{"id":1915,"date":"2015-04-01T17:48:31","date_gmt":"2015-04-01T17:48:31","guid":{"rendered":"https:\/\/www.couchbase.com\/blog\/?p=1915"},"modified":"2023-06-27T22:59:03","modified_gmt":"2023-06-28T05:59:03","slug":"mongodb-rules-single-node-deployments","status":"publish","type":"post","link":"https:\/\/www.couchbase.com\/blog\/pt\/mongodb-rules-single-node-deployments\/","title":{"rendered":"MongoDB controla implanta\u00e7\u00f5es de n\u00f3 \u00fanico, mas n\u00e3o consegue dimensionar"},"content":{"rendered":"

O MongoDB publicou um refer\u00eancia<\/a> comparando o desempenho do MongoDB, do Apache Cassandra e do Couchbase Server em implanta\u00e7\u00f5es de n\u00f3 \u00fanico para combater a um<\/a> que publicamos comparando o desempenho do MongoDB e do Couchbase Server em implanta\u00e7\u00f5es de 9 n\u00f3s. O MongoDB tem um bom desempenho quando 1) est\u00e1 limitado a um \u00fanico n\u00f3, 2) n\u00e3o armazena muitos dados e 3) n\u00e3o oferece suporte a muitos usu\u00e1rios. Esse \u00e9 o ponto ideal para o MongoDB.<\/p>\n

O MongoDB aumentou a conscientiza\u00e7\u00e3o sobre os bancos de dados NoSQL ao facilitar para os desenvolvedores a cria\u00e7\u00e3o de uma prova de conceito ou de um pequeno aplicativo. No entanto, o MongoDB n\u00e3o consegue atender \u00e0s rigorosas demandas das implementa\u00e7\u00f5es de produ\u00e7\u00e3o. O Couchbase Server, por outro lado, se destaca quando implantado como um banco de dados distribu\u00eddo. Ele \u00e9 dimensionado com facilidade para armazenar mais dados, oferecer suporte a mais usu\u00e1rios e fornecer maior rendimento e menor lat\u00eancia de acesso aos dados.<\/p>\n

1) O benchmark de n\u00f3 \u00fanico n\u00e3o atende aos requisitos de escalabilidade<\/h3>\n

Se quiser ver o desempenho de um banco de dados com um pequeno conjunto de dados e poucos usu\u00e1rios, fa\u00e7a uma avalia\u00e7\u00e3o comparativa com uma implementa\u00e7\u00e3o de n\u00f3 \u00fanico. Se quiser ver como ser\u00e1 o desempenho em um ambiente de produ\u00e7\u00e3o com um grande conjunto de dados e muitos usu\u00e1rios, fa\u00e7a uma avalia\u00e7\u00e3o comparativa com uma implementa\u00e7\u00e3o em cluster.<\/p>\n

\u00c9 importante n\u00e3o apenas medir o desempenho em escala, mas tamb\u00e9m medir o desempenho enquanto atende aos requisitos da empresa. Por exemplo, alta disponibilidade.<\/p>\n

Por que o MongoDB n\u00e3o comparou o desempenho de implementa\u00e7\u00f5es distribu\u00eddas? Bem, \u00e9 dif\u00edcil para o MongoDB escalar al\u00e9m de um \u00fanico n\u00f3.<\/p>\n

Conforme observado pela InformationWeek (link<\/a>), o dimensionamento n\u00e3o \u00e9 linear. A adi\u00e7\u00e3o de n\u00f3s a um conjunto de r\u00e9plicas do MongoDB n\u00e3o aumentar\u00e1 o desempenho de grava\u00e7\u00e3o porque cada grava\u00e7\u00e3o ainda ser\u00e1 executada por um \u00fanico n\u00f3 - o n\u00f3 prim\u00e1rio. O mesmo se aplica aos shards do MongoDB: cada grava\u00e7\u00e3o ainda ser\u00e1 executada pelos n\u00f3s prim\u00e1rios. Se houver tr\u00eas shards com tr\u00eas n\u00f3s por shard, as grava\u00e7\u00f5es ser\u00e3o executadas pelos tr\u00eas n\u00f3s prim\u00e1rios.<\/p>\n

2) O benchmark aplicou um cen\u00e1rio de grava\u00e7\u00e3o diferente para o Couchbase Server - n\u00e3o \u00e9 uma compara\u00e7\u00e3o de igual para igual<\/h3>\n

O MongoDB executava uma opera\u00e7\u00e3o por grava\u00e7\u00e3o - a atualiza\u00e7\u00e3o. No entanto, o MongoDB, inadvertidamente, fez com que o Couchbase Server executasse duas opera\u00e7\u00f5es por grava\u00e7\u00e3o: uma leitura e uma atualiza\u00e7\u00e3o. Isso limitou o desempenho de grava\u00e7\u00e3o do Couchbase Server.<\/p>\n

O MongoDB (com o WiredTiger) e o Couchbase Server utilizam o bloqueio em n\u00edvel de documento. Se dois clientes atualizarem o mesmo documento ao mesmo tempo, um deles falhar\u00e1 e ter\u00e1 de tentar novamente a atualiza\u00e7\u00e3o. Esse \u00e9 o caso do MongoDB e do Couchbase Server. Esse foi o cen\u00e1rio de grava\u00e7\u00e3o para o MongoDB nesse benchmark, mas n\u00e3o para o Couchbase Server.<\/p>\n

Outro cen\u00e1rio de grava\u00e7\u00e3o \u00e9 quando voc\u00ea precisa garantir que um cliente n\u00e3o possa atualizar um documento se ele tiver sido atualizado primeiro por um cliente diferente. Nesse cen\u00e1rio de grava\u00e7\u00e3o, o Couchbase Server oferece suporte \u00e0 compara\u00e7\u00e3o e troca, enquanto o MongoDB recomenda a op\u00e7\u00e3o \"Atualizar documento se atual\" padr\u00e3o<\/a>. Esse era o cen\u00e1rio de grava\u00e7\u00e3o do Couchbase Server, mas n\u00e3o do MongoDB.<\/p>\n

Por que o MongoDB faria com que o Couchbase Server executasse a compara\u00e7\u00e3o e a troca, mas n\u00e3o implementaria seu pr\u00f3prio padr\u00e3o \"Atualizar documento se atual\"?<\/p>\n

3) O benchmark utilizou um cliente Couchbase desatualizado, em vez do cliente atual<\/h3>\n

O MongoDB optou por usar uma biblioteca de cliente desatualizada lan\u00e7ada em 2013 para o Couchbase Server, o que limitou o desempenho do Couchbase Server. Lan\u00e7amos uma nova biblioteca de clientes em setembro do ano passado, baseada em Netty e RxJava, seguida de vers\u00f5es menores em fevereiro e mar\u00e7o.<\/p>\n

Por que o MongoDB faria um benchmark do Couchbase Server com uma biblioteca de cliente desatualizada, mas faria um benchmark de si mesmo com sua biblioteca de cliente mais recente?<\/p>\n

4) Durabilidade de n\u00f3 \u00fanico versus durabilidade de banco de dados distribu\u00eddo<\/h3>\n

O objetivo da durabilidade \u00e9 garantir que os dados n\u00e3o sejam perdidos quando um servidor falhar. Nesse benchmark, como ele foi realizado com implanta\u00e7\u00f5es de n\u00f3 \u00fanico, os dados s\u00f3 podem ser dur\u00e1veis quando s\u00e3o gravados no disco. Essa \u00e9 a mesma limita\u00e7\u00e3o dos bancos de dados relacionais tradicionais.<\/p>\n

Atualmente, os bancos de dados distribu\u00eddos contam com uma abordagem moderna de durabilidade que distribui o risco de perda de dados - eles replicam os dados em v\u00e1rios n\u00f3s. O Couchbase Server \u00e9 \u00fanico no sentido de que, embora grave no disco como um banco de dados convencional, ele tamb\u00e9m aproveita a replica\u00e7\u00e3o mais r\u00e1pida de mem\u00f3ria para mem\u00f3ria entre os n\u00f3s. Os dados n\u00e3o s\u00e3o apenas dur\u00e1veis, mas tamb\u00e9m altamente dispon\u00edveis. Eles podem ser replicados para n\u00f3s em diferentes servidores, diferentes racks ou diferentes data centers.<\/p>\n

Dito isso, se o MongoDB tivesse usado a biblioteca cliente mais recente, o desempenho de grava\u00e7\u00e3o do Couchbase Server teria sido pelo menos 10 vezes maior. A biblioteca cliente de dois anos atr\u00e1s (1.1.8) esperava um m\u00ednimo de 100 ms antes de verificar se a grava\u00e7\u00e3o tinha sido gravada no disco. Em uma vers\u00e3o posterior (1.4.x), 10 ms. Na vers\u00e3o mais recente (2.x), 10\u00b5s. \u00c9 por isso que voc\u00ea deve sempre fazer benchmark de bancos de dados com suas bibliotecas de clientes mais recentes, e n\u00e3o com as de dois anos atr\u00e1s.<\/p>\n

Implanta\u00e7\u00f5es de n\u00f3 \u00fanico de regras do MongoDB<\/h3>\n

O MongoDB \u00e9 adequado para uma prova de conceito ou um aplicativo pequeno que tenha um conjunto de dados pequeno e poucos usu\u00e1rios. O Couchbase Server \u00e9 mais adequado para aplicativos com mais dados, mais usu\u00e1rios e requisitos de maior rendimento \/ menor lat\u00eancia - aqueles que se beneficiam de uma implementa\u00e7\u00e3o distribu\u00edda. De fato, o Couchbase Server \u00e9 frequentemente escolhido para alimentar aplicativos de miss\u00e3o cr\u00edtica - pequenos ou grandes, de consumo ou empresariais, sociais ou de jogos - em que os bancos de dados relacionais tradicionais n\u00e3o conseguem fornecer a escalabilidade ou o desempenho necess\u00e1rios.<\/p>\n

Discutir sobre Not\u00edcias Hacker<\/a><\/strong><\/p>\n

Para sua informa\u00e7\u00e3o - N\u00f3s aferido<\/a> MongoDB e Couchbase Server com implementa\u00e7\u00f5es de 9 n\u00f3s.<\/p>","protected":false},"excerpt":{"rendered":"

MongoDB published an independent benchmark comparing the performance of MongoDB, Apache Cassandra, and Couchbase Server in single node deployments to counter the one we published comparing the performance of MongoDB and Couchbase Server in 9-node deployments. MongoDB performs well when […]<\/p>","protected":false},"author":13,"featured_media":13873,"comment_status":"open","ping_status":"open","sticky":false,"template":"","format":"standard","meta":{"_acf_changed":false,"inline_featured_image":false,"footnotes":""},"categories":[1],"tags":[],"ppma_author":[9000],"class_list":["post-1915","post","type-post","status-publish","format-standard","has-post-thumbnail","hentry","category-uncategorized"],"acf":[],"yoast_head":"\nMongoDB Rules Single Node Deployments, Fails to Scale - 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\/pt\/mongodb-rules-single-node-deployments\/\" \/>\n<meta property=\"og:locale\" content=\"pt_BR\" \/>\n<meta property=\"og:type\" content=\"article\" \/>\n<meta property=\"og:title\" content=\"MongoDB Rules Single Node Deployments, Fails to Scale\" \/>\n<meta property=\"og:description\" content=\"MongoDB published an independent benchmark comparing the performance of MongoDB, Apache Cassandra, and Couchbase Server in single node deployments to counter the one we published comparing the performance of MongoDB and Couchbase Server in 9-node deployments. 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