Many enterprise developers are presently looking into advanced search engines that have simple criteria and a mechanism for full-text search. Scalability and high efficiency is also something they demand of these search engines and, for the longest time, this wasn’t available. In fact, there wasn’t even a demand for it until web developers began to process more and more data over time.
At first, developers had no real need to pay close attention to the efficiency of their applications, but now that many businesses have brought their solutions to the web, there are huge amounts of data that need to be processed. This fact has forced web developers to take a new approach to search problems in order to tackle the advanced problems that many businesses are facing today.
Most of the problems that developers face during the development of websites today can be fixed by using one of a handful of main databases, such as Oracle, MySQL, or PostgreSQL. Cache systems can also be implemented, as well as MongoDB and other non-relational databases.
Sometimes, however, a basic main database is not enough for a company which wants more out of its search engine. When a business wants to use a data search engine that is both very efficient and highly scalable, what should it use? The answer is Elasticsearch. Based upon the Apache Lucene engine, Elasticsearch is a real-time, distributed search engine that is completely open source. Elasticsearch provides a huge array of benefits and services for businesses looking to get the most out of their search engines. These features include:
- Advanced Search Queries
- Shorter Development Times
- Lots of Built-In Helpful Solutions
- Data Result Scoring That is Manageable
- Simple Full-Text Search.
Another great aspect of Elasticsearch is that communication with it is based on Rest API. Programming languages such as PHP and Java also come with libraries that are able to handle Elasticsearch, which makes life a whole lot easier for web developers.
Meeting a Challenge
Let’s say that a business wanted a search engine with advanced data and full data scoring functionality, as well as full-text search. Now let’s say that a user wanted to search for all rows that contained words such as “php,” “test,” or “job.” With a MySQL engine version 5.6.28 that has a table of 169123 records, an average length of searchable field that was 2550 characters long, and a maximum length of searchable field that was 686141 characters long, the duration time of the search would be about 9.1 seconds, which is far too long for almost any business. With a MySQL engine that also included a full-text indexed field for the query, the search would only take about 0.4 seconds.
For most businesses, this search time is most certainly acceptable, but the problem is the search would have to be full-text. This engine would not work if a business was requiring more advanced conditions for the search and data sorting that was based upon those conditions. In cases like this, the only feasible option is Elasticsearch.
When an Elasticsearch is performed with the same exact inputs as above, the result is nearly the same as a MySQL search with a full-text indexed field. So why is Elasticsearch still considered superior in this situation? The answer is that Elasticsearch can also provide more complicated options for a user.
One great example of an option that Elasticsearch provides that is not available with more basic search engines as highlights. The options to include highlights allows a user to also view the context of a word that has been searched, which provides a huge advantage for many businesses. This feature is so easy to implement for developers that their customers are basically getting it for free. Trying to implement this feature on a more basic relational database would require a far greater workload and might not be worth the effort. With the addition of nodes to the Elasticsearch system, the engine is also highly scalable while remaining very efficient and stable.
To put it simply, Elasticsearch provides services and features that are far more compatible with the demands of today than other relational databases. It provides a solution that is matched perfectly to advanced search within very complex data structures, and this is twice as true if a client wants to obtain results which are ordered very precisely within an application.
If you are a business owner who is looking for a solution to the search engine needs that you require, and you also want to be able to scale your engine up as needed, Elasticsearch is without a doubt the service you should consider using. When it comes to results and value, nothing delivers more consistently and effectively than Elasticsearch.
WOULD YOU LIKE TO LEARN MORE?
If you’re interested in more, be sure to send us an email at firstname.lastname@example.org! And get in touch with Weblink if you have tough Elasticsearch problems you need help with!
Elasticsearch Consulting and Implementation Services
Weblink Technologies a leader in Elasticsearch products, to provide a solution based solely on Elastic-search. As an Elastic partner and reseller, we have worked with hundreds of customers across the globe to provide expert consulting and implementation for Elasticsearch, Logstash, Kibana (ELK), and Beats. Whether you are using Elasticsearch for a web-facing application, your corporate intranet, or a search-powered big data analytics platform, our Elasticsearch experts bring end-to-end services that support your search and analytics infrastructure, enabling you to maximize ROI.
- Elasticsearch consulting and strategy planning
- Search application assessment
- Elasticsearch, Logstash, Kibana, and Beats (Elastic Stack) implementation
- Search relevancy review and improvement
- Full support and managed services: (OnSite and Remote)
Contact us at email@example.com to learn more about how we can help you leverage Elastic products for high-performing, easy-to-maintain, and scalable search and analytics solutions.
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