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Editor to share with you what the Elasticsearch application scenarios are, I believe most people do not know much about it, so share this article for your reference, I hope you can learn a lot after reading this article, let's go to know it!

1-logging and log analysis

For those familiar with Elasticsearch, this should come as no surprise. The ecosystem built around Elasticsearch makes it one of the easiest to implement and extend logging solutions. Many users on our platform are no different, and they use this to add logging to their main use cases, or to use us purely for logging.

From Beats,Logstash to Ingest Nodes,Elasticsearch, there are a number of options for getting data from anywhere and indexing it. Then, using Kibana tools enables you to create rich dashboards and analyses, while Curator enables you to automate the lifecycle of indexes.

2-collect and combine public data

Like log data, Elastic Stack has a number of tools that can easily fetch and index remote data. In addition, like most document stores, non-strict schemas give Elasticsearch the flexibility to receive multiple different data sources and make the data manageable and searchable.

A cool example you can view is our Twitter connector (shown below), which allows you to set the topic tags you see on Twitter, then collect tweets about those topic tags and analyze them in Kibana. We built the product on top of the core Elastic Stack components and added some additional parts to help it expand.

3-full-text search

There is no doubt that full-text search, as the core function of Elasticsearch, occupies an important place in this list. Surprisingly, the application of full-text search in our customer base goes far beyond traditional enterprise search or e-commerce.

From fraud detection / security to collaboration, our users have proven that Elasticsearch search is powerful, flexible, and contains a number of tools to make search easier; Elasticsearch has its own query DSL, built-in auto-completion, and so on.

4-event data and indicators

Elasticsearch can also handle time series data such as metrics and application events very well. This is another area of the huge Beats ecosystem that allows you to easily access data from common applications. No matter what technology you use, Elasticsearch has a good opportunity to get out-of-the-box metrics and events. It is very easy to add this feature

5-data Visualization

With a large number of chart options, geographic data tiling service and time series data TimeLion,Kibana is a powerful and easy-to-use visualization tool. For each of the above use cases, Kibana handles some visual components.

Once you are satisfied with the various data extraction tools, you will find that Elasticsearch + Kibana will be your preferred tool for visualizing your data.

These are all the contents of the article "what are the Elasticsearch application scenarios?" Thank you for reading! I believe we all have a certain understanding, hope to share the content to help you, if you want to learn more knowledge, welcome to follow the industry information channel!

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