Why Searching Techniques Like Elastic OR Solr Important to Build a Good Product?

Searching techniques plays an important role in building a good product. It depends on whether your product searching is required or not. If I talk about e-commerce platforms then searching is an essential and a crucial part for that. Think about amazon or flipkart without a searching capability. They are nothing without a search and filters. Searching makes the user’s buying experience easy.

While working in service based companies I was not aware about all these technologies. I learned there only CRUD operations, handling clients, documentation, some part project management not more than that. That’s why I say that I learn there only how to code. Before I joined startups I usually thought about how these guys did it whenever I visit any website and if its pages are loading very fast. If you search any product on amazon, myntra or flipkart and scroll down the products load very fast.

Have you ever thought about it? If not, think about it.

How did they do it?

What technology is working behind?

If you are curious about technologies then these are common questions and obvious to come to our mind.

There are some searching techniques which are used by them. If you are thinking of building any product and search and filters are in your roadmap then these technologies are very important to you.

Whether you are a software engineer or a product manager, at least basic knowledge about these technologies is much required. Based on my 11 years of working experience in startups, I would say that knowledge of searching techniques is much required to work effectively with startups.

Now lets understand first what are the searching techniques and how these work. We already understood in the previous article what is caching and how it works. In similar ways there are some searching techniques which are used to store the large data itself instead of using data directly from the database. If we fetch the data directly from the database for searching and filtering then we can’t maintain the ideal page load speed which is between 0–5 seconds.

There is a huge amount of data for searching and filtering if we talk about amazon, myntra or flipkart, right?

That’s the reason the searching techniques were invented to improve the user experience by loading the products in a fast way. These searching techniques have their own storage. All the products imported from the database into this storage. We can say it’s a separate database which is maintained by these techniques. There are some workers which are used to import all the new products from the database to this storage.

These searching techniques provide various features like full-text search, logging, metrics analysis, and other use cases that involve searching and analyzing large amounts of structured and unstructured data.

We can easily understand how these techniques works internally by the help of the following diagram as

Why Search Engines Are Important to Build a Scalable Product?

Search engines are important to build a scalable product for several reasons:

1. Improved User Experience: Search engines allow users to quickly and easily find the information they are looking for within a product. This enhances user experience and increases user satisfaction.
2. Relevant Search Results: Search engines like Elastic utilize advanced algorithms to provide users with relevant search results. This improves the accuracy and usefulness of search results, making it easier for users to find what they are looking for.
3. Scalability: Search engines like Elastic are designed to handle large amounts of data, making them a scalable solution for products that need to process and index vast amounts of information.
4. Real-time Search: Elastic allows for real-time search capabilities, enabling users to see updates and changes to the data immediately. This is particularly important for products that deal with time-sensitive information or data that is frequently updated.
5. Analytics: Search engines like Elastic provide powerful analytics capabilities, allowing product teams to understand how users are interacting with their product and identify areas for improvement. This can help inform product decisions and drive better outcomes.

What Are The Different Types of Search Engines to Build a Scalable Product

There are various types of Inverted index search engines. They are a type of full-text search engine that uses an index to efficiently search through large amounts of text-based data. Here are some different types of inverted index search engines:

1. Apache Lucene: Lucene is a popular open-source search engine library that is widely used in many applications. It is designed to be highly scalable and efficient, making it a good choice for indexing and searching through large volumes of text-based data.
2. Elasticsearch: Elasticsearch is an open-source, distributed search engine based on Lucene. It provides a RESTful API and advanced features such as faceted search, real-time indexing, and support for multiple document types.
3. Apache Solr: Solr is another open-source search engine based on Lucene. It provides a web interface for managing indexes and search queries, and supports features such as faceted search, highlighting, and spell checking.
4. Amazon CloudSearch: CloudSearch is a fully managed search service provided by Amazon Web Services (AWS). It is based on Solr and provides a scalable, fully managed search solution that can be integrated with other AWS services.
5. Microsoft Azure Search: Azure Search is a fully managed cloud search service provided by Microsoft. It supports full-text search, faceted search, and geo-spatial search, and can be integrated with other Azure services such as Azure Blob Storage and Azure SQL Database.

Each of these inverted index search engines has its own strengths and weaknesses, and the best choice depends on your specific use case and requirements. It’s important to evaluate the features, performance, scalability, and cost of each option before making a decision.

Based on resource availability, expertise and your comfort you can choose any searching technique. I hope this will be useful for your knowledge to grow in your career or to build a product. I would request you to like it, share it and mention in the comment box which one is suitable for you?

Conclusion

Searching techniques plays an important role to build a scalable and good product. Searching techniques are useful to improve user experience for any product. What are the different types of searching techniques, how searching techniques work internally and how these are helpful to improve user experience.