Most applications and websites that operate vast and ever-increasing volumes of data cannot serve their customers well without implementing modern full-text search engines. Compared to traditional relational databases, full-text search engines allow for a much more relevant search and can quickly process larger quantities of structured, semi-structured, or unstructured texts using specific words or word combinations.
Today, there is no shortage of capable full-text search engine solutions in the market. Some of them are proprietary technologies, while others are open-source products. This post explains the full-text search concept and reviews the five best publicly available and proprietary solutions. Read on to find the one that meets your business needs in full.
What Is Full-Text Search?
Full-text search is a method of searching a single text or a collection of texts stored on a computer or in a full-text database. When processing an advanced linguistic text query, the search engine examines and analyzes all the words in every applicable document, seeking to match the criteria provided by the user.
As static sites become more of a trend and replace dynamic database-driven online resources, full-text search systems are turning into a much-needed, customizable tool for performing complex search operations.
The Benefits of Using a Full-Text Search Engine
The reasons for implementing a full-text search system are many and varied. Here are just a few advantages users can derive from such solutions:
- High query-processing/result-retrieving speed. The use of full-text search ensures a high speed of processing the user’s text query and obtaining accurate results for a vast number of documents across an extensive text database.
- Great accuracy and precision. Thanks to their highly sensitive recommendation algorithms and advanced relevancy ranking for organizing results, full-text search solutions provide a more accurate, personalized search experience for the user.
- Room for customization. The search logic and criteria of such solutions are flexible and can easily be configured to match the user’s more specific needs. The best solutions provide extensive support for keyword search, Google-style syntax search, Boolean operator search, etc.
- Support of static websites. Employing a full-text search solution ensures an improved experience for the user of static websites where the lack of dynamic features can make searching for a piece of content difficult, lengthy, and rather sloppy.
- Support of mobile applications. Modern mobile apps require quick and sophisticated search capabilities. Full-text search products implemented in mobile applications will allow to quickly and efficiently index and search all the documents, providing the user with accurate and relevant results.
Full-text search is not always the best possible technology for a website or app to rely on, and in some situations, a relational database with its excellent storing and structured data-manipulating capabilities will offer more measurable and successful results.
Top-4 Most Interesting Full-Text Search Solutions in 2021
To make sure you have all the essential information handy, here are the top-4 full-text search technological solutions worth exploring in 2021:
ClickHelp and Algolia are the two best-known and most trusted closed-source full-text search solutions, while Sphinx and Elasticsearch are all ready-to-use open-source alternatives. Here is more about each of them to help you make a more informed user decision.
Known for enabling incredibly fast indexing speed and yielding accurate search results, ClickHelp is the most trusted closed-source full-text search engine in the 2021 tech market. The browser-based solution offers impressive searching, filtering, and reporting capabilities, supports the context-sensitive help feature, and uses taxonomies for improved search results.
This C++ -based full-text search engine server offers seamless performance on macOS, Windows, and Linux. It has a high index and search speed, integrates smoothly with MySQL and PostgreSQL, and comes with a rich API for the most prevalent programming languages (PHP, Java, Ruby, Python, Perl, and C++).
Built on the Lucene library, Elasticsearch is the most popular open-source full-text search engine. The solution boasts both HTTP RESTful and Native Java APIs. Users love Elasticsearch for its excellent real-time index sharding and scaling capabilities.
Algolia is a well-known full-text search engine built on the SaaS model of business. This closed source solution is fast, dependable, and requires very little infrastructure. It can be used straight from the client or different services and offers an effortless integration at all times. Algolia offers customizable UI libraries for Angular, Vue, iOS, and Android.
Nothing can beat modern full-text search technologies in their high-speed search powers and the ability to sift through large volumes of data, delivering quick and accurate results. Most user-intensive apps and websites will surely benefit from the flexibility and customization potential of such products.
What full-text search solution do you trust the most? How well does it work for you? Which features are the most essential for a good full-text search engine? Feel free to speak up in the comments, and share the post with friends!