Access to accurate Google search results in structured form is essential for research, SEO, and product development. A SERP API removes the friction of managing proxies, CAPTCHAs, or changing result formats by delivering clean, ready-to-use data at scale.
Among providers, HasData offers one of the fastest and most reliable Google SERP APIs, designed to handle real-time workloads while keeping output consistent and easy to integrate. This article compares several leading options across speed, reliability, and scalability to help you see where each stands.
HasData - Fast and Reliable at Scale
HasData's Google SERP API is built for real-time use and large-scale workloads. Independent benchmarks showed a median response of 2.3 seconds (95th percentile 3.0) with zero failures, backed by a 99.99% SLA. This makes it one of the fastest and most consistent options available.
The API delivers JSON output that covers more than 15 result types. You get organic results, ads, maps, featured snippets, "People Also Ask", shopping results, and Google's AI-generated answers. The JSON is clean and LLM-friendly, so you avoid the common problems of nested fields or broken encodings. Optional screenshots are also available for verification.
Integration is straightforward. Authentication uses a single API key, and over 20 parameters let you customize results by country, city, language, or device. The service automatically handles proxy rotation, JavaScript rendering, and CAPTCHA solving. Every request returns data, since failed attempts are retried until successful.
For developers, HasData provides official SDKs for Python and Node.js, along with interactive documentation. Non-technical users can connect it to Zapier or Make to add SERP data into workflows without writing extra code.
HasData scales smoothly. Tests with 100,000+ requests showed consistent performance without hitting limits. Pricing starts with 1,000 free calls. After that, you pay only for successful requests. At enterprise levels, cost drops to around $0.00083 per request.
Why HasData Stands Out
- Fast: Median 2.3 seconds with no failures
- Reliable: 99.99% uptime SLA and automatic retries
- Scalable: Handles millions of requests with stable speed
- Flexible: 20+ parameters, SDKs, and no-code integrations
HasData is well suited for real-time SEO dashboards, rank tracking, or AI applications that depend on clean and complete SERP feeds. It ensures you get accurate data at scale, without extra infrastructure or maintenance.
Decodo
Decodo, previously known as Smartproxy, positions itself as a SERP API provider that relies on a large proxy pool. It claims a high success rate by rotating more than 125 million IPs and using headless browsers to avoid blocks.
The API delivers standard JSON or CSV outputs. Supported elements include organic links, ads, related searches, and knowledge panels. Advanced features are more limited, so results cover the basics but not every SERP variation or AI-driven answer. This makes it less suitable for advanced use cases.
Integration is functional but not frictionless. Developers use API keys, a web Playground, and code snippets. While documentation is clear, responses often need extra parsing. The JSON structure is not streamlined for LLM pipelines and might require cleanup before it becomes useful.
Performance is a concern. Average response times range from 4 to 5 seconds per request. This speed is manageable for batch jobs, but it does not fit real-time workflows or dashboards. Latency stays consistent, but the trade-off is slower delivery compared to faster APIs.
Pricing starts at $29 for about 23,000 requests, roughly $1.25 per thousand. Larger volumes reduce the cost further. While affordable, the entry plans show the service is aimed at bulk data collection rather than precision or low-latency needs.
Limitations worth noting
- Slower performance not fit for real-time use
- Basic SERP coverage only
- JSON requires extra cleanup for AI pipelines
- Pricing geared toward batch scraping rather than agile projects
Decodo is a dependable tool for those who value raw scale and simple data extraction. For projects that demand fast responses, advanced features, or optimized integration with modern AI systems, its limitations are more apparent.
NetNut
NetNut is a proxy-based service that offers a SERP scraping API. Its infrastructure focuses on raw capacity and speed, delivering average response times around 2.1 seconds. Success rates in tests were high, thanks to automatic CAPTCHA handling and large proxy coverage.
The API supports queries from over 150 locations worldwide. Output is available in JSON or HTML. The focus is on standard search results, returning elements like titles, snippets, and URLs. More advanced SERP features are not consistently included.
The service is targeted at enterprise clients. The minimum subscription starts at $1,200 per month for 1 million requests, about $1.20 per thousand. There is no pay-as-you-go or smaller entry plan, which makes it inaccessible for startups or smaller projects.
Feature coverage is narrower than some other providers. There are no dedicated endpoints for image search, news, or "People Also Ask." The scope is limited to basic Google search pages, which restricts its usefulness for broader SEO analysis or AI-driven pipelines.
Key limitations
- High entry cost with no low-volume options
- Narrower feature set limited to basic SERPs
- Focused on enterprises, not smaller teams
- Limited flexibility outside standard web search
NetNut is best suited for companies with significant budgets and predictable, large-scale needs. For those requiring advanced features, flexible pricing, or broader SERP coverage, its value is harder to justify.
Zenserp
Zenserp offers APIs for Google, Bing, Yahoo, and other search engines. Setup is simple: you get an API key and start making REST calls. A Playground helps build queries, and code snippets are generated automatically. A free plan with about 50 searches is available for testing.
The main issue is completeness. Independent reviews show JSON responses sometimes miss organic results or parse them incorrectly. Certain fields may be empty. This reduces reliability for rank tracking or detailed SERP research. Inconsistent output makes the data less dependable for professional use.
Security practices also raise concerns. In some cases, API responses returned the user's own API key inside the payload. If logs or outputs are shared, this could expose the key and allow unauthorized use of the account. That risk makes it unsuitable for sensitive projects.
Performance is moderate. Typical responses take around 3.9 seconds, with spikes beyond 11 seconds during heavier loads. While the service did not show frequent errors, the latency is a limitation for real-time workflows. Batch use is manageable, but not optimal for applications needing fast updates.
Pricing is mid-range. It is not the cheapest option, and the features are basic compared to more advanced APIs. The value is tied to multi-engine support rather than depth of Google-specific coverage.
Limitations to consider
- Incomplete or inaccurate JSON outputs
- Security risk with exposed API keys
- Slower response under load
- Limited advanced SERP features
Zenserp is serviceable for experiments or small projects where occasional data is enough. For production-grade workloads or applications requiring consistent accuracy and speed, its shortcomings become more visible.
ScrapingBee
ScrapingBee is positioned as a broad web scraping API. It supports headless browsers, proxy rotation, and AI-based extraction. One of its endpoints covers Google Search. Setup is simple: you send a GET request and receive JSON results. Pricing is straightforward, with free trial credits and volume-based plans.
The Google-specific output is limited. Responses usually contain only titles, snippets, and URLs. Rich elements like featured snippets, knowledge panels, and "People Also Ask" entries are often missing. Some tests also showed raw HTML fragments mixed in, requiring additional post-processing before the data becomes usable.
Performance is the biggest drawback. Median response times were recorded at about 20.9 seconds per request, with worst cases exceeding 40 seconds. This latency makes the service impractical for real-time monitoring or large-scale SERP data extraction where fast and consistent delivery is required.
ScrapingBee suits general scraping projects where Google data is an occasional need. As a specialized SERP solution, it lacks speed, completeness, and efficiency. Its role is better as a secondary option within a broader scraping toolkit rather than the foundation for mission-critical search data pipelines.
Limitations to consider
- Slow response times, often 20+ seconds
- Minimal SERP coverage with missing features
- Inconsistent output with raw HTML fragments
- Best suited for light or occasional use
Choosing the Best SERP API
When deciding which Google SERP API to use, consider your project's priorities: Do you need results as fast as possible? Is absolute data completeness and accuracy critical? How many requests will you run per month? For most startups and SEO professionals, a balance of speed, reliability, and scalability is key. This is where HasData shines. It provides lightning-fast responses, almost 100% uptime, and full SERP coverage, all on a flexible pay-as-you-grow model. It handles heavy loads without flinching, and its output is immediately usable for analytics or feeding into AI models (no cleanup required).
Other providers like Decodo or NetNut might be viable if you have very specific needs - for example, if you're already invested in a proxy network or want the absolute lowest cost for bulk data. Zenserp and ScrapingBee can work for hobby projects or basic use, but they introduce compromises in data depth or speed.
In the end, the best Google SERP API for you is the one that reliably delivers the data you need without headaches. For most, that means HasData. It objectively leads in the metrics that matter - speed, reliability, and scale - making it a smart choice to power your SEO tools, rank trackers, or any application that depends on real-time Google search results. With HasData SERP API, you can focus on using the data, not wrestling with how to get it.
