Elasticsearch and Solr Development and Implementation to Manage Vast Information Databases

 

“For a long time, search was all about the bag of words,” Stephen Emmott, an expert at Gartner, once said. Not anymore. The modern business environments operate huge databases to run, control and manage their data volumes efficiently. Understandably, such a vast array of information needs being constantly analyzed, structured and, consequently, rendered/found quickly and maximally conveniently for the users. How to achieve such a solution? We are going to walk you through our practical experience in the area to demonstrate the very search engine platforms along with their advantages and effectiveness for clients and their end-users.

ELASTICSEARCH as a perfect alternative to a slow standardized Bigdata search platform

We would like to start the article by sharing our experience while implementing Elasticsearch, as a leading search platform, to turn an ordinary and so widely used web searching process into a real pleasure.

The client turned to us while being driven by a pressing necessity to make a slow and outdated relational database search customized with the help of Elasticsearch engine implementation. The end goal was getting a high quality, fast, scalable, flexible, and highly reliable product that would allow processing and visualizing tones of information the customer dealt with easily and smoothly.

Does a highly smart search solution with a perfect analytics analysis and flexible search algorithm sound to be a dream? Not sure? Just scan the information below.

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What were the main features of Elasticsearch (ES) we implemented in the process of the case customization?

  • Enhanced flexibility: a search phrase can be easily widened or narrowed while allowing for a number of mistakes and inaccuracies either by default or manually. 

  • Full-text search was used to arrange all the data in accordance with time, location, duration, distance, etc. Those complex filters are highly convenient for users to find and choose what they want easily and quickly. What is more, the filters mentioned could be set as default or chosen manually.

  • Autocomplete is another feature Elasticsearch offers. Due to a completion suggested functionality, we provided fast lookups, flashy feedback as well as real-time suggestions. It is really fantastic to start typing the word and getting an instant search result, isn’t it? 

  • What is more, we implemented multilingualism while choosing a primary and secondary language with a number of modifications possible. 

  • Geolocation and search: on being provided with the address and coordinates, the search engine can easily find all the locations pointed out in the radius of hundreds of miles. All the actions needed are performed accurately and quickly granting the users wider possibilities and reliable automated responses on their requests.  

  • Something simple but powerful, informative, and easy to grasp missing? ES Kibana. Robust visualization capabilities were supported by the featureto give the customer a great opportunity to build impressive and scalable graphics based on the information received. It has been scientifically proved, that data visualization is perfect for concise and meaningful message delivering and understanding. 

On the mentioned above ES features utilization, the end goal of getting a highly reliable, fast and user-friendly search engine implementation was achieved. The client got a perfect visualization and high-ranking website; the users gained quick and highly efficient search results.

Both the client and his target users benefitted from the Elasticsearch site customization greatly. Besides a fast and convenient searching mode, the customer got a perfect possibility to get the fullest information on his site performance while being enabled of gathering and analyzing all the income information with further consideration and enhancement.

SOLR Search Implementation for PHP CMS websites

Besides Elasticsearch, our engineering team has handled the SOLR search solution implementation for a couple of projects based on one of the PHP content management systems. 

The first of them was a TYPO3 project, a product catalog websitenamely. The client regularly updated a list of his product specifications, instructions and documentation on the website, thus making the information turnover highly saturated and variable.  All the data added and changed was dynamically loaded, structured and processed along with all the numerous attributes and additional characteristics. When the quantity of the latter was not very high, a standardized search was used. However, as the dataset was continuously increasing, there arose a need for the search platform update and, consequently, a SOLR search was opted for. 

In the framework of the given project, our engineering team managed to integrate Solr search to enable the users to look for and find the info easily and quickly and for the client to get a holistic solution for his business needs. 

The second Solr case to mention was a big news portal run on Kubernetes.  A text content search was aimed at being replaced by Solr integration for better convenience and speed. We made the implementation; installed and configured Solr with its further integration into the TYPO3 application and Kubernetes cluster integration/installation. 

So, Agiliway, as a company, has ample experience while working with Elasticsearch and Solr search platforms. Our team has expertise not only in integrating Solr with the PHP CMS website hosted on Kubernetes but also the Elasticsearch installation and configuration for a huge database to meet its uprising demands maximally efficiently. It is believed to be of utmost importance to have a practically acknowledged and skilled engineering team while operating Elasticsearch and Solr as the dominant players on the modern search platforms market. We, in Agiliway, are open for the cooperation to share our experience and to offer the very solution best for you. 

Finally, the key question is: ES or Solr? Actually, no unambiguous answer exists. Elasticsearch is better for complex applications while Solr is more oriented at text content. However, it is totally up to you to choose the one and then fit it accordingly to your business needs, requests, and end results expected. Not sure how to do it? Contact  Agiliway expert for tech recommendations, consultation, or best software solutions.

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