Today we cover another interesting topic: how much does it cost to create a search engine? We, at Azati, develop and deliver commercial search engines. Those engines are entirely different from the regular ones like Google, Yahoo, Bing, Baidu, and others. Many facts about commercial search engines are unobvious and quite hard to understand without a degree in computer science.
In this article, we give precise information on the types of commercial search engines and how much it costs to build one.
We describe several main aspects that affect the end price:
– Search engine types and how they differ
– The development cost is not the thing you should care about
– The Average Costs of Search Engine Development
Interested? Read on to discover the details!
How search engines differ one from another
You won’t be surprised to discover that the web search engines today are similar to the ones from the 1990th. In fact, there is a spider-bot, which crawls the web pages and evaluates the content according to several factors like keywords, keyword density, meta tags, images, page load time and so on. There are dozens of different factors that indeed define the page quality. By the way, it takes the Google web-crawler (or Googlebot) 20 seconds to processes the entire page.
How modern web search engines work (simplified)
The commercial search engines are different from the public ones (Google, Yahoo, Bing, and others). Yeah, their crawlers somehow rank the content, but the entire process is a bit more complicated. The commercial search engines deal with vast and complex data processing. Their search algorithms are still looking for the patterns, which can describe the data unit, but they do it differently.
As stated before, we have developed and optimized several search engines, and we could explain how the data is processed. Let’s describe “the traditional search approach” first. The best way to explain it is to look at the top Google search queries for “How to build the search engine for a website”.
Suppose, we have a typical website with the blog containing three hundred HTML pages. HTML is a kind of understandable text format that can quickly be analyzed with any text processor. We refer to any file as a document, for the sake of simplicity.
To find the data in the document that is related to the user query we should:
– Determine the pattern
– Download the page from the database
– Analyze the page (in search of the pattern)
– Build Search Engine Result Page (also known as SERP)
There are two bottlenecks here, and both are related to the page size:
– It might take some time to download the page (document)
– It usually takes much time to find the pattern, if you are using the standard search approaches
Typically, it requires 2 ms to process a document (HTML page) of a WordPress website (written in PHP). Now imagine, that we have about 200 pages. They are processed within 400 ms or half a second. It seems fast enough.
Now imagine that we deal with an e-book library, where millions (!) of books with hundreds of pages are stored. Surprisingly, it takes little time to process it as we do not need to download a single page from the database – we download the whole e-book at once.
Now that you know this, here’s another fact: there are many documents that a search engine cannot quickly process – images, videos, encrypted formats, etc.
You might have thought: “Why can’t Google show us everything we want? Can it find relevant information?” Yes, it can, actually. Every year, the SERP algorithm becomes more accurate. Although the search quality improves, there are still many files that cannot be processed even today. Therefore, both public and commercial search engines require closer examination of the custom search algorithms they use to find relevant data.
By the way, we have an impressive case study – we’ve improved the search engine for the talent acquisition system by tuning their search algorithm.
The development price is not the only thing we should care about
From our point of view, the development cost is probably not the first thing customers should care about when calculating the final costs. There is another aspect that should be taken into consideration – maintenance.
If we look at the big brother – Google – we see that there are many servers (hundreds of thousands, probably) processing data in real time.
Why do they do so? The World Wide Web is a fast-changing environment. There are both static and dynamic pages, and all those pages should be recrawled multiple times to track the data changes (if there are any). In this way, Google processes the same data over and over again to make SERP fit the user query. It is the best and the most effective way to monitor changes, mainly if there are sextillions of pages available.
Internet grows incredibly fast!
Large search engine companies use complex algorithms to look for “footprints” in the document. For example, we do not need to collect all the data about the book, when we can spot the key thesis in its summary. This way, we recognize the above-mentioned footprint that contains the necessary data: author, titles, summary, brief description, keywords, publication data, etc. – and add this footprint to a separate database.
When the user instructs Google to find something, the search engine looks for the pattern in the footprint database first. If it doesn’t find a matching answer, it performs a deep search. If this is the case, the pages are generated at a slower pace. You can check it yourself – make a complex query and compare the SERP generation time for different pages (usually, the first page pops up far quicker than the thirtieth).
If there are hundreds of thousands of servers needed to perform a search – so how much will it cost? Well, nobody knows the exact estimates. The only thing we know for sure – a lot. Google is now setting up new powerful servers to process data in a quicker, more accurate and secure way. Thus, even the most complicated and in-depth queries will be performed in an instant and generate precise results.
We discovered how Google works. Now let’s see how commercial search engines process data.
We can use two approaches:
– Develop a lightning-fast search engine powered by solid mathematical knowledge, modern databases, SSD drive and coded with the fast programming language like C++
– Develop a “footprint” database
These two approaches affect search engine development costs. Customers usually prefer the first one as it is more accurate but slightly more expensive.
The Average Costs of Search Engine Development
If you want to build a search engine from scratch in Python or PHP, for example, you can do it for free after completing some courses at Udemy or EDX. It requires some programming skills though. In the case of paid courses, it will cost you up to $100.
If you want to create a search engine like Google (with a decent search quality), we would say it might cost you about $100M (for the prototype) – including costs for servers, bandwidth, colocation, electricity and so on. Maintenance costs for the existing cluster may go up to $25M per year.
If you want to create a commercial search engine for your business – be it the insurance, bio-informatics, healthcare, e-commerce, or other company – the development costs may range from $10,000 to $60,000, with a low maintenance fee.
Want to develop your own search engine? Call +1 (973) 597-1000 or fill the form below to get the free consultation or estimation!