The Elastic Stack, commonly referred to as the ELK Stack, is a collection of open-source tools designed to work together for data ingestion, storage, analysis, and visualization. It consists of Elasticsearch, Logstash, and Kibana, with Beats added later to expand its capabilities. Each component plays a distinct role, making the stack highly versatile for log management, analytics, and real-time monitoring.

Core Components:
1. Elasticsearch: A search and analytics engine that indexes and queries data at high speed. It handles the storage and analysis of ingested data.
2. Logstash: A data processing pipeline that ingests data from various sources, transforms it, and forwards it to Elasticsearch.
3. Kibana: A visualization and dashboard tool that interacts with Elasticsearch to display data insights through charts, graphs, and maps.
4. Beats: Lightweight data shippers that collect and send data from endpoints to Logstash or Elasticsearch.

Key Features:
- Real-Time Analytics: Provides instant insights into data trends and anomalies.
- Data Scalability: Manages massive datasets with ease through its distributed architecture.
- Extensibility: Integrates with numerous plugins and APIs, adapting to diverse use cases.
- Open Source: Freely accessible, with a strong community contributing to continuous development.

Use Cases:
- Log Management: Captures, processes, and visualizes logs for debugging and monitoring.
- Security: Supports threat detection, security incident management, and compliance monitoring.
- Operational Intelligence: Tracks system performance and user behavior in real-time.

The Elastic Stack is widely used across industries for its flexibility, performance, and ability to consolidate disparate data sources into actionable insights. Its popularity stems from its seamless integration capabilities and the robustness of its individual components.