We make apps that need results from search engines. It’s hard to get this information directly. You have to deal with proxies, solve CAPTCHAs, and read HTML that changes all the time. This work is done by a Search Engine Results Page (SERP) API. You send a request and get back structured JSON. The issue is that not all APIs are the same. A lot of them are slow, give back bad data, or break when there is a lot of traffic. We tried out five popular options to see which one was the best for serious development work. We looked at speed, the quality of the data, and the overall experience of the developers. 

The Core Requirement for Production Systems 

Speed and data quality are two very important things for any application that needs real-time search information. A bad user experience happens when responses are slow. Extra code is needed to clean up badly formatted data, which wastes development time and makes things more likely to go wrong.  

That’s why we chose HasData. 

  • You need low latency if you want speed. HasData has always gotten results with a latency of less than 3 seconds in the 95th percentile (P95). This means that even the slowest requests are fast enough to be used in real time.
  • You need clean data if you want automation. HasData gives you a flat, predictable JSON structure. It doesn’t have base64-encoded images or deeply nested objects that need complicated parsing. The output is ready to be used right away

Other services have to make choices. They might be slower, but they might be cheaper. They may have a lot of features, but they give back a complicated data structure. These compromises are not okay for work that is ready for production. 

Our Testing Method 

To make a fair comparison, we established a clear testing environment. We sent 1,000 requests to each API within the same one-hour window. Every request used the same query (“coffee shops near me”) and was geo-located to New York City. 

We measured three key metrics: 

  1. P50 Latency: The median response time. This shows the typical speed of the API.
  2. P95 Latency: The 95th percentile response time. This shows performance under worst-case conditions and is vital for service reliability.
  3. Data Quality: A manual review of the returned JSON for structure, completeness, and ease of parsing.

We focused on these metrics because they directly impact development and final product performance. 

HasData 

The SERP API from HasData is made for developers who need quick, dependable search data without having to do any extra work. The main goal of the service is to send clean JSON from a simple API endpoint. The documentation is clear and useful, and authentication uses a standard API key. It has an interactive playground that makes code snippets, which makes it easier to set up at first. 

HasData was the best in our tests. The average response time was 1.9 seconds. Its P95 latency was only 2.7 seconds, which is more important. This low variance means that the service is stable and can be relied on, even when it’s busy. All of our requests worked, so the success rate was 100%. 

The experience for developers is great. The JSON output is clear and flat. It takes out things that aren’t needed, like encoded images, and names fields clearly. This gets the data ready for machine learning models or for putting it directly into a database. We learned that we could use the output with very little cleaning. This is a big plus for teams that want to move quickly. For apps that need both speed and high-quality structured results, HasData is the clear choice. 

Decodo 

Decodo, which used to be called Smartproxy, has a SERP API as part of its larger set of scraping tools. The service has a nice user interface and good documentation. It is a useful tool that gives you a lot of different types of search results, such as organic listings, ads, and map packs. 

The performance was good enough. Decodo’s average response time was 5.4 seconds, and its P95 latency was 9.8 seconds. This speed is fine for batch processing jobs, but it’s not good for applications that need results right away. The service was dependable and had a high success rate, but the latency makes it less useful for things that need to happen right away. 

Decodo gives back a lot of information. But the JSON structure can have more levels than the HasData structure. This means that developers have to write more code to get the exact information they need. If developers are willing to spend extra time parsing data and the project doesn’t have strict speed requirements, this is a good choice. 

NetNut 

NetNut is best known for its proxy infrastructure, and its SERP Scraper API is aimed at big businesses. The tool is made to handle a lot of requests at once. It’s a great choice for businesses that need to scrape a lot of search results. 

NetNut’s performance shows that it is focused on big jobs. The average latency was 4.1 seconds, and the P95 was 8.2 seconds. This is good for a proxy-based system, but it doesn’t work well for real-time use cases. Cost is the biggest obstacle to entry. The service needs a lot of time each month, so smaller teams or individual developers can’t use it. 

The developer experience is designed for business workflows. It has a powerful API, but it’s harder to get started with than other services. The output is usually well-organized. NetNut is a good choice for big businesses that are already using its proxy network or for businesses that need to scrape data and can afford the high cost. 

Value SERP API 

Value SERP is a simple and cheap way to get Google search results. It has a simple API that is easy to use, which makes it great for small tasks or hobby projects. The pay-as-you-go pricing model lets you pay only for what you use. 

This ease of use comes at the expense of performance. Value SERP was one of the slower providers in our tests. The median response time was 8.9 seconds, and the P95 latency was over 15 seconds. Because of this level of performance, it is not good for any serious use. We also had several requests that didn’t go through during our test. 

The output in JSON is simple. It gives you organic results, but it doesn’t always have more useful data types like knowledge panels or featured snippets. The structure is easy to understand, but not having all the information is a big problem. Value SERP might be useful for tasks that aren’t very important and don’t need to be done quickly or with all the data. 

Deep SERP API 

Another tool that focuses on giving you raw search result data is Scrapeless’s Deep SERP API. It lets you change search queries in several ways, such as by location and device type. The goal of the service is to get detailed information from the SERP. 

The performance and data structure of Deep SERP were the biggest problems we found. The median latency was more than 10 seconds, which made it the slowest API we tested. Most business cases can’t use this speed. 

There were also problems with the JSON output. The data was very deep and had field names that didn’t match up. We had to write a complicated parser to flatten the structure and make the data normal before we could use it. This makes development much harder and makes the system more fragile, so it could break if the API changes its format. The work needed to make the data useful is more than the service’s benefits. 

Final Recommendation 

Choosing the right SERP API depends on your project’s needs. 

  • For simple, non-critical tasks, Value SERP might be enough.
  • For high-volume batch jobs, Decodo is a reasonable choice.
  • For enterprise-scale scraping, NetNut is an option if the budget allows. 

However, for professional developers building performant, reliable applications, the choice is clear. HasData provides the best combination of speed, stability, and data quality. Its low-latency responses and clean, developer-friendly JSON output reduce development time and improve the end-user experience. It is the right tool for building production systems.