Elasticsearch Saga— Brief Intro to Elasticsearch
Welcome, This is Part-1!
You know, for search! But Do you actually know how things working under the hood!? So let’s get our basics straight. This is would be a series of topics that would cover primarily the working mechanism of that topic.
What is ElasticSearch?
We don’t need only search, we want robustness, relevance, quickness in our searches. ElasticSearch, one-stop shop with all these features.
Elasticsearch is the go-to search engine (that been built on top of Lucene search engine), you can see its elasticity in terms of use-cases, searching capabilities, administrating capabilities, etc.
Why Elasticsearch?
All aforementioned features plus it’s Open-Source! :P
So let me brief you on WHY.
Any System, Just plug (Use-cases):
ES as the primary backend for your website: So suppose you have a website that allows people to write blog posts or any other content, and you want the ability to search through the posts or content. You can use ES to store all the data related to these posts and serve queries as well.
Adding ES to an existing system: Suppose you have a relational database for your software and you can’t completely switch to ES because ES might not provide some features that you need like transaction support, etc and you can’t redesign the whole architecture (time constraints) then you can just use ES as a secondary data store to your existing system.
Furthermore, ES exposes REST API so any application can use it no matter which programming language it was written in.
What beyond search (functionality):
Handling typos, supporting word derivatives, flexibility in query formation, embedding storage for semantic search with dense vector support, etc.
So this was a brief intro to Elasticsearch. As I told you this is gonna be long series covering the important topics of Elasticsearch which will help you understand the working mechanism of this powerful search tool.
In the next part, I’m writing about Data Organization in ES so stay tuned!
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