Software Engineer, Get Ahead of The Game With Elasticsearch.
You’re doing well at your job as a software engineer. Everything is almost okay — yes almost. So why the hell do you need to care about Elasticsearch, a search and analytics engine? You may think you don’t.
And many developers think so. They’re probably right. But I want to share with you 5 mind-blowing and simple truths about Elasticsearch and I dare that after, you won’t see Elasticsearch the same way.
Elasticsearch is a distributed, free and open search and analytics engine for all types of data, including textual, numerical, geospatial, structured, and unstructured. — Elastic.co
Here are the 5 reasons why you have to take a look at Elasticsearch.
1- It is used by Sharks and mouses
Companies like Netflix, Medium — you get me right — , Uber, Shopify, Stack overflow, Slack are using Elasticsearch. At the same time, some software engineers are using it just for syslog search feature on their web servers.
The fact is Elasticsearch is a terrific flexible tool. You can use it as a pen or a beast. It’s up to you.
2- It’s free. Yes, it is.
There are a bunch of proprietary solutions with great features to set up a search engine on the market.
But Elasticsearch has created a disruptive change in the search engine industry being an open-source and free solution. All Elasticsearch features you need to set up a good search engine are free.
3- Don’t care about your infrastructure maintenance
One of the challenging moments in software engineer life is the moment to commit to production. Once it’s done the next major question is about maintenance. That’s where one of Elasticsearch's forces lays.
Platforms like Amazon Elasticsearch, Bonsai, Qbox, and so on have got the ideal plan for you to set up, maintain and grow your Elasticsearch system as you want. Trust me, they propose you The Gain Without Pain.
4- Elasticsearch, sorry ELK is a family of tools
I’ve worked with some well-known companies. One of the main problems of great companies, web platforms, and software engineers is to find the “All is one solution” that can resolve maximum problems: data processing and seeding, full-text search feature, system integration, business intelligence, and analytics tool.
The good news is Elasticsearch has got brother tools like Logstash (a powerful ETL tool for telecom operators, syslog feature, files processing, …), Kibana (an awesome data analysis, visualization, business analytics tool, and dashboard on top of ELK stack), and many others.
5- Install it and start using it
Elasticsearch exposes REST APIs that are easy to use from your terminal or any other client. Furthermore, the Elasticsearch team proposes easy-to-integrate clients (in PHP, NodeJs, Java, C#, and so on).
They have great documentation and you can find well-featured tutorials and training courses online to start right away.
The Elasticsearch community is growing rapidly. With advances in data science and data-processing, companies need more and more experts with good search engine skills. So don’t wait, mate.
I‘m looking forward to reading from you about your experiences with Elasticsearch.
Thanks to my friend Mr. Ofori.