Key Features of Elasticsearch

• Distributed Architecture– Handles large-scale data across multiple nodes.
• Full-Text Search– Uses inverted indexes for fast and efficient text-based queries.
• Real-Time Data Processing– Supports near real-time indexing and search.
• Scalability & High Availability– Scales horizontally using sharding and replication.
• RESTful API- Provides easy interaction with various programming languages.
• Multi-Tenancy Support– Allows indexing of multiple datasets in isolated indices.

Core Components of Elasticsearch

• Index: A collection of documents with similar characteristics, like a database in relational systems.
• Document: A JSON-based data unit stored in an index, similar to a row in a database table.
• Shard: A subset of an index, allowing distributed storage and parallel processing for scalability.
• Replica: A copy of a shard, improving fault tolerance and enhancing query performance.
• Cluster: A group of interconnected nodes working together as a unified system.
• Node: A single server that stores data and performs search and indexing operations.
• Inverted Index: A data structure that enables fast full-text searches by mapping words to documents.
• Query DSL (Domain-Specific Language): A flexible JSON-based query language for searching and filtering data.
• Analyzer: Processes text during indexing and search, including tokenization and stemming.
• Aggregation: A framework for performing analytics, such as calculating metrics and generating reports.

Advantages of Elasticsearch

• High-Speed Search Performance: Lightning-fast search and retrieval of data.
• Scalability & Distributed Architecture: Easily scales horizontally by adding nodes and shards to handle growing data.
• Full-Text Search Capabilities: Supports advanced natural language processing (NLP), tokenization, and relevance scoring.
• Real-Time Data Processing: Indexes data instantly, allowing near real-time search and analytics.
• Flexible Query Language (DSL): Provides a powerful JSON-based Query DSL for complex searches and filtering.
• Built-In Analytics & Aggregations: Performs real-time data analysis, statistical computations, and visualization.
• Fault Tolerance & High Availability: Replica shards ensure data redundancy, minimizing downtime risks.
• Easy Integration with Other Tools: Works seamlessly with Kibana, Logstash, Beats, and other data sources.
• Security & Access Control: Provides role-based access, encryption, and authentication mechanisms.
• Open Source & Active Community: Free to use with strong developer support and regular updates.