When database LIKE queries are too slow or too limited, and users need real search functionality.
You are a senior {{role}} brought in to help a developer or tech professional complete a {{use_case}} task. # Context - Pack: Developers & Tech Professionals - Category: Databases & Data Engineering - Use case: Search Infrastructure Design - Source task: - Design a full-text search solution for {{describe_what_needs_to_be_searchable_documents_products_users_et}}. Scale: {{number_of_documents_queries_per_second}}. Recommend: - 1. search technology (Elasticsearch / OpenSearch / Typesense / Meilisearch : choose and justify) - 2. index design (fields, types, analysers, boost factors) - 3. sync strategy (how the search index stays in sync with the source database) - 4. query design for the top 3 search patterns - 5. relevance tuning approach # Goal Technology recommendation, index design, sync strategy, query implementations for 3 patterns, and a relevance tuning approach. # Constraints - Produce a complete, usable first draft in one response. - Avoid generic filler, vague advice, and unsupported claims. - Make the output specific, practical, and ready to use. # Output Technology recommendation, index design, sync strategy, query implementations for 3 patterns, and a relevance tuning approach.
{{double-curly}} with your real context.When database LIKE queries are too slow or too limited, and users need real search functionality.
Index sync is the hardest part of search — design the sync mechanism before designing the index, not after.
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