eCommerce has become the most engaging & trending business model. But with intense competition & unique features to offer it is a challenging business strategy. If you want to boost the conversion rate and grow the revenue of your Magento selling store, then integrating an incredible search engine is a must.
The primary objective of a search engine is to display the most relevant results to visitors’ questions. If your website doesn’t offer quick and accurate search results, visitors will not stay on your site and find another alternative. When it is about the e-commerce search engines, the 2 most widely-used e-commerce search engines are Magento Sphinx Search Vs Magento Elastic Search to meet merchant selling needs.
Working of Magento Search
When a search engine is installed, it works by indexing website content. This indexing process is constant and when an update is created on the website, it needs to be refreshed. For example, you want to include smartphones in your store. The search engine will index things including title, description, and price. Once a user enters a query, the search engine will display results sorted through the list of items and their attributes. Different search engines respond in a different manner and have features to interpret and filter complex data.
Magento Sphinx Search Vs Magento Elastic Search
Introduction to Magento Elastic Search
Elasticsearch is the most popular and the default option for Magento search. It is a Java-based document store, designed to store JSON documents and interact with it natively. Thus, in addition to the management of text-based queries, it can also comprehend the latest analytical questions as well, covering interpretation of numeric details. From the customer’s viewpoint, it offers faster and more related search experiences. For merchants, this results in faster conversions.
Advantages of Elastic Search
- Great Scalability
If you’re planning to grow your products database, then you might face difficulties while searching for relevant items. But Elasticsearch can help to improve your search capabilities in line with the products database. Several airline tickets and hotel aggregator implements Elasticsearch to provide results by verifying 1 TB data along with 300K events every second.
- Data Visualization
Data visualization is the most demanding feature of eCommerce websites and it’s been thoroughly implemented in Elasticsearch. The presence of Logstash, Kibana plugins, and Elasticsearch offers Magento developers an amazing tool for analytics. It supports not only real-time tracking of web traffic, but also keeps records of important including the number of unique visitors, total visitors, searched questions, and browser used. All this information is presented in the dashboard with colorful tables, charts, and maps.
- Real-time indexing
Elasticsearch has the flexibility to index changing data in real-time. Therefore, if a Magento store needs updating the database instantly, Elasticsearch is a great option to consider. Uber, for example, implements Elasticsearch to gather its business metrics as per the dynamic metrics like pricing and supply positioning. Consequently, Uber can manage over 1,000 questions per second at peak times.
Introduction to Magento Sphinx Search
Sphinx is an SQL-based search tool that customizes search API for different scripting languages including PHP, Python, and Perl. It is an open-source search engine written in C++. It allows to batch index and search data saved in the database, or find data on the go. With multiple text processing features in its kitty, Magento development agency implements Sphinx to satisfy your diverse application requirements. The search engine hosts several significant functions, making sure search quality is easy to tweak.
Advantages of Sphinx Search
- Fast and Robust
From the last few years, Sphinx Search has transformed to a great extent and gained the skills to offer real-time search. Its search speed has reached 500+ queries per second against 1,000,000 documents. Craigslist, which holds over 50 billion page views in a month, can serve more than 300+ million users’ queries on a daily basis. Moreover, Infegy also indexes around 20 billion Facebook, Twitter, and assorted blog posts to offer insightful social media monitoring and analytic queries.
- Create ResultSet in Parallel
One key advantage of the Sphinx is that it allows Magento developers to generate multiple results from the same data at the same time. In contrast, a conventional SQL approach produces a temporary table for each search result set. Meanwhile, Sphinx implements a multi-query mechanism to apply this task. In other words, rather than applying one query after another, Sphinx uses several queries at once and submits them within a single request.
So, these advantages give a clear picture regarding which is a better choice when making a selection between Magento Sphinx Search Vs Magento Elastic Search for your e-commerce store integration.
If you experience a slow response from your eCommerce store to retrieve the search results, it basically needs to integrate a robust search engine. The two Magento Search engines discussed are quite different in their working and making a selection is a complex job. We hope that this article somehow offered you some relevant details, helping you pick the right option for your e-commerce store.
Frequently Asked Questions
Q. How does Magento search work?
The standard Magento 2 search works in the following way: either manually or on a set schedule, the site re-indexes all the goods and adds information about the attributes involved in the search in the database.
Q. What is Magento Elasticsearch?
Elasticsearch is an open-source product that enables you to take data from any source, any format, and search and visualize it in real-time. Elasticsearch performs quick and advanced searches on products in the product catalog.
Q. What is Elasticsearch good for?
Elasticsearch is a highly scalable open-source full-text search and analytics engine. It allows you to store, search, and analyze big volumes of data quickly and in near real-time. It is generally used as the underlying engine/technology that powers applications that have complex search features and requirements.