• Granularity: Supports city-level and coordinate-based targeting.

Cons:

• Google-Centric: Focuses heavily on Google; other engines are secondary.

Pricing:

• Starting price: $29/mo (Very Affordable)
• Free trial: 3,000 Requests

If your application requires real-time data (e.g., a user clicks a button and waits for a result), Zyte is the unrivaled winner. In our tests, it clocked a median response time of under 1.5 seconds.

Performance:

• Benchmark speed: < 1.5s (Market Champion)
• Data richness: Standard

Pros:

• Speed: The fastest option on the market, period.

Cons:

• Cost: Achieving this speed can be pricier than standard proxy-based solutions.
• Data depth: Returns standard SERP data; less granular than Bright Data.

Apify wins on usability and ecosystem. It’s not just an API; it’s a platform where you can rent ready-made “Actors” (scrapers) for Google Maps, Shopping, and more.

Performance:

• Benchmark speed: ~8.0s (Slower)
• Data richness: ~85 Fields (Good)

Pros:

• Low entry: You can start for as little as $5/month.
• Community: Excellent open-source libraries and developer support.

Cons:

• Latency: Not recommended for real-time, user-facing applications due to slower response times.

Our benchmark showed it to be slower than the market leaders, and the pricing model is strictly geared towards enterprise users with high budgets.

Performance:

• Benchmark speed: ~6.0s
• Data richness: Standard

Pros:

• ISP network: Accessing real ISP IPs reduces the chance of being flagged as a bot.

Cons:

• High entry barrier: Not suitable for small projects or individual developers.
• Speed: Slower response times compared to Zyte or Bright Data in our tests.

SerpApi is not the fastest or the cheapest, but it is the most versatile. While competitors struggle with niche engines like Google Scholar, YouTube, or Google Flights, SerpApi handles them effortlessly.

Pros:

• Widest coverage: Supports Google Images, News, Shopping, YouTube, Yahoo, Baidu, and more.
• Developer-friendly: Excellent documentation and libraries for Python, PHP, Ruby, and Go.

Cons:

• Using the basic features is easy, but to make the most of the advanced options and understand the different results for each search type takes some time.

Pricing:

• Starting price: $49/mo
• Free trial: 5,000,000 API credits

Nimbleway offers a full-stack scraping pipeline (proxy network, browserless rendering, and unblocker) that supports various targets, including search engine results pages. The SERP scraping API supports Google, Bing, and Yandex.

Pros:

• Dedicated and rotated IPs: Built-in dedicated residential proxies.
• Zip code-level targeting: Collect Google SERP data for a specific ZIP code.

Cons:

• The unit cost is higher than that of enterprise-oriented providers like Bright Data and Oxylabs. Heavy users may still find Bright Data or Oxylabs cheaper at scale.

DataForSEO SERP API provides a unified request schema for Google, Bing, YouTube, Yahoo, Baidu, Naver, and Seznam. The company specializes in delivering SERP data solutions to SEO professionals and marketers.

Pros:

• You can take a screenshot of a Google page.
• The provider offers an AI Summary endpoint feature that summarizes search engine result pages and provides an LLM-generated synopsis for a fee.

Cons:

• Live mode costs 3-4 * the base rate.
• Not PAYG credits

Serpstack is a search-scraping platform that provides access to the Google Search API to scrape Google search results data in real-time. The tool includes built-in proxy rotation and automatic CAPTCHA handling.

Pros:

• Offers a dedicated location API that lets you specify the exact location to which you intend to send a request.

Cons:

• If you intend to scrape hundreds of thousands of keywords, it would not be the most cost-effective option at scale.

ScraperAPI offers Google SERP API with built-in proxy servers. It extracts structured JSON data from Google search results. ScraperAPI doesn’t provide API endpoints for any search engines other than Google.

Pros:

• Ability to perform JavaScript rendering. It retrieves and returns JavaScript-heavy search result pages.
• Offers a free plan with a 7-day trial with 5,000 credits

Cons:

• If you need full-browser rendering for every request, the unit cost rises on heavy pages.

SERP scraper API benchmark results

Compare providers’ median response time and the average number of fields that they returned in our benchmark:

1,200 queries were used in this benchmark including a total of 200 query result pages from the two main search engines: google.com and bing.com. Queries were the top 100 Google searches in the United States.

Benchmarking the stability of SERP scraper solutions

We have run 18,000 queries in this benchmark so far. We run live requests every 15 min, caching off, with a 60s timeout, using 250+ queries across Google, Bing, and Yandex in the United States.

The chart shows the daily success rate and average response time (successful calls only):

Benchmark methodology

Multiple search engine results page (SERP) providers are evaluated against Google, Bing, and Yandex. Caching is disabled to ensure that each request retrieves current results.

A pool of over 250 unique queries is used to generate more than 900 URLs across the evaluated search engines. Each iteration randomly samples one or more queries from this pool.

Requests are executed at 15-minute intervals. Each request is subject to a 60-second timeout period.

During each iteration, a provider is paired with a supported search engine, and the corresponding live search URL is retrieved. The benchmark is conducted in single mode.

A response is considered successful if it meets the following criteria:

1. The response returns non-empty data, and
2. At least one engine-specific Cascading Style Sheets (CSS) selector is present in the returned HTML.

The following CSS selectors are used for validation:

• Google: .tF2Cxc, .yuRUbf, #search
• Bing: .b_algo, .b_caption, .b_title
• Yandex: .serp-item,.Organic, .content__left

The following metrics are recorded:

• The daily success rate is calculated as the number of successful requests divided by the total number of requests, multiplied by 100, both per engine and overall.
• The average response time is computed as the mean of successful request response times only.
• Timeout frequency and error distribution are also monitored throughout the evaluation process.

All errors encountered during the process are logged.

• The types of errors recorded include timeouts (fixed at 60 seconds), network or connection errors, parsing or decoding failures, and empty responses.

The following fields are recorded for each request:

• query, search_engine, url, success (1/0), response_time_s, mode=single, batch_id.

Building vs. buying: Open source options

If you have no budget or technical expertise, you can build your own scraper using open-source Python libraries such as Scrapy, Selenium, or Puppeteer. While this method is free, be prepared to handle CAPTCHA, proxy rotation, and IP bans manually.

Want to try building one?
Check out our step-by-step guide below on how to scrape Google results using Python.

FAQs about SERP scraper APIs

Reference Links

1.

Google Terms of Service – Privacy & Terms – Google

Industry Analyst

Gulbahar Karatas

Industry Analyst

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Gülbahar is an AIMultiple industry analyst focused on web data collection, applications of web data and application security.

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