Optimizing Elasticsearch queries using pagination is essential for managing large datasets efficiently, especially when building web pages that display stored data. Elasticsearch offers three primary pagination methods: from/size pagination, scroll pagination, and search_after pagination, each with distinct advantages and limitations. From/size pagination is simple and suitable for small datasets, but it may miss documents in dynamic datasets. Scroll pagination is robust for processing extensive indexes and maintains a consistent index state, though it requires significant memory resources. The search_after pagination, enhanced by the point-in-time (PIT) API from version 7.10, allows for efficient deep pagination with consistent page results, making it the preferred method for large datasets over 10,000 documents. However, AWS users must rely on scroll pagination until support for Elasticsearch version 7.10 is available. Understanding the requirements and characteristics of each method helps developers choose the most suitable approach for their specific needs and data structures.