Elasticsearch is a non-relational vector database designed primarily for machine-generated data, such as logs and metrics. It offers a wide range of features, including full-text and semantic search, support for vectorized data, native integration of machine learning models, and geospatial capabilities. Elasticsearch aims to serve as a comprehensive engine for observability, security, and search applications.

Kibana is a graphical user interface designed for Elasticsearch. It serves as a central hub for cluster management, developer tools, and specialized solutions in Observability, Security, and Search. It features a robust Dashboards application that enables users to create advanced visualizations, including geospatial components that integrate seamlessly with other visual elements.

In this workshop, we aim to provide attendees with an in-depth look at the analytical aspects of Elasticsearch, focusing specifically on ES|QL. This new query language offers a more robust and comprehensive syntax than the traditional JSON query language. We will also explore the application of ES|QL in Kibana Maps and Dashboards with large datasets and cover other essential topics such as aggregation capabilities and dashboard features. Additionally, we will dedicate some time to discussing new features coming to geospatial Elasticsearch and Kibana Dashboards.