Search Azure terms

AI and Machine Learning command-rich Search admin key A search admin key is one of the generated API keys for an Azure AI Search service that allows full read-write data-plane access. It can create, update, or delete indexes, indexers, data sources, and documents, so it must be protected, rotated, and replaced with role-based access when possible. Azure AI Search fundamentals 5 commands Aliases: Azure AI Search admin key, search service admin key, Azure Search API admin key, primary admin key, secondary admin key Quick peek Open full term page

AI and Machine Learning premium Search analyzer A search analyzer is the Azure AI Search text-processing component that breaks strings into searchable tokens during indexing and query execution. Built-in, language, or custom analyzers control tokenization, normalization, stemming, stop words, and other lexical behavior for searchable string fields. Azure AI Search fundamentals 8 commands Aliases: Azure AI Search analyzer, text analyzer, search text analyzer, custom analyzer, language analyzer Quick peek Open full term page

AI and Machine Learning premium Search data source A search data source is an Azure AI Search indexer object that describes where external content comes from. It specifies the supported source type, connection information, credentials or identity, container or query, and sometimes change or deletion detection used by indexers. Azure AI Search fundamentals 5 commands Aliases: Azure AI Search data source, indexer data source, SearchIndexerDataSourceConnection, data source connection, Azure Search data source object Quick peek Open full term page

AI and Machine Learning premium Search document A search document is a single searchable JSON record stored in an Azure AI Search index. It contains field values defined by the index schema, including a unique key, retrievable content, filters, facets, sortable values, and sometimes vector fields. Azure AI Search fundamentals 5 commands Aliases: Azure AI Search document, search index document, indexed document, searchable document, document in search index Quick peek Open full term page

AI and Machine Learning premium Search filter A search filter is an OData expression in Azure AI Search that narrows query results before or during retrieval. Filters compare fields, ranges, collections, geography, or security values so the service returns only documents that satisfy those conditions. It depends on filterable fields and trusted query construction. Azure AI Search fundamentals 5 commands Aliases: Azure AI Search filter, OData filter, search query filter, filter expression, Azure Search filter, document filter Quick peek Open full term page

AI and Machine Learning premium Search index A search index is the searchable data structure in Azure AI Search. It defines fields, attributes, analyzers, vector settings, scoring options, and stored documents so applications can run queries, filters, facets, and retrieval workflows. It is the contract that applications query at runtime. Search fundamentals 5 commands Aliases: Azure AI Search index, Azure Search index, search schema, index schema, searchable index, retrieval index Quick peek Open full term page

AI and Machine Learning premium Search index projection A search index projection defines how enriched content from an Azure AI Search skillset is projected into one or more indexes. It is commonly used to create chunked child documents with parent metadata for retrieval-augmented generation. It is configured as part of the enrichment pipeline. Azure AI Search fundamentals 5 commands Aliases: Azure AI Search index projection, indexer projection, projected search index, RAG chunk projection, skillset index projection, index projections, projection selector, projected index, chunk projection Quick peek Open full term page

AI and Machine Learning premium Search indexer A search indexer is an Azure AI Search component that crawls a supported data source, extracts or enriches content, and loads documents into a search index. It can run on demand or on a schedule. It connects source freshness to searchable content. Azure AI Search fundamentals 5 commands Aliases: Azure AI Search indexer, Azure Search indexer, search crawler, pull indexing pipeline, managed search ingestion, indexer run, indexer schedule, search ingestion job Quick peek Open full term page

AI and Machine Learning premium Search partition A search partition is a capacity unit in Azure AI Search that provides storage and indexing resources for indexes. Increasing partitions expands index storage and can improve throughput for data ingestion and some query workloads. It is configured on the search service capacity model. Azure AI Search intermediate 5 commands Aliases: Azure AI Search partition, Azure Search partition, search service partition, search capacity partition, partition count, search unit partition Quick peek Open full term page

AI and Machine Learning premium Search query key A search query key is an Azure AI Search API key that permits read-only document queries against indexes. It is intended for client applications that need search results but should not manage indexes, data sources, indexers, skillsets, or service configuration. Search fundamentals 5 commands Aliases: Azure AI Search query key, search API query key, read-only search key, query API key, Azure Search query key Quick peek Open full term page

AI and Machine Learning premium Search relevance Search relevance in Azure AI Search is the process of ranking matching documents so the most useful results appear first. Relevance can depend on BM25 keyword scoring, analyzers, filters, scoring profiles, vector retrieval, semantic ranking, application query design, and production feedback. Search intermediate 5 commands Aliases: Azure AI Search relevance, search ranking, result relevance, BM25 relevance, semantic relevance, ranking quality Quick peek Open full term page

AI and Machine Learning premium Search replica A search replica is a copy of the Azure AI Search engine used to serve query and indexing workloads. Adding replicas increases query concurrency and availability, while partitions provide storage capacity; together they determine search units, cost, and production capacity-planning decisions. Search fundamentals 5 commands Aliases: Azure AI Search replica, search service replica, replica count, query replica, search capacity replica Quick peek Open full term page

AI and Machine Learning premium Search scoring profile A search scoring profile is an Azure AI Search index configuration that boosts or suppresses ranking for matching documents. It can use weighted text fields and scoring functions such as freshness, magnitude, distance, or tags to shape relevance during query execution. Search intermediate 5 commands Aliases: Azure AI Search scoring profile, search ranking profile, scoring profile, relevance boost profile, search boost profile Quick peek Open full term page

AI and Machine Learning premium Search semantic configuration A search semantic configuration is an Azure AI Search index setting that names the fields used by semantic ranker. It prioritizes title, content, and keyword fields so semantic ranking, captions, and answers can evaluate the most meaningful document text during semantic queries. Search advanced 5 commands Aliases: Azure AI Search semantic configuration, semantic search configuration, semantic ranker configuration, prioritized fields, semantic config Quick peek Open full term page

AI and Machine Learning premium Search service An Azure AI Search service is the provisioned Azure resource that hosts indexes, indexers, skillsets, query APIs, keys, networking, replicas, partitions, and monitoring settings. It is the management and data-plane boundary for building searchable content and retrieval experiences. and governance reviews. Azure AI Search fundamentals 5 commands Aliases: Azure AI Search service, search resource, search endpoint, Microsoft.Search search service, managed search service Quick peek Open full term page

Monitoring and Observability premium Search service diagnostic logs Search service diagnostic logs are Azure Monitor resource logs from Azure AI Search that record query, suggest, autocomplete, lookup, indexing, service statistics, and operational events. They are collected in Log Analytics or storage when diagnostic settings are enabled on the search service. Data operations intermediate 5 commands Aliases: Azure AI Search logs, search resource logs, Microsoft.Search diagnostics, search operation logs, Search diagnostic settings Quick peek Open full term page

AI and Machine Learning premium Search skill A search skill is one processing step inside an Azure AI Search skillset. It transforms extracted source content during indexing, such as OCR, entity recognition, translation, text splitting, embedding generation, or custom enrichment, and writes output into the enriched document tree. Search intermediate 5 commands Aliases: Azure AI Search skill, enrichment skill, cognitive skill, custom skill, indexing skill Quick peek Open full term page

AI and Machine Learning premium Search skillset A search skillset is a reusable Azure AI Search object attached to an indexer. It groups one or more skills that transform raw source content during indexing, producing searchable text, vectors, structure, or custom enrichments before output mappings populate the target index. Azure AI Search fundamentals 5 commands Aliases: Azure AI Search skillset, AI enrichment pipeline, cognitive skillset, indexer skillset, search enrichment pipeline Quick peek Open full term page

AI and Machine Learning premium Search suggester A search suggester is an Azure AI Search index configuration that enables typeahead behavior for users and apps. It names string fields used to build internal prefix structures so autocomplete can complete partial queries and suggestions can return matching documents from selected fields. Azure AI Search fundamentals 5 commands Aliases: Azure AI Search suggester, typeahead suggester, autocomplete suggester, search-as-you-type configuration, suggest API fields Quick peek Open full term page

AI and Machine Learning premium Search synonym map A search synonym map is an Azure AI Search resource that stores equivalent terms, abbreviations, or phrase rewrites. It can be assigned to searchable string fields so queries match related words without requiring users to type every possible production search term. Azure AI Search fundamentals 5 commands Aliases: synonym map, search synonyms, Azure AI Search synonyms, synonymMaps, query expansion map Quick peek Open full term page

AI and Machine Learning premium Search vectorizer A search vectorizer is an Azure AI Search index configuration that converts text or images into vectors at query time. It references an embedding model, connects through a vector profile, and should match the model used to create indexed vector content. Search advanced 5 commands Aliases: vectorizer, search vectorizer, Azure AI Search vectorizer, query-time vectorization, integrated vectorization Quick peek Open full term page

AI and Machine Learning command-rich Data source in AI Search Data source in AI Search is documented by Microsoft as part of the Azure AI Search area in Azure. Azure AI Search intermediate 6 commands Aliases: No aliases yet Quick peek Open full term page

AI and Machine Learning premium Azure AI Search index An Azure AI Search index is the place where your application searches. It is not just a pointer to a database or blob container. It is a separate searchable structure with documents, fields, and rules for how text, filters, facets, semantic ranking, and vectors behave. If the index schema is wrong, the search experience feels wrong even when the source data is good. Developers and operators use indexes to make. AI platform and search intermediate 5 commands Aliases: Azure AI Search index, search index, AI Search index, azure-ai-search-index Quick peek Open full term page

AI and Machine Learning premium Azure AI Search indexer An Azure AI Search indexer is the automated worker that fills a search index from another data source. Instead of your application pushing every document into Azure AI Search, the indexer pulls from places such as Blob Storage, Azure SQL, Cosmos DB, or Data Lake Storage. It can map fields, detect changes, crack documents, and run enrichment skills before writing searchable documents. It is useful when source data changes regularly. AI platform and search intermediate 5 commands Aliases: Azure AI Search indexer, search indexer, indexer, azure-ai-search-indexer Quick peek Open full term page

Databases premium Cosmos DB full-text search Cosmos DB full-text search means searching natural-language text stored in Cosmos DB for NoSQL items. It is the practical label operators use when they decide how application data should be modeled, queried, protected, and monitored in Azure Cosmos DB. In plain English, it explains where developers, platform engineers, and support teams meet: the application wants fast data access, while the platform controls scale, cost, security, and recovery. A good glossary entry helps the team know which setting to inspect, which owner to involve, and which symptoms prove the design works. Azure Cosmos DB intermediate 5 commands Aliases: Azure Cosmos DB full-text search, cosmos db full-text search Quick peek Open full term page

AI and Machine Learning premium Hybrid search Hybrid search in Azure AI Search combines vector search and keyword or full-text search in a single request and merges the results. Azure AI Search advanced 5 commands Aliases: Hybrid search, hybrid search Quick peek Open full term page

AI and Machine Learning premium Azure AI Search Azure AI Search is a managed retrieval service for full-text, vector, hybrid, and semantic search across application and enterprise content. It provides search services, indexes, indexers, skillsets, ranking features, security controls, and APIs used by apps, copilots, and knowledge portals. Search fundamentals 4 commands Aliases: Azure AI Search, AI Search, Azure Cognitive Search, enterprise search, vector search, hybrid search, semantic search, Search service Quick peek Open full term page

AI and Machine Learning premium Azure AI Search data source Azure AI Search data source is the connection definition an Azure AI Search indexer uses to read content from a supported external data store. AI platform and search intermediate 4 commands Aliases: Search data source, SearchIndexerDataSourceConnection, data source connection, indexer data source, search data source connection Quick peek Open full term page

AI and Machine Learning premium Azure AI Search service Azure AI Search service is the Azure resource that hosts Azure AI Search indexes, indexers, skillsets, keys, capacity, networking, and query endpoints. AI platform and search intermediate 4 commands Aliases: AI Search resource, AI Search service, Azure Search service, Search service, search service Quick peek Open full term page

AI and Machine Learning premium Azure AI Search skillset Azure AI Search skillset is a reusable Azure AI Search enrichment object that applies built-in or custom processing during indexer execution. AI platform and search intermediate 4 commands Aliases: AI enrichment skillset, Search skillset, cognitive skillset, skillset Quick peek Open full term page

Databases premium Full-text search in Cosmos DB Full-text search in Cosmos DB is the Azure Cosmos DB for NoSQL capability that lets selected text fields be indexed and queried by meaningfully matching words instead of only exact values. Teams use it to build search features inside a Cosmos DB application when text relevance, hybrid retrieval, or document search must stay close to transactional data. In daily Azure work, it shows up when engineers design product search, rank support articles, combine text and vector retrieval, tune index policy, or investigate why a query misses expected documents. Azure Cosmos DB advanced 4 commands Aliases: Cosmos DB full-text search, full text search for NoSQL, Cosmos DB text search Quick peek Open full term page

Databases premium Hybrid search in Cosmos DB Hybrid search in Cosmos DB is a Cosmos DB for NoSQL capability that combines vector search with full-text search scoring, then merges results with Reciprocal Rank Fusion. Azure Cosmos DB advanced 4 commands Aliases: Cosmos DB hybrid search, Cosmos DB RRF search, Hybrid search in Azure Cosmos DB, hybrid search in cosmos db, Hybrid search in Cosmos DB Quick peek Open full term page

Databases premium Cosmos DB vector search Cosmos DB vector search is an Azure glossary term for the Azure Cosmos DB capability for storing vector embeddings with operational data and querying for similar items instead of only exact field matches. In practice, it helps teams reason about semantic retrieval, recommendation, retrieval augmented generation, and similarity search inside a Cosmos DB workload using live Azure evidence, documented ownership, and Microsoft Learn guidance. It should be reviewed through security, reliability, operations, cost, and performance lenses before production changes. Azure Cosmos DB advanced 3 commands Aliases: Azure Cosmos DB vector search Quick peek Open full term page

Databases field-manual-complete Redis vector similarity search Redis vector similarity search lets Redis answer questions like “which stored items are most similar to this embedding?” Instead of matching only exact words, applications store vectors that represent meaning, images, products, documents, or events. Redis indexes those vectors and returns nearby results quickly. In Azure, this is useful when a team wants low-latency AI retrieval or recommendations close to the application cache. It is not a magic model; the quality still depends on embeddings, index design, metadata filters, and refresh discipline. Azure Managed Redis advanced 5 commands Aliases: Redis vector search, Redis VSS, RediSearch vector search, Redis KNN search Quick peek Open full term page

AI and Machine Learning field-manual-complete Vector search Vector search retrieves content by comparing embedding vectors, helping Azure applications find semantically similar documents, images, products, or passages. Search fundamentals 4 commands Aliases: semantic vector search, similarity search, nearest-neighbor search, AI Search vector search Quick peek Open full term page

AI and Machine Learning premium Searchable field A searchable field is an Azure AI Search index field whose text is analyzed and added to the full-text search index. Queries can match tokens from that field at query time, unlike fields used only for filtering, sorting, faceting, or retrieval. AI platform and search intermediate 5 commands Aliases: searchable field, searchable index field, Azure AI Search field attribute, full-text field, searchable attribute Quick peek Open full term page

AI and Machine Learning learning-path-anchor Synonym map A synonym map helps Azure AI Search understand that different words can mean the same thing for search. Users may type laptop, notebook, ultrabook, or a product nickname, while the indexed document uses only one of those terms. The synonym map teaches the search service to expand or rewrite the query so relevant documents... Azure AI Search intermediate 5 commands Aliases: AI Search synonym map, search synonyms, synonymMaps, equivalent terms map Quick peek Open full term page

Storage learning-path-anchor Table Storage Table Storage is Azure Storage for simple structured NoSQL records. You create tables, store entities, and identify each entity with a PartitionKey and RowKey. It is useful when the data is large, sparse, inexpensive to keep, and usually accessed by known keys. It is not a relational database, search engine, or analytics warehouse. The best fit is operational data that can be denormalized, read directly, updated independently, and kept cheap without requiring joins, stored procedures, or secondary indexes. Table Storage fundamentals 5 commands Aliases: Azure Table Storage, Storage Tables, Azure Storage Tables, Azure Tables storage Quick peek Open full term page

Databases learning-path-anchor Cosmos DB dedicated gateway Azure Cosmos DB dedicated gateway is provisioned server-side compute that fronts an account and enables the integrated cache for supported NoSQL workloads. Azure Cosmos DB fundamentals 3 commands Aliases: No aliases yet Quick peek Open full term page

AI and Machine Learning premium Computer Vision the Azure AI capability that helps applications understand images, read text, detect visual features, and return structured insights from pictures or screenshots Azure AI services fundamentals 12 commands Aliases: No aliases yet Quick peek Open full term page

AI and Machine Learning premium Azure OpenAI Azure OpenAI provides OpenAI model capabilities through Azure resources, deployments, identity, networking, quota, and monitoring controls. Azure OpenAI intermediate 8 commands Aliases: Azure OpenAI Service Quick peek Open full term page

AI and Machine Learning premium Scoring profile A scoring profile is an Azure AI Search index setting that boosts ranking for matches that meet business rules. It can weight text fields or apply functions for freshness, distance, magnitude, or tags, and a query chooses one profile to influence returned order. Azure AI Search fundamentals 8 commands Aliases: Azure AI Search scoring profile, search relevance profile, relevance scoring profile, scoringProfiles, boosting profile Quick peek Open full term page

Databases premium Cosmos DB vector embedding policy Cosmos DB vector embedding policy is the container policy that defines vector paths, dimensions, data type, and distance function for embeddings stored in Cosmos DB for NoSQL. It tells Cosmos DB which item properties contain embeddings and how those vectors should be interpreted. You see it when teams build semantic search, recommendation, image similarity, or retrieval-augmented generation features on Cosmos DB data. The production check is whether the vector path, dimensions, data type, and distance function are correct before production data lands. Document the decision in code, templates, metrics, and runbooks. Azure Cosmos DB intermediate 7 commands Aliases: No aliases yet Quick peek Open full term page

Databases premium Cosmos DB vector index Cosmos DB vector index is an indexing-policy configuration that improves vector-search latency and RU efficiency for embeddings in Cosmos DB for NoSQL. It helps Cosmos DB find similar vectors without comparing every embedding in a container one by one. You see it when queries use VectorDistance, hybrid search combines text and vectors, or teams tune flat, quantized flat, and DiskANN-style index choices. The production check is whether the index type, vector path, dimensions, filters, and recall target fit the workload. Document the decision in code, templates, metrics, and runbooks. Azure Cosmos DB intermediate 7 commands Aliases: No aliases yet Quick peek Open full term page

Databases premium Cosmos DB TTL Cosmos DB TTL is the time-to-live setting that lets Cosmos DB automatically delete items after a configured number of seconds. It turns data expiration into a database policy instead of a manual cleanup job. You see it when containers store sessions, events, temporary search data, soft-delete markers, or records with explicit retention windows. The production check is whether container-level TTL, item overrides, change-feed behavior, and recovery expectations match the business retention rule. Document the decision in code, templates, metrics, and runbooks. Azure Cosmos DB intermediate 6 commands Aliases: No aliases yet Quick peek Open full term page

AI and Machine Learning premium Exhaustive KNN Exhaustive KNN is a vector search algorithm that calculates distances across all candidate vectors to return the exact nearest neighbors for a query. Teams use it to test vector relevance, produce exact nearest-neighbor baselines, or serve smaller vector workloads where accuracy matters more than approximate search speed. It is not HNSW approximate search, semantic ranking, a text analyzer, an embedding model, or a fix for poor chunking and low-quality vectors. In production, confirm index schema, vector dimensions, algorithm configuration, vector profile, query k value, exhaustive flag, latency, throttling, relevance test set, and comparison with HNSW results before treating the design. Azure AI Search advanced 6 commands Aliases: exhaustive k-nearest neighbors, brute-force vector search, exhaustive vector search Quick peek Open full term page

Analytics premium External data source An External data source is a database object that defines the location and connection information used by SQL engines to access external data. Teams use it to point serverless SQL, dedicated SQL pools, or PolyBase-style queries to data stored outside the database, such as Azure Storage or Data Lake paths. It is not the external table schema, the file format definition, the storage account itself, or proof that the credential can read every file under the path. Synapse SQL and data virtualization intermediate 6 commands Aliases: CREATE EXTERNAL DATA SOURCE, PolyBase external data source, Synapse external data source Quick peek Open full term page

AI and Machine Learning premium Facetable field A Facetable field is an Azure AI Search index field marked so the service can return facet buckets, counts, or filter choices for query results. Teams use it to let search applications show refiners such as category, brand, location, date range, status, or price band without scanning and counting results in application code. It is not a full-text analyzer, vector field setting, ranking rule, security trim, or proof that every facet value is clean, useful, or safe to expose to users. Azure AI Search intermediate 6 commands Aliases: Azure AI Search facetable field, facetable index field, facet-enabled field, facetable attribute Quick peek Open full term page

AI and Machine Learning premium Faceted navigation Faceted navigation is an Azure AI Search pattern where query responses include facet buckets that users select to narrow search results by fields such as category, location, price, or date. Teams use it to help users explore large result sets through visible refiners instead of typing exact terms or manually paging through every matching document. It is not a ranking algorithm, semantic answer, vector search method, access-control system, or guarantee that facet counts represent information a user is authorized to see. Azure AI Search intermediate 6 commands Aliases: facets, search facets, facet navigation, Azure AI Search facets, refiners Quick peek Open full term page

AI and Machine Learning premium Form Recognizer Form Recognizer is the former name for Azure AI Document Intelligence, an Azure AI service that analyzes documents and extracts text, tables, layout, and structured fields. Teams use it to turn invoices, receipts, IDs, contracts, forms, and scanned documents into structured data for applications, workflow automation, search indexing, review queues, and compliance processing. It is not a human legal review, a guarantee that every extracted field is correct, a storage system for regulated documents, or a reason to skip confidence thresholds and validation logic. Azure AI Document Intelligence intermediate 6 commands Aliases: Azure Form Recognizer, Azure AI Document Intelligence, Document Intelligence, Azure AI Form Recognizer Quick peek Open full term page