{"id":135788,"date":"2025-06-04T09:05:06","date_gmt":"2025-06-04T07:05:08","guid":{"rendered":"https:\/\/prohoster.info\/blog\/novosti-interneta\/sravnenie-proizvoditelnosti-subd-valkey-i-redis"},"modified":"2025-06-04T09:05:06","modified_gmt":"2025-06-04T07:05:08","slug":"sravnenie-proizvoditelnosti-subd-valkey-i-redis","status":"publish","type":"post","link":"https:\/\/prohoster.info\/es\/blog\/news\/sravnenie-proizvoditelnosti-subd-valkey-i-redis","title":{"rendered":"Comparativa de rendimiento entre las bases de datos Valkey y Redis","gt_translate_keys":[{"key":"rendered","format":"text"}]},"content":{"rendered":"<p>Se presentan los resultados de las pruebas de las \u00faltimas versiones de las bases de datos Redis 8.0 y Valkey 8.1, en las que se han anunciado significativas optimizaciones de rendimiento. En todas las pruebas realizadas, el fork desarrollado por la comunidad super\u00f3 el proyecto original, principalmente gracias a la implementaci\u00f3n en Valkey de un nuevo mecanismo para el procesamiento multihilo de entrada\/salida en modo as\u00edncrono, proporcionado al proyecto por Amazon.    <\/p>\n<p>En el entorno de prueba AWS Graviton4 c8g.2xlarge con 8 VCPU, Valkey 8.1.1 logr\u00f3 un rendimiento de 999.8 mil solicitudes SET por segundo, mientras que en Redis 8.0 se alcanz\u00f3 un nivel de 729.4 mil solicitudes por segundo. En general, la capacidad de Valkey fue superior a la de Redis en un 37% para operaciones SET y en un 16% para GET. Adem\u00e1s, en comparaci\u00f3n con Redis, el proyecto Valkey mostr\u00f3 una disminuci\u00f3n de la latencia en el procesamiento de solicitudes del 30% para operaciones SET y del 60% para operaciones GET.    <center><img decoding=\"async\" alt=\"Comparativa de rendimiento entre las bases de datos Valkey y Redis\" src=\"\/wp-content\/uploads\/2025\/06\/512bd8dc9f4e4cc2562b59db68823b07.png\" style=\"display:block;margin: 0 auto;\" \/><\/center>    <\/p>\n<p>Se realiz\u00f3 un an\u00e1lisis separado del cambio en el ancho de banda y la latencia en funci\u00f3n del n\u00famero de procesadores en ejecuci\u00f3n simult\u00e1nea en modo de procesamiento multihilo de entrada\/salida. Hasta 3 hilos, Valkey y Redis muestran resultados aproximadamente iguales, pero luego Valkey se adelanta. Con 6 hilos en un sistema con 8 VCPU, el rendimiento de Valkey fue de 678 mil solicitudes SET por segundo, mientras que Redis alcanz\u00f3 las 563 mil solicitudes por segundo con un l\u00edmite de 256 conexiones simult\u00e1neas. Al aumentar las conexiones a 400, el rendimiento de Valkey aument\u00f3 a 832 mil solicitudes SET por segundo.    <center><img decoding=\"async\" alt=\"Comparativa de rendimiento entre las bases de datos Valkey y Redis\" src=\"\/wp-content\/uploads\/2025\/06\/b81d26ec066d0af829859a11236ae2a6.png\" style=\"display:block;margin: 0 auto;\" \/><\/center>    <\/p>\n<p>Despu\u00e9s de optimizar el manejo de interrupciones en el sistema para reducir el n\u00famero de cambios de contexto, Valkey logr\u00f3 elevar su rendimiento a 999.8 mil solicitudes SET por segundo. La esencia de la optimizaci\u00f3n consisti\u00f3 en asignar 2 VCPU para el manejo de interrupciones y vincular las 6 VCPU restantes a los hilos de procesamiento de entrada\/salida de Valkey y Redis, para evitar la migraci\u00f3n de controladores entre CPU.       sudo ethtool -L ens34 combined 2 # limitamos a 2 el n\u00famero de controladores IRQ     grep ens34 \/proc\/interrupts # vemos qu\u00e9 controladores est\u00e1n involucrados (99 y 100)     echo 1 | sudo tee \/proc\/irq\/99\/smp_affinity # vinculamos el controlador 99 al n\u00facleo 1     echo 2 | sudo tee \/proc\/irq\/100\/smp_affinity # vinculamos el controlador 100 al n\u00facleo 2       # Ejecutamos la base de datos (para Redis cambiar valkey\/valkey:8.1.1 a redis:8.0) vinculando el contenedor a los n\u00facleos de CPU 2-7     docker run --network='host' --rm \\       --cpuset-cpus='2-7' valkey\/valkey:8.1.1 \\       --save '' --appendonly no --io-threads 6 \\       --protected-mode no --maxmemory 10gb        <\/p>\n<p>Para probar el rendimiento se utiliz\u00f3 el comando:       docker run --network='host' --rm --cpuset-cpus='2-7' \\        valkey\/valkey:8.0.1 valkey-benchmark \\        -h 172.31.4.92 -p 6379 -t SET,GET -n 100000000 -c 256 \\        -r 3000000 --threads 6 -d 1024<br \/>\n<br \/>Fuente: <a content=\"nofollow\" rel=\"nofollow\" href=\"https:\/\/www.opennet.ru\/opennews\/art.shtml?num=63335\">opennet.ru<\/a> <\/p>","protected":false,"gt_translate_keys":[{"key":"rendered","format":"html"}]},"excerpt":{"rendered":"<p>\u041f\u0440\u0435\u0434\u0441\u0442\u0430\u0432\u043b\u0435\u043d\u044b \u0440\u0435\u0437\u0443\u043b\u044c\u0442\u0430\u0442\u044b \u0442\u0435\u0441\u0442\u0438\u0440\u043e\u0432\u0430\u043d\u0438\u044f \u0441\u0432\u0435\u0436\u0438\u0445 \u0432\u044b\u043f\u0443\u0441\u043a\u043e\u0432 \u0421\u0423\u0411\u0414 Redis 8.0 \u0438 Valkey 8.1, \u0432 \u043a\u043e\u0442\u043e\u0440\u044b\u0445 \u0431\u044b\u043b\u0438 \u0437\u0430\u044f\u0432\u043b\u0435\u043d\u044b \u0437\u043d\u0430\u0447\u0438\u0442\u0435\u043b\u044c\u043d\u044b\u0435 \u043e\u043f\u0442\u0438\u043c\u0438\u0437\u0430\u0446\u0438\u0438 \u043f\u0440\u043e\u0438\u0437\u0432\u043e\u0434\u0438\u0442\u0435\u043b\u044c\u043d\u043e\u0441\u0442\u0438. \u0412\u043e \u0432\u0441\u0435\u0445 \u043f\u0440\u043e\u0432\u0435\u0434\u0451\u043d\u043d\u044b\u0445 \u0442\u0435\u0441\u0442\u0430\u0445 \u0440\u0430\u0437\u0432\u0438\u0432\u0430\u0435\u043c\u044b\u0439 \u0441\u043e\u043e\u0431\u0449\u0435\u0441\u0442\u0432\u043e\u043c \u0444\u043e\u0440\u043a \u043e\u0431\u043e\u0433\u043d\u0430\u043b \u043e\u0440\u0438\u0433\u0438\u043d\u0430\u043b\u044c\u043d\u044b\u0439 \u043f\u0440\u043e\u0435\u043a\u0442, \u0432 \u043e\u0441\u043d\u043e\u0432\u043d\u043e\u043c \u0431\u043b\u0430\u0433\u043e\u0434\u0430\u0440\u044f \u0432\u043d\u0435\u0434\u0440\u0435\u043d\u0438\u044e \u0432 Valkey \u043d\u043e\u0432\u043e\u0433\u043e \u043c\u0435\u0445\u0430\u043d\u0438\u0437\u043c\u0430 \u0434\u043b\u044f \u043c\u043d\u043e\u0433\u043e\u043f\u043e\u0442\u043e\u0447\u043d\u043e\u0439 \u043e\u0431\u0440\u0430\u0431\u043e\u0442\u043a\u0438 \u0432\u0432\u043e\u0434\u0430\/\u0432\u044b\u0432\u043e\u0434\u0430 \u0432 \u0430\u0441\u0438\u043d\u0445\u0440\u043e\u043d\u043d\u043e\u043c \u0440\u0435\u0436\u0438\u043c\u0435, \u043f\u0435\u0440\u0435\u0434\u0430\u043d\u043d\u043e\u0433\u043e \u043f\u0440\u043e\u0435\u043a\u0442\u0443 \u043a\u043e\u043c\u043f\u0430\u043d\u0438\u0435\u0439 Amazon. \u0412 \u0442\u0435\u0441\u0442\u043e\u0432\u043e\u043c \u043e\u043a\u0440\u0443\u0436\u0435\u043d\u0438\u0438 AWS Graviton4 c8g.2xlarge \u0441 8 [&hellip;]<\/p>\n","protected":false,"gt_translate_keys":[{"key":"rendered","format":"html"}]},"author":1,"featured_media":135789,"comment_status":"open","ping_status":"open","sticky":false,"template":"","format":"standard","meta":{"footnotes":""},"categories":[702],"tags":[],"class_list":["post-135788","post","type-post","status-publish","format-standard","has-post-thumbnail","hentry","category-news"],"aioseo_notices":[],"aioseo_head":"\n\t\t<!-- All in One SEO 5.0.2 - aioseo.com -->\n\t<meta name=\"description\" content=\"\u041f\u0440\u0435\u0434\u0441\u0442\u0430\u0432\u043b\u0435\u043d\u044b \u0440\u0435\u0437\u0443\u043b\u044c\u0442\u0430\u0442\u044b \u0442\u0435\u0441\u0442\u0438\u0440\u043e\u0432\u0430\u043d\u0438\u044f \u0441\u0432\u0435\u0436\u0438\u0445 \u0432\u044b\u043f\u0443\u0441\u043a\u043e\u0432 \u0421\u0423\u0411\u0414 Redis 8.0 \u0438 Valkey 8.1, \u0432 \u043a\u043e\u0442\u043e\u0440\u044b\u0445 \u0431\u044b\u043b\u0438 \u0437\u0430\u044f\u0432\u043b\u0435\u043d\u044b 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