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ElasticSearch established itself as one Elasticsearch is an open-source, RESTful, distributed search and analytics engine built on Apache Lucene. Since the first version of Elasticsearch was released in 2010, it has quickly become the best databases most popular search engine, and is commonly used for reallog analytics, full-time text search , and operational intelligence use cases. When coupled with Kibana, a visualization tool, Elasticsearch can be used to provide near-real time analyticsusing large volumes of log data. It Elasticsearch is distributedalso popular because of its easy-to-use search APIs which allow you to easily add powerful search capabilities to your applications.  # Log Analytics - Analyze un-structured and semi-structured logs generated by websites, mobile devices, servers, sensors, and more for a wide variety of applications such as digital marketing, application monitoring, fraud detection, ad tech, gaming, and IoT. Capture, pre-process, and load log data into Elasticsearch using Logstash, Amazon Kinesis Firehose, or Amazon CloudWatch Logs. You can then search, explore, and visualize the data using Kibana and the Elasticsearch query DSL to gain valuable insights about your users and applications.# Full Text Search - Provide your customers with a rich search and navigation experience. Elasticsearch supports faceting, scalablewhich allows your customers to narrow their search results by value ranges for fields like price, highly availableproduct characteristics, and brands; ability to create advanced search criteria filters; search-as-you-type suggesters; and near real-time index updates.# Distributed Document Store - Power your application with an easy to use JSON document-oriented storage platform. Elasticsearch provides a sophisticated simple REST API, fast performance, powerful search capabilities, so you can build highly performant applications that can store and retrieve billions of documents.# Real-time Application Monitoring - Capture activity logs across your customer-facing applications and websites. Use Logstash to push these logs to your Elasticsearch cluster. Elasticsearch indexes the data and makes it available for analysis in near real-time (less than one second). You can then use Kibana to visualize the data and perform operational analyses like identifying outages and problems. With Elasticsearch’s geospatial analysis, you can identify the geographical region where the problem is occurring. Troubleshooting teams can then search the index and perform statistical aggregations to identify root cause and fix issues.