{"id":6043,"date":"2018-11-27T16:36:51","date_gmt":"2018-11-28T00:36:51","guid":{"rendered":"https:\/\/www.couchbase.com\/blog\/?p=6043"},"modified":"2025-06-13T18:45:03","modified_gmt":"2025-06-14T01:45:03","slug":"connecting-to-couchbase-via-odbc","status":"publish","type":"post","link":"https:\/\/www.couchbase.com\/blog\/es\/connecting-to-couchbase-via-odbc\/","title":{"rendered":"Conexi\u00f3n a Couchbase mediante ODBC"},"content":{"rendered":"

An\u00e1lisis de Couchbase<\/span><\/h2>\n

Couchbase Data Platform ahora soporta cargas de trabajo h\u00edbridas de procesamiento transaccional\/anal\u00edtico (HTAP). Adem\u00e1s, nuestro motor de consultas de procesamiento paralelo masivo (MPP) permite a los usuarios ejecutar consultas anal\u00edticas ad hoc que ofrecen informaci\u00f3n m\u00e1s r\u00e1pida sin afectar al rendimiento.<\/span><\/p>\n

Couchbase Analytics reduce el tiempo necesario para obtener informaci\u00f3n sobre los datos operativos gracias a estas funciones clave:<\/span><\/p>\n

Ingesta r\u00e1pida:<\/b> Disponga de los datos para su procesamiento anal\u00edtico en milisegundos<\/span><\/p>\n

NoETL para NoSQL:<\/b> Procese datos JSON en su forma natural sin ninguna transformaci\u00f3n ni dise\u00f1o de esquemas<\/span><\/p>\n

Aislamiento de la carga de trabajo:<\/b> Ejecute consultas ad hoc sin afectar al rendimiento de la aplicaci\u00f3n<\/span><\/p>\n

Consultas ad hoc:<\/b> Los usuarios empresariales pueden explorar los datos y realizar uniones y agregaciones complejas.<\/span><\/p>\n

N1QL para an\u00e1lisis:<\/b> Es la primera implementaci\u00f3n comercial del lenguaje SQL++ para consultar datos JSON semiestructurados y sin esquema.<\/span><\/p>\n

Muchas de las herramientas de visualizaci\u00f3n m\u00e1s populares no soportan de forma nativa la integraci\u00f3n JSON, pero s\u00ed la conectividad a trav\u00e9s de tecnolog\u00edas est\u00e1ndar como JDBC, ODBC o ADO.NET. Con los drivers de CData, cualquier herramienta de BI que soporte conectividad basada en SQL (como Tableau, Power BI, MicroStrategy, Excel, etc.) podr\u00e1 visualizar los datos almacenados en Couchbase Analytics.<\/span><\/p>\n

Como ejemplo, adjunto una captura de pantalla de una visualizaci\u00f3n en Tableau de datos procedentes de Couchbase Analytics.<\/span><\/p>\n

\"\"<\/p>\n

Controladores CData para Couchbase<\/span><\/h2>\n

Los drivers CData para Couchbase proporcionan una interfaz SQL para fuentes de datos NoSQL, como Couchbase Analytics. Mediante innovadoras t\u00e9cnicas de aplanamiento y un potente motor SQL integrado, los controladores CData traducen sin problemas las consultas SQL a SQL++, aprovechando las capacidades del lado del servidor de Couchbase Analytics para proporcionar datos en tiempo real para BI y an\u00e1lisis. Esto es especialmente cr\u00edtico para las herramientas que generan consultas SQL internamente para solicitar datos de las fuentes de datos conectadas. Por ejemplo, dado un documento de muestra de \"coches\", se puede esperar que Tableau genere una consulta SQL. Esa consulta SQL ser\u00e1 traducida a SQL++ por el controlador CData.<\/span><\/p>\n

Modelo de documento sobre veh\u00edculos<\/span><\/p>\n

{  \r\n   \"cars\":{  \r\n      \"EngineTemp\":214,\r\n      \"TPMS\":\"ON\",\r\n      \"TirePressure\":[  \r\n         33,\r\n         36,\r\n         34,\r\n         34\r\n      ],\r\n      \"Indicators\":{  \r\n         \"WindshieldWiper\":\"OFF\",\r\n         \"Headlamp\":\"ON\",\r\n         \"BrakePedal\":\"OFF\",\r\n         \"Ignition\":\"OFF\"\r\n      },\r\n      \"ABS\":\"OFF\",\r\n      \"Location\":{  \r\n         \"lat\":34.25320048276987,\r\n         \"long\":-117.33252478191595\r\n      },\r\n      \"Fuel\":88,\r\n      \"TransmissionGear\":2,\r\n      \"AcceleratorPedalPosition\":15,\r\n      \"VIN\":\"RU2S4T1TR1TR30UR\",\r\n      \"ModelType\":\"Medium SUV\",\r\n      \"OutsideTemp\":150,\r\n      \"Speed\":25,\r\n      \"EngineOil\":36\r\n   }\r\n}\r\n<\/pre>\n
Ejemplo de consulta SQL<\/span><\/h4>\n
SELECT ModelType, COUNT(*) AS Total FROM cars GROUP BY ModelType;<\/pre>\n
El controlador traduce la consulta SQL a SQL++.<\/span><\/p>\n
Ejemplo de consulta SQL<\/span><\/h4>\n
SELECT `cars`.`ModelType`, COUNT(*)  AS `total` FROM `cars` GROUP BY `cars`.`ModelType`;<\/pre>\n
Aunque las diferencias entre las consultas SQL y SQL++ pueden parecer peque\u00f1as, son exageradas cuando se trabaja con herramientas que generan consultas SQL basadas en una interfaz gr\u00e1fica de usuario (como Tableau). Dado que el usuario no tiene control sobre la consulta generada, estas diferencias significan que una traducci\u00f3n de SQL a SQL++ no s\u00f3lo es cr\u00edtica, sino necesaria para realizar BI, an\u00e1lisis e informes en herramientas basadas en SQL. Dado que los controladores CData traducen a SQL++ puro, pueden aprovechar las potentes capacidades de procesamiento del lado del servidor del servicio Analytics.<\/span><\/p>\n
Interfaz de SQL a SQL<\/span><\/h2>\n
\u00bfC\u00f3mo crean los controladores CData la interfaz SQL para los datos JSON? Para explicarlo, nos referiremos al documento de ejemplo anterior.<\/span><\/p>\n
Aplanamiento de objetos<\/span><\/h3>\n
Los controladores CData aplanan los objetos utilizando una notaci\u00f3n de puntos para representar la estructura jer\u00e1rquica original. Por ejemplo, para acceder al <\/span>Limpiaparabrisas <\/span>del objeto Indicador, se referir\u00eda a la columna <\/span>coches.Indicador.Limpiaparabrisas<\/span>. Muchas herramientas no permiten puntos en los nombres de columna, as\u00ed que cuando sea necesario, los controladores CData crear\u00e1n definiciones de esquema temporales en memoria para permitir la conectividad desde dichas herramientas. A continuaci\u00f3n ver\u00e1 un ejemplo de consulta SQL, la consulta SQL++ correspondiente, y los resultados de la consulta.<\/span><\/p>\n
SQL: SELECT Indicators_WindshieldWiper FROM cars;\r\nSQL++: SELECT `cars`.`Indicators`.`WindshieldWiper` FROM `cars`;<\/pre>\n
Aplanamiento de matrices<\/span><\/h3>\n
Los drivers de CData aplanan los arrays dentro de los documentos JSON usando indexaci\u00f3n basada en 0, similar a lo que se ve en otros lenguajes de programaci\u00f3n. Por ejemplo, para acceder a las entradas 1\u00aa y 2\u00aa de la matriz TirePressure, se har\u00eda referencia a las columnas<\/span> coches.TirePressure.0<\/span> y <\/span>coches.presionneumaticos.1<\/span>. A continuaci\u00f3n ver\u00e1s un ejemplo de consulta SQL, la consulta SQL++ correspondiente y los resultados de la consulta.<\/span><\/p>\n
SQL: SELECT TirePressure_0, TirePressure_1 FROM cars;\r\nSQL++: SELECT `cars`.`TirePressure`[0], `cars`.`TirePressure`[1] FROM `cars`;<\/pre>\n
A medida que el servicio Analytics y las interfaces SQL++ crezcan y evolucionen, tambi\u00e9n lo har\u00e1n los controladores CData, implementando nuevas funciones de consulta a medida que se a\u00f1adan y continuando el aprovechamiento de las potentes capacidades de procesamiento de datos del servicio Analytics para permitir a los usuarios de Couchbase trabajar, visualizar e informar sobre sus datos de forma r\u00e1pida y sencilla.<\/span><\/p>\n
Pruebe Couchbase 6.0 y CData hoy mismo<\/span><\/h2>\n
Descargar la nueva versi\u00f3n de Couchbase<\/span><\/a> y <\/span>los \u00faltimos controladores CData<\/span><\/a> para empezar a trabajar con datos de Couchbase en las herramientas y aplicaciones compatibles con SQL que ya utiliza. Esperamos sus comentarios sobre el <\/span>Foros de Couchbase<\/span><\/a>.<\/span><\/p>\n
Agradecimientos<\/span><\/h2>\n
Esta entrada de blog es una colaboraci\u00f3n entre Couchbase y CData. Muchas gracias a <\/span>Jerod Johnson<\/span><\/a>Evangelista tecnol\u00f3gico de CData Software, por su contribuci\u00f3n a esta entrada del blog. \u00a0<\/span><\/p>","protected":false},"excerpt":{"rendered":"
Couchbase Analytics Couchbase Data Platform now supports hybrid transaction\/analytical processing (HTAP) workloads. Plus, our massively parallel processing (MPP) query engine lets users run ad-hoc analytical queries that deliver faster insights without impacting performance. Couchbase Analytics reduces the time to insight […]<\/p>","protected":false},"author":559,"featured_media":13873,"comment_status":"open","ping_status":"open","sticky":false,"template":"","format":"standard","meta":{"_acf_changed":false,"inline_featured_image":false,"footnotes":""},"categories":[2294,1821,1816,1812],"tags":[1829,2250,1725],"ppma_author":[9052],"class_list":["post-6043","post","type-post","status-publish","format-standard","has-post-thumbnail","hentry","category-analytics","category-couchbase-architecture","category-couchbase-server","category-n1ql-query","tag-bi","tag-data-visualization","tag-nosql-database"],"acf":[],"yoast_head":"\nConnecting to Couchbase via ODBC - The Couchbase Blog<\/title>\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\/connecting-to-couchbase-via-odbc\/\" \/>\n<meta property=\"og:locale\" content=\"es_MX\" \/>\n<meta property=\"og:type\" content=\"article\" \/>\n<meta property=\"og:title\" content=\"Connecting to Couchbase via ODBC\" \/>\n<meta property=\"og:description\" content=\"Couchbase Analytics Couchbase Data Platform now supports hybrid transaction\/analytical processing (HTAP) workloads. 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