The development and implementation of an internal search engine is a complex and difficult undertaking. It requires a vast amount of dataset and/or website indexing, advanced algorithm development, and multiple types of query processing development, as well as monitoring and analytics to determine the degree of match to the initial user query. Required internal skills sets needed to build an internal search engine include backend development, database management, search technologies, API (application programming interface) design, deployment, testing, and security.
This complexity is why more and more companies are looking to implement search APIs rather than an in-house search capabilities solution. Read on to learn what a search API is, how search APIs work, and the considerations to keep in mind when choosing a search API.
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A search API is a tool used to interface with a search engine, sending a user query to the search engine and refining the user query results to more relevant content. The search engine behind the API takes care of web search aspects such as web crawling, indexing, algorithm development, and processing data, allowing developers to use the API to connect their application to that engine and retrieve the relevant information without developing a search engine of their own. The search API also affords developers a greater degree of control over web search results refinement when those results are returned.
Search APIs enable communications between a developer's client applications and search engines, providing a standardized interface for querying and retrieving web search results without building the web search capabilities from scratch. There are several steps in this communication process.
Client applications send their search queries to the search API, providing their search criteria (e.g., keywords, filters) as well as results preferences such as sorting and format. This is accomplished by the API sending a request to a specific endpoint using HTTP (e.g., GET, POST). Each request sent from the client to the API server is considered a single API call.
Once the search API receives the search query from the client application, it parses the query to identify relevant keywords and filters. Some preprocessing may also take place at this time, including text normalization, spell checks, and stemming (e.g., reducing a word to its root) to improve search accuracy.
The search API then translates the client application's web search query into a format that the underlying search engine can understand. This process includes converting queries into a specific programming language or adjusting the format of the queries into a format supported by the search engine (e.g., SQL, MongoDB Query API, Lucene Query Syntax, JSON).
Once translated, the search API then sends the web search query to the search engine for execution. The query is then processed against the search engine's index, where relevant search results are retrieved and ranked based on content relevance, website popularity, posting date, etc.
After execution, the search results are returned to the search API in such formats as JSON or XML. The results are then aggregated by the search API and formatted against the requirements of the client application. The formatted results are often put through additional filtering or sorting before returning the results to the client.
The formatted, filtered, and sorted search results are then sent back to the client application that created the query by the search API. The API also manages any exceptions that may happen during this process, including system errors.
Search APIs provide developers with the opportunity to integrate search functionality into their applications with specific customizations they require. This includes configuring relevance criteria, additional filtering/sorting requirements, creation or modification of additional search indexes, and more.
The search API may enforce authentication to protect sensitive data using various authorization tools such as an API key (e.g., a unique identifier used to control access to an API), authentication token, or other credentials to authenticate and authorize their API requests.
Search APIs are used in virtually every industry, providing developers ways to utilize powerful search engines while customizing web search results and enhancing the search experience for their users. Better yet, even the most simple API(s) can include search functionality. Below are a few use cases to consider.
E-commerce: Search APIs help customers quickly find desired products on e-commerce platforms using features such as hierarchical search (e.g., product category, subcategory, SKU), sorting options (e.g., by price or product type), and such aides as auto-complete and suggested product feature search terms.
Hospitality and travel: Search APIs power travel review sites (e.g.,TripAdvisor), hotel reservation systems, and third-party travel aggregators, enabling users to search for everything from flights, rental cars, and hotel rooms, to local activities based on price, location, travel dates, and more.
Healthcare: Search APIs are used by healthcare providers to retrieve patient records, query medical texts, and filter clinical trial data every day. Maintaining electronic health records (EHRs) requires search APIs to fuel everything from doctors' patient record reviews while in the exam room to post-appointment charting. Additionally, this can be seen in laboratory test results cataloging as patient management software employs search APIs to interface with research databases, laboratory systems, insurance databases, and more.
Real estate: Search APIs are leveraged by real estate platforms, such as Realtor.com and Zillow, to help users find properties matching their desired criteria. These criteria can include property type, prices, property status (e.g., pending sale, price reduced), location, assumable mortgage available, etc.
Social media: Search APIs help users to find friends and relatives, special interest groups, photos, and hashtags of interest. Search filters, sorting, and auto-complete functionality also help users find relevant content as well as discover new types of content which they may enjoy.
There are quite a few search APIs available that have benefits over an in-house solution in terms of functionality, development time, and cost. However, each search API has relative strengths and weaknesses when compared to others, so it's important to carefully evaluate them against your own existing and anticipated requirements to find the right fit. Here are a few factors to consider when choosing your search API.
To have the best developer experience possible, seamless integration with all data sources is essential to avoid configuration issues. In addition to gathering the appropriate data, ensuring that data sources are always synchronized to have the latest possible information is of paramount importance.
A search API is, before anything else, a tool that should make software engineers more productive. Having a tool with a syntax that is familiar to developers makes the search experience and resulting adoption rate better. This ultimately will translate into a better search experience for users as well.
Most modern applications provide auto-completion and suggestions for the end-user as they type in search terms. However, the differentiation is speed. The search solution selected will need to be blazing fast to deliver user suggestions quickly from the back-end to the front-end application.
Returning relevant results is not necessarily the same as returning the first search engine results page (SERP). For example, sponsored content might be bumped to the top or results could be prioritized based on a specific attribute such as geographic location. For this reason, the search API selected will need custom scoring options to return the most relevant results for your organization and user base.
MongoDB Atlas Search is best-in-class when it comes to search APIs, offering everything to support developers while fueling relevant search for end users.
Atlas Search is powered by Lucene search for its full-text search and connects directly to your MongoDB collection in Atlas. No need to manage additional software or infrastructure. Enabled with the toggle of a button, with a single API call, searching through all of your collections will be fast and effective.
Atlas Search uses the MongoDB Query API that your software developers already use (or are familiar with) to query other MongoDB collections, enhancing both rapid adoption and usage.
Atlas Search provides an easy-to-integrate auto-complete tool that will instantly deliver suggestions to end-users with minimal configuration.
Atlas Search provides custom scoring, ensuring that results found by the search engine are the most relevant results to your users.
MongoDB Atlas Search provides you with all the necessary features to deliver the best possible experience to your users without compromising developer experience. Check out how to implement an Atlas Search solution in this quick start guide and take your search experience to the next level.
A search API (application programming interface) is a tool used to interface with a search engine. It is used to send requests to a search engine and refine the returned results. The idea behind a search API is to make it easier for software developers to interact with the engine itself.