{"id":4295,"date":"2017-12-04T18:26:28","date_gmt":"2017-12-05T02:26:28","guid":{"rendered":"https:\/\/www.couchbase.com\/blog\/?p=4295"},"modified":"2025-11-07T04:29:38","modified_gmt":"2025-11-07T12:29:38","slug":"comparing-couchbase-views-couchbase-n1ql-indexing","status":"publish","type":"post","link":"https:\/\/www.couchbase.com\/blog\/es\/comparing-couchbase-views-couchbase-n1ql-indexing\/","title":{"rendered":"Comparando Couchbase Views con Couchbase N1QL & Indexing."},"content":{"rendered":"

A medida que la plataforma de datos Couchbase evolucion\u00f3, servicios como N1QL y GSI Indexing manejaron los casos de uso que Couchbase VIEWS sol\u00eda manejar y mucho m\u00e1s. Es l\u00f3gico hacer la pregunta comparativa entre ellos. He aqu\u00ed una tabla comparativa entre ambos. Esto est\u00e1 pensado para desarrolladores y arquitectos familiarizados con ambos y no como un art\u00edculo introductorio. Utiliza los enlaces aqu\u00ed para aprender m\u00e1s y jugar con las caracter\u00edsticas respectivas.<\/p>\n

\"\"<\/p>\n

\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n
Tema<\/strong><\/th>\nVistas de Couchbase Map-Reduce<\/strong><\/th>\nCouchbase N1QL+GSI<\/strong><\/th>\n<\/tr>\n
Ac\u00e9rquese a<\/td>\nBasado en funciones map() y reduce() definidas por el usuario que operan sobre los datos en segundo plano. Como map() y reduce() est\u00e1n escritas en Javascript, se puede codificar l\u00f3gica compleja dentro de esas funciones.<\/td>\nBasado en la consulta declarativa N1QL (SQL para JSON). Utiliza \u00edndices apropiados para optimizar la ejecuci\u00f3n y se ejecuta din\u00e1micamente orquestando servicios de consulta-\u00edndice-datos. N1QL permite realizar consultas f\u00e1cilmente escribibles y legibles para JSON. Porque est\u00e1 inspirado en SQL, es flexible, componible. Al estar extendido para JSON, funciona con datos JSON enriquecidos. Utiliza l\u00f3gica booleana de 4 valores (true, false,NULL, MISSING)<\/td>\n<\/tr>\n
M\u00e1s informaci\u00f3n<\/td>\nDocumentos de Couchbase:\u00a0https:\/\/bit.ly\/2jQrY11<\/a><\/td>\n\n1. https:\/\/query.couchbase.com<\/a>
\n2. https:\/\/www.couchbase.com\/blog\/n1ql-practical-guide-second-edition\/<\/a><\/td>\n<\/tr>\n
Consulta de<\/td>\nConsulta basada en<\/strong><\/p>\n

\n1. Tecla \u00fanica
\n2. Juego de llaves
\n3. Tecla Inicio-Fin
\n4. Teclas de inicio-fin de documento
\n5. Agrupar por, Agregaci\u00f3n
\n6. Paginaci\u00f3n<\/p>\n<\/td>\n

Declaraciones de consulta<\/strong><\/p>\n

1. SELECCIONE
\n2. INSERTAR
\n3. ACTUALIZACI\u00d3N
\n4. BORRAR
\n5. FUSIONAR
\n6. INFER
\n7. EXPLICAR
\nOperaciones de consulta:<\/strong>
\n1. Tecla \u00fanica
\n2. Juego de llaves
\n3. Teclas de rango
\n4. Gama de teclas de documento
\n5. Predicados arbitrariamente complejos
\n6. INNER JOIN, LEFT OUTER JOIN
\n7. NEST, UNNEST
\n8. GRUPO POR
\n9. Agregaci\u00f3n
\n10. Paginaci\u00f3n (OFFSET, LIMIT)
\n11. Optimizaci\u00f3n
\n12. ORDEN POR
\n13. TENIENDO
\n14. 14. Subconsultas (correlacionadas, no correlacionadas)
\n15. Tablas derivadas
\n16. Operaciones SET: UNI\u00d3N, UNI\u00d3N TODO, EXCEPTO, EXCEPTO TODO, INTERSECCI\u00d3N
\n17. Consultas altamente componibles, lo que significa que estas operaciones pueden combinarse simplemente entre s\u00ed para expresar f\u00e1cilmente preguntas y operaciones empresariales complejas.<\/p>\n<\/td>\n<\/tr>\n

Indexaci\u00f3n<\/td>\n\u00cdndice simple para vistas.<\/td>\n\n \t1. \u00cdndice primario
\n \t2. \u00cdndice primario con nombre
\n \t3. \u00cdndice secundario
\n \t4. \u00cdndice secundario compuesto
\n 5. \u00cdndice funcional
\n \t6. \u00cdndice de matrices
\n \t7. matriz ALL
\n \t8. matriz ALL DISTINCT
\n \t9. \u00cdndice parcial
\n \t10. \u00cdndice adaptativo
\n \t11. \u00cdndices duplicados
\n \t12. \u00cdndice de cobertura<\/p>\n<\/td>\n<\/tr>\n
Particionamiento<\/td>\nAlineado con la partici\u00f3n de datos.<\/td>\nServicios independientes.<\/p>\n

Las escalas N1QL y GSI son independientes del servicio Data y entre s\u00ed.<\/span><\/td>\n<\/tr>\n

Escala<\/td>\nEscalas con servicio de datos<\/td>\nEscalado independiente mediante escalado multidimensional (MDS)<\/td>\n<\/tr>\n
B\u00fasqueda con clave de documento<\/td>\nDado que los datos est\u00e1n particionados en funci\u00f3n de la clave del documento, obtiene el documento directamente del nodo<\/td>\nEspecifique la consulta mediante la cl\u00e1usula USE KEYS.<\/p>\n

Dado que los datos est\u00e1n particionados en funci\u00f3n de la clave del documento, obtiene el documento directamente del nodo<\/span><\/td>\n<\/tr>\n

B\u00fasqueda con clave de \u00edndice<\/td>\nDispersi\u00f3n-Recogida<\/td>\nCada exploraci\u00f3n de \u00edndice en un \u00fanico nodo; Datos en varios nodos.<\/p>\n

Postprocesamiento en el nodo Consulta<\/span><\/td>\n<\/tr>\n

Exploraci\u00f3n de la gama<\/td>\nDispersi\u00f3n-Recogida<\/td>\nExploraci\u00f3n de \u00edndices en un \u00fanico nodo.<\/p>\n

Postprocesamiento en el nodo Consulta<\/span><\/td>\n<\/tr>\n

Agrupaci\u00f3n, agregaci\u00f3n<\/td>\nIntegrado con Views API<\/td>\nIntegrado en N1QL<\/td>\n<\/tr>\n
Almacenamiento en cach\u00e9<\/td>\nSistema de archivos<\/td>\nGrupo de b\u00faferes de \u00edndice<\/p>\n

Cach\u00e9 de datos<\/span><\/td>\n<\/tr>\n

Almacenamiento<\/td>\nTienda de sof\u00e1s<\/td>\nMotor de almacenamiento de plasma (5.0 y superior)<\/p>\n

\u00cdndice optimizado para memoria (4.5 y superior)<\/span><\/p>\n

ForestDB (comunidad)<\/span><\/td>\n<\/tr>\n

Disponibilidad<\/td>\nBasado en r\u00e9plicas<\/td>\n5.0: R\u00e9plicas<\/p>\n

4.x: \u00cdndices equivalentes<\/span><\/td>\n<\/tr>\n

Latencia de la consulta<\/p>\n

(Consultas simples)<\/span><\/td>\n

10 milisegundos a 100 milisegundos<\/td>\n5 milisegundos+<\/td>\n<\/tr>\n
Rendimiento de las consultas<\/p>\n

(Consultas simples)<\/span><\/td>\n

De 3.000 a 4.000 consultas por segundo<\/td>\n40.000 consultas por segundo<\/td>\n<\/tr>\n
Escalabilidad<\/td>\nModerado (escalado vinculado al servicio de datos)<\/td>\nAlta (escalado independiente de los servicios de \u00edndice y consulta: MDS)<\/td>\n<\/tr>\n
Aplicabilidad<\/td>\nAgregaciones, lo mejor de las agregaciones a gran escala para requisitos de latencia baja y moderada. Las operaciones map-reduce sobre los datos se realizan en segundo plano a medida que estos se modifican.<\/td>\nLo mejor para b\u00fasquedas basadas en atributos, escaneos de rangos, select-join-project-array complejos<\/p>\n

Operaciones. Admite agrupaci\u00f3n, agregaci\u00f3n y ordenaci\u00f3n: estas operaciones se realizan din\u00e1micamente como parte de la ejecuci\u00f3n de la consulta.<\/span><\/td>\n<\/tr>\n

Requisitos de la solicitud<\/td>\nInformar sobre m\u00e9tricas bien definidas<\/p>\n

Agregaciones a gran escala<\/span><\/p>\n

Sensible a la latencia<\/span><\/td>\n

B\u00fasqueda de claves secundarias<\/p>\n

Exploraciones de la gama<\/span><\/p>\n

Agregaciones operativas<\/span><\/p>\n

Consultas filtradas<\/span><\/p>\n

Consultas ad hoc con predicados complejos, uniones, agregaciones, b\u00fasqueda de aplicaciones, paginaci\u00f3n, actualizaciones basadas en claves secundarias.<\/span><\/td>\n<\/tr>\n

Espacial<\/td>\nCon vistas espaciales<\/td>\nNo directamente.<\/p>\n

https:\/\/dzone.com\/articles\/speed-up-spatial-search-in-couchbase-n1ql<\/a><\/span><\/td>\n<\/tr>\n

Coherencia<\/td>\nStale = UPDATE_AFTER<\/p>\n

Caducado = OK<\/p>\n

Anticuado = FALSE<\/td>\n

Sin l\u00edmites (antiguo = OK)<\/p>\n

AT_PLUS (lea sus propios escritos)<\/span><\/p>\n

REQUEST_PLUS (lectura despu\u00e9s de las actualizaciones del \u00edndice hasta now(). Stale = False).<\/td>\n<\/tr>\n

Herramientas<\/td>\nConsola web<\/td>\nConsola web, Workbench para desarrolladores, Supervisi\u00f3n de consultas, Perfiles de consultas, Visual explain, INFER.<\/td>\n<\/tr>\n<\/tbody>\n<\/table>\n<\/div>","protected":false},"excerpt":{"rendered":"

As Couchbase data platform evolved, services like N1QL and GSI Indexing handled the use cases Couchbase VIEWS used to handle and much more.\u00a0 It’s logical to ask the comparative question between them.\u00a0 Here is a table comparing both.\u00a0 This is […]<\/p>","protected":false},"author":55,"featured_media":4301,"comment_status":"open","ping_status":"open","sticky":false,"template":"","format":"standard","meta":{"_acf_changed":false,"inline_featured_image":false,"footnotes":""},"categories":[1814,1815,1821,1819,9417,1812],"tags":[1696,1248,1641],"ppma_author":[8929],"class_list":["post-4295","post","type-post","status-publish","format-standard","has-post-thumbnail","hentry","category-application-design","category-best-practices-and-tutorials","category-couchbase-architecture","category-data-modeling","category-performance","category-n1ql-query","tag-indexing","tag-mapreduce","tag-secondary-indexing"],"acf":[],"yoast_head":"\nComparing Couchbase Views with Couchbase N1QL & Indexing<\/title>\n<meta name=\"description\" content=\"The blog focuses on the table comparison between Couchbase Map-Reduce Views and Couchbase N1QL+GSI indexing. This is intended for developers and architects.\" \/>\n<meta name=\"robots\" content=\"index, follow, max-snippet:-1, max-image-preview:large, max-video-preview:-1\" \/>\n<link rel=\"canonical\" href=\"https:\/\/www.couchbase.com\/blog\/es\/comparing-couchbase-views-couchbase-n1ql-indexing\/\" \/>\n<meta property=\"og:locale\" content=\"es_MX\" \/>\n<meta property=\"og:type\" content=\"article\" \/>\n<meta property=\"og:title\" content=\"Comparing Couchbase Views with Couchbase N1QL & Indexing.\" \/>\n<meta property=\"og:description\" content=\"The blog focuses on the table comparison between Couchbase Map-Reduce Views and Couchbase N1QL+GSI indexing. This is intended for developers and architects.\" \/>\n<meta property=\"og:url\" content=\"https:\/\/www.couchbase.com\/blog\/es\/comparing-couchbase-views-couchbase-n1ql-indexing\/\" \/>\n<meta property=\"og:site_name\" content=\"The Couchbase Blog\" \/>\n<meta property=\"article:published_time\" content=\"2017-12-05T02:26:28+00:00\" \/>\n<meta property=\"article:modified_time\" content=\"2025-11-07T12:29:38+00:00\" \/>\n<meta property=\"og:image\" content=\"https:\/\/www.couchbase.com\/blog\/wp-content\/uploads\/sites\/1\/2017\/12\/questions.png\" \/>\n\t<meta property=\"og:image:width\" content=\"512\" \/>\n\t<meta property=\"og:image:height\" content=\"512\" \/>\n\t<meta property=\"og:image:type\" content=\"image\/png\" \/>\n<meta name=\"author\" content=\"Keshav Murthy\" \/>\n<meta name=\"twitter:card\" content=\"summary_large_image\" \/>\n<meta name=\"twitter:creator\" content=\"@rkeshavmurthy\" \/>\n<meta name=\"twitter:label1\" content=\"Written by\" \/>\n\t<meta name=\"twitter:data1\" content=\"Keshav Murthy\" \/>\n\t<meta name=\"twitter:label2\" content=\"Est. reading time\" \/>\n\t<meta name=\"twitter:data2\" content=\"4 minutos\" \/>\n<script type=\"application\/ld+json\" class=\"yoast-schema-graph\">{\"@context\":\"https:\/\/schema.org\",\"@graph\":[{\"@type\":\"Article\",\"@id\":\"https:\/\/www.couchbase.com\/blog\/comparing-couchbase-views-couchbase-n1ql-indexing\/#article\",\"isPartOf\":{\"@id\":\"https:\/\/www.couchbase.com\/blog\/comparing-couchbase-views-couchbase-n1ql-indexing\/\"},\"author\":{\"name\":\"Keshav Murthy\",\"@id\":\"https:\/\/www.couchbase.com\/blog\/#\/schema\/person\/c261644262bf98e146372fe647682636\"},\"headline\":\"Comparing Couchbase Views with Couchbase N1QL & Indexing.\",\"datePublished\":\"2017-12-05T02:26:28+00:00\",\"dateModified\":\"2025-11-07T12:29:38+00:00\",\"mainEntityOfPage\":{\"@id\":\"https:\/\/www.couchbase.com\/blog\/comparing-couchbase-views-couchbase-n1ql-indexing\/\"},\"wordCount\":652,\"commentCount\":0,\"publisher\":{\"@id\":\"https:\/\/www.couchbase.com\/blog\/#organization\"},\"image\":{\"@id\":\"https:\/\/www.couchbase.com\/blog\/comparing-couchbase-views-couchbase-n1ql-indexing\/#primaryimage\"},\"thumbnailUrl\":\"https:\/\/www.couchbase.com\/blog\/wp-content\/uploads\/sites\/1\/2017\/12\/questions.png\",\"keywords\":[\"Indexing\",\"MapReduce\",\"Secondary Indexing\"],\"articleSection\":[\"Application Design\",\"Best Practices and Tutorials\",\"Couchbase Architecture\",\"Data Modeling\",\"High Performance\",\"SQL++ \/ N1QL Query\"],\"inLanguage\":\"es\",\"potentialAction\":[{\"@type\":\"CommentAction\",\"name\":\"Comment\",\"target\":[\"https:\/\/www.couchbase.com\/blog\/comparing-couchbase-views-couchbase-n1ql-indexing\/#respond\"]}]},{\"@type\":\"WebPage\",\"@id\":\"https:\/\/www.couchbase.com\/blog\/comparing-couchbase-views-couchbase-n1ql-indexing\/\",\"url\":\"https:\/\/www.couchbase.com\/blog\/comparing-couchbase-views-couchbase-n1ql-indexing\/\",\"name\":\"Comparing Couchbase Views with Couchbase N1QL & Indexing\",\"isPartOf\":{\"@id\":\"https:\/\/www.couchbase.com\/blog\/#website\"},\"primaryImageOfPage\":{\"@id\":\"https:\/\/www.couchbase.com\/blog\/comparing-couchbase-views-couchbase-n1ql-indexing\/#primaryimage\"},\"image\":{\"@id\":\"https:\/\/www.couchbase.com\/blog\/comparing-couchbase-views-couchbase-n1ql-indexing\/#primaryimage\"},\"thumbnailUrl\":\"https:\/\/www.couchbase.com\/blog\/wp-content\/uploads\/sites\/1\/2017\/12\/questions.png\",\"datePublished\":\"2017-12-05T02:26:28+00:00\",\"dateModified\":\"2025-11-07T12:29:38+00:00\",\"description\":\"The blog focuses on the table comparison between Couchbase Map-Reduce Views and Couchbase N1QL+GSI indexing. 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