### Module 1: Introduction to OpenSearch #### Lesson 1: Overview of OpenSearch and Its Ecosystem **Objective**: Introduce OpenSearch and its ecosystem, outlining its origins, development, and current standing in the search and analytics landscape. **Topics**: - **History and Evolution**: Brief history of OpenSearch, its fork from Elasticsearch 7.10, and the role of AWS in its development. - **Core Components**: Introduction to OpenSearch and OpenSearch Dashboards, highlighting their purposes and capabilities. - **Ecosystem and Tools**: Overview of the broader OpenSearch ecosystem, including plugins, integrations, and community contributions. - **Use Cases**: Discussion on common use cases for OpenSearch, such as log analytics, full-text search, and real-time analytics applications. #### Lesson 2: Differences Between OpenSearch and Other NoSQL Databases **Objective**: Provide an understanding of how OpenSearch fits within the NoSQL landscape and how it differs from other NoSQL databases. **Topics**: - **Database Types**: Quick recap of different NoSQL database types (key-value, document, wide-column, graph) and their typical use cases. - **Comparison Criteria**: Comparison of OpenSearch against other NoSQL databases based on criteria like data model, query capabilities, scalability, performance, and use case applicability. - **When to Use OpenSearch**: Guidelines on choosing OpenSearch over other NoSQL options, focusing on its strengths in search and analytics scenarios. #### Lesson 3: Key Concepts and Terminologies **Objective**: Provide a comprehensive overview of core OpenSearch concepts and terminologies, emphasizing their role and interaction within an OpenSearch cluster. **Topics**: See [[_Entities]]