{"id":6760,"date":"2019-05-26T23:50:29","date_gmt":"2019-05-27T06:50:29","guid":{"rendered":"https:\/\/www.couchbase.com\/blog\/?p=6760"},"modified":"2025-06-13T17:32:38","modified_gmt":"2025-06-14T00:32:38","slug":"the-unreasonable-effectiveness-of-sql-in-nosql-databases","status":"publish","type":"post","link":"https:\/\/www.couchbase.com\/blog\/pt\/the-unreasonable-effectiveness-of-sql-in-nosql-databases\/","title":{"rendered":"A efic\u00e1cia irracional do SQL em bancos de dados NoSQL"},"content":{"rendered":"

Os aplicativos de neg\u00f3cios t\u00eam requisitos: receber pedidos de clientes, entregar pedidos de clientes, rastrear remessas, gerar relat\u00f3rios de invent\u00e1rio, relat\u00f3rios comerciais de fim de dia\/m\u00eas\/trimestre, gerar pain\u00e9is de neg\u00f3cios e muito mais. Esses requisitos evoluem lentamente. Eles permanecem mesmo quando voc\u00ea escolhe um Banco de dados NoSQL<\/a>.<\/span><\/p>\n

Nos bancos de dados NoSQL, os desafios s\u00e3o enfrentados por uma s\u00e9rie de tecnologias e solu\u00e7\u00f5es alternativas. Aqui est\u00e3o algumas delas:<\/span><\/p>\n

    \n
  1. Copiar os dados com uma chave diferente para facilitar as digitaliza\u00e7\u00f5es.<\/span><\/li>\n
  2. Obter todos os dados necess\u00e1rios para o aplicativo e, em seguida, gerar relat\u00f3rios<\/li>\n
  3. Carregar os dados em bancos de dados relacionais para gerar o relat\u00f3rio.<\/span><\/li>\n
  4. Os produtos oferecem solu\u00e7\u00f5es alternativas com <\/span>visualiza\u00e7\u00f5es de redu\u00e7\u00e3o de mapas<\/span><\/a>, <\/span>APIs<\/span><\/a>etc.<\/span><\/li>\n
  5. Por fim, o pr\u00f3prio SQL foi <\/span>injustificadamente eficaz<\/span><\/a> para dados estruturados e semiestruturados. Os bancos de dados NoSQL, como <\/span>Couchbase<\/span><\/a>, <\/span>Cassandra<\/span><\/a>, <\/span>CosmosDB<\/span><\/a> estenderam o SQL para JSON e modelo de dados de coluna ampla.<\/span><\/li>\n<\/ol>\n

    O NoSQL evoluiu de \"NO SQL\" para Not Only SQL. Se voc\u00ea estiver interessado em alguns dos antecedentes evolutivos combinados com um hist\u00f3rico da evolu\u00e7\u00e3o do SQL para dar suporte a dados semiestruturados, sugiro as seguintes entrevistas.<\/p>\n

      \n
    1. Entrevista de Ravi Mayuram com Don Chamberlin [2017]:\u00a0 https:\/\/youtu.be\/-U_UjqnhMBI?t=3492<\/a><\/li>\n
    2. Um painel de discuss\u00e3o entre Ravi Mayuram, Don Chamberlin e o Prof. Mike Carey [2018]:\u00a0 https:\/\/www.youtube.com\/watch?v=LAlDe1w7wxc<\/a><\/li>\n<\/ol>\n

      Muitos bancos de dados NoSQL alegam ter \"suporte a SQL\". O Padr\u00e3o SQL<\/span><\/a> \u00e9 amplo e profundo, coberto de <\/span>nove livros volumosos<\/span><\/a>. Ningu\u00e9m, nem <\/span>Or\u00e1culo<\/span><\/a> nem <\/span>SQL Server<\/span><\/a>O NoSQL, apesar de d\u00e9cadas de trabalho, suporta tudo o que est\u00e1 no padr\u00e3o. Portanto, os bancos de dados NoSQL t\u00eam um longo caminho a percorrer para se atualizarem. Portanto, vale a pena fazer uma avalia\u00e7\u00e3o detalhada do suporte a SQL.\u00a0<\/span><\/p>\n

      Aqui est\u00e3o os crit\u00e9rios que voc\u00ea deve usar para avaliar o suporte a SQL em bancos de dados NoSQL.<\/p>\n

        \n
      1. Suporte \u00e0 linguagem: Quais declara\u00e7\u00f5es, tipos de dados, opera\u00e7\u00f5es (jun\u00e7\u00f5es, agrupamento, agrega\u00e7\u00e3o, janelas, pagina\u00e7\u00e3o, etc.)<\/li>\n
      2. Suporte \u00e0 indexa\u00e7\u00e3o: Os \u00edndices s\u00e3o essenciais para o desempenho, especialmente nas cargas de trabalho de aplicativos interativos.<\/li>\n
      3. Otimizador: A reescrita de consultas, a escolha do caminho de acesso correto e a cria\u00e7\u00e3o do caminho ideal de execu\u00e7\u00e3o de consultas \u00e9 o que torna o SQL uma 4GL bem-sucedida. Alguns t\u00eam um otimizador baseado em regras, outros t\u00eam um otimizador baseado em custos e outros t\u00eam ambos. \u00c9 fundamental avaliar a qualidade do otimizador. Os benchmarks t\u00edpicos (TPC-C, TPC-DS, YCSB, YCSB-JSON) n\u00e3o o ajudar\u00e3o aqui.<\/li>\n
      4. Como diz o ditado: \"H\u00e1 tr\u00eas coisas importantes nos bancos de dados: desempenho, desempenho e desempenho\". \u00c9 importante medir o desempenho de sua carga de trabalho.\u00a0\u00a0YCSB<\/a>\u00a0e a extens\u00e3o\u00a0YCSB-JSON<\/a>\u00a0facilitar\u00e1 essa avalia\u00e7\u00e3o.<\/li>\n
      5. SDKs: SDKs avan\u00e7ados e suporte a idiomas aceleram seu desenvolvimento.<\/li>\n
      6. \u00a0Suporte de ferramentas de BI: Para a an\u00e1lise de grandes volumes de dados, \u00e9 importante o suporte das ferramentas de BI, geralmente por meio de drivers de conectividade de banco de dados padr\u00e3o.<\/li>\n<\/ol>\n

        Neste artigo, vou comparar e contrastar o suporte \u00e0 linguagem SQL no Cassandra, CosmosDB, Couchbase e MongoDB por meio de suas respectivas implementa\u00e7\u00f5es. Com certeza, o MongoDB n\u00e3o oferece suporte a SQL, mas tem alguns comandos comparativos<\/a>.<\/span><\/p>\n

        Dividi a an\u00e1lise em v\u00e1rias se\u00e7\u00f5es. A formata\u00e7\u00e3o do WordPress torna essas tabelas muito grandes. Aqui est\u00e1 uma vers\u00e3o em PDF que \u00e9 compacta e f\u00e1cil de ler. [Clique na imagem para visualizar o PDF].<\/p>\n

        \"\"<\/a>

        Resumo do suporte a SQL no Cassandra, CosmosDB, Couchbase e MongoDB.<\/p><\/div>\n

         <\/p>\n

         <\/p>\n

         <\/p>\n

         <\/p>\n

         <\/p>\n

        Abordagem de suporte ao SQL: \u00a0<\/b><\/p>\n\n\n\n\n\n\n\n
        SQL<\/span><\/td>\n O SQL \u00e9 uma linguagem declarativa, com as opera\u00e7\u00f5es select-join-project servindo como base.<\/span><\/td>\n<\/tr>\n
        Cassandra<\/span><\/td>\nCQL: Linguagem inspirada em SQL para o Cassandra.<\/span><\/td>\n<\/tr>\n
        CosmosDB<\/span><\/td>\nOferece suporte a SQL juntamente com a API do MongoDB, Gremlin (para o gr\u00e1fico), etc. Suporte simples a select-from-where-order-by. \u00a0<\/span><\/td>\n<\/tr>\n
        Couchbase<\/span><\/td>\nN1QL: SQL para JSON.\u00a0<\/span><\/p>\n

        O Couchbase tem duas implementa\u00e7\u00f5es do N1QL: servi\u00e7o de consulta e servi\u00e7o de an\u00e1lise.<\/td>\n<\/tr>\n

        MongoDB<\/span><\/td>\nConsulta baseada em comandos SQL simplificada e baseada em Javascript.<\/span><\/td>\n<\/tr>\n<\/tbody>\n<\/table>\n

        ENTRADA e SA\u00cdDA<\/strong><\/p>\n\n\n\n\n\n\n\n
        SQL<\/span><\/td>\nINPUT: Conjunto de linhas (tuplas)<\/span><\/p>\n

        SA\u00cdDA: Um conjunto de linhas (tuplas)<\/span><\/td>\n<\/tr>\n

        Cassandra<\/span><\/td>\nENTRADA: Conjuntos de linhas<\/span><\/p>\n

        SA\u00cdDA: Conjunto de linhas<\/span><\/td>\n<\/tr>\n

        CosmosDB<\/span><\/td>\nINPUT: Conjuntos de JSON<\/span><\/p>\n

        SA\u00cdDA: Conjunto de JSON<\/span><\/td>\n<\/tr>\n

        Couchbase<\/span><\/td>\nINPUT: Conjuntos de JSON<\/span><\/p>\n

        SA\u00cdDA: Conjunto de JSON<\/span><\/td>\n<\/tr>\n

        MongoDB<\/span><\/td>\nINPUT: Conjuntos de JSON<\/span><\/p>\n

        SA\u00cdDA: Conjunto de JSON<\/span><\/td>\n<\/tr>\n<\/tbody>\n<\/table>\n

        SELECT: FROM Clause<\/b><\/p>\n\n\n\n\n\n\n\n
        SQL<\/span><\/td>\nEspecifica as tabelas de fontes de dados (rela\u00e7\u00f5es)<\/span><\/td>\n<\/tr>\n
        Cassandra<\/span><\/td>\ncl\u00e1usula FROM com apenas uma tabela permitida. Agora s\u00e3o permitidas jun\u00e7\u00f5es, subconsultas ou express\u00f5es. A interpreta\u00e7\u00e3o da cl\u00e1usula From \u00e9 igual \u00e0 do SQL.<\/span><\/td>\n<\/tr>\n
        CosmosDB<\/span><\/td>\nA cl\u00e1usula FROM oferece suporte a uma \u00fanica cole\u00e7\u00e3o e a uni\u00f5es pr\u00f3prias (o mesmo que UNNEST no Couchbase). \u00a0\u00a0<\/span><\/td>\n<\/tr>\n
        Couchbase<\/span><\/td>\nCl\u00e1usula FROM com v\u00e1rios espa\u00e7os-chave (subconjunto de bucket), subconsultas, express\u00f5es. Igual ao SQL<\/span><\/td>\n<\/tr>\n
        MongoDB<\/span><\/td>\ndb.t1.find() para uma \u00fanica tabela SELECT.<\/span><\/p>\n

        db.t1.aggregate() \u00e9 usado como a estrutura de consulta generalizada. aggregate() pode se unir a cole\u00e7\u00f5es adicionais usando o operador $lookup. Pode haver v\u00e1rios operadores $lookup na estrutura do pipeline de agrega\u00e7\u00e3o, o que o torna o primo mais pr\u00f3ximo da cl\u00e1usula SQL FROM.<\/span><\/td>\n<\/tr>\n<\/tbody>\n<\/table>\n

        SELECT: Cl\u00e1usula WHERE<\/b><\/p>\n\n\n\n\n\n\n\n
        SQL<\/td>\nCrit\u00e9rios para selecionar uma linha<\/td>\n<\/tr>\n
        Cassandra<\/td>\nExpress\u00f5es booleanas padr\u00e3o. Sem subconsultas.<\/td>\n<\/tr>\n
        CosmosDB<\/span><\/td>\nIgual ao SQL<\/td>\n<\/tr>\n
        Couchbase<\/td>\nExpress\u00f5es e subconsultas booleanas padr\u00e3o.<\/td>\n<\/tr>\n
        MongoDB<\/td>\ndb.t1.find({x:10});<\/p>\n

        aggregate() tem a cl\u00e1usula $match.<\/td>\n<\/tr>\n<\/tbody>\n<\/table>\n

        SELECT: Cl\u00e1usula SELECT<\/b><\/p>\n\n\n\n\n\n\n\n
        SQL<\/td>\nCl\u00e1usula de proje\u00e7\u00e3o<\/td>\n<\/tr>\n
        Cassandra<\/td>\nA cl\u00e1usula SELECT \u00e9 igual \u00e0 do SQL.<\/td>\n<\/tr>\n
        CosmosDB<\/span><\/td>\nA cl\u00e1usula SELECT \u00e9 igual \u00e0 do SQL.<\/td>\n<\/tr>\n
        Couchbase<\/td>\nA cl\u00e1usula SELECT \u00e9 igual \u00e0 do SQL.<\/td>\n<\/tr>\n
        MongoDB<\/td>\ndb.t1.find({x:10}, {a:1, b:1})<\/p>\n

        Operador do projeto $ no pipeline de agrega\u00e7\u00e3o<\/td>\n<\/tr>\n<\/tbody>\n<\/table>\n

        SELECT: CTE - Express\u00e3o de tabela comum<\/b><\/p>\n\n\n\n\n\n\n\n
        SQL<\/span><\/td>\nFonte de dados definida dinamicamente (tabela, conjunto de resultados)<\/span><\/td>\n<\/tr>\n
        Cassandra<\/span><\/td>\nSem suporte<\/span><\/td>\n<\/tr>\n
        CosmosDB<\/span><\/td>\nSem suporte<\/span><\/td>\n<\/tr>\n
        Couchbase<\/span><\/td>\nWITH; igual ao SQL (na vers\u00e3o 6.5). N\u00e3o h\u00e1 suporte para CTE recursivo<\/span><\/td>\n<\/tr>\n
        MongoDB<\/span><\/td>\nSem suporte<\/span><\/td>\n<\/tr>\n<\/tbody>\n<\/table>\n

        SELECT: Subquery<\/b><\/p>\n\n\n\n\n\n\n\n
        SQL<\/td>\nSubquery: Subconsultas na cl\u00e1usula FROM, na cl\u00e1usula WHERE e em qualquer lugar em que uma express\u00e3o seja permitida.<\/td>\n<\/tr>\n
        Cassandra<\/td>\nSem suporte<\/td>\n<\/tr>\n
        Cosmosdb<\/td>\nSem suporte<\/td>\n<\/tr>\n
        Couchbase<\/td>\nOferece suporte a subconsultas correlacionadas e n\u00e3o correlacionadas.<\/td>\n<\/tr>\n
        MongoDB<\/td>\nSem suporte em find(). Pode adicionar $match no pipeline, mas n\u00e3o \u00e9 exatamente um equivalente de uma subconsulta.<\/td>\n<\/tr>\n<\/tbody>\n<\/table>\n

        SELECT: GROUP BY<\/b><\/p>\n\n\n\n\n\n\n\n
        SQL<\/td>\nAgrupa as linhas com base em uma ou mais express\u00f5es. Bastante \u00fatil em relat\u00f3rios e agrega\u00e7\u00e3o de grupos.<\/td>\n<\/tr>\n
        Cassandra<\/td>\nSuportado; igual ao SQL.<\/td>\n<\/tr>\n
        Cosmosdb<\/td>\nSem suporte. S\u00f3 \u00e9 poss\u00edvel fazer a agrega\u00e7\u00e3o em todo o conjunto de resultados.<\/td>\n<\/tr>\n
        Couchbase<\/td>\nSuportado; semelhante ao SQL.<\/td>\n<\/tr>\n
        MongoDB<\/td>\nOperador $group no pipeline aggregate()<\/td>\n<\/tr>\n<\/tbody>\n<\/table>\n

        SELECT: cl\u00e1usula HAVING<\/b><\/p>\n\n\n\n\n\n\n\n
        SQL<\/td>\nFiltragem ap\u00f3s a agrega\u00e7\u00e3o.<\/td>\n<\/tr>\n
        Cassandra<\/td>\nSem suporte<\/td>\n<\/tr>\n
        CosmosDB<\/span><\/td>\nSem suporte<\/td>\n<\/tr>\n
        Couchbase<\/td>\nCl\u00e1usula HAVING; igual ao SQL<\/td>\n<\/tr>\n
        MongoDB<\/td>\n$match ap\u00f3s o agrupamento e a agrega\u00e7\u00e3o.<\/td>\n<\/tr>\n<\/tbody>\n<\/table>\n

        SELECT: Cl\u00e1usula ORDER BY<\/b><\/p>\n\n\n\n\n\n\n\n
        SQL<\/td>\nA ordem final dos resultados produzidos pelo bloco de consulta<\/td>\n<\/tr>\n
        Cassandra<\/td>\nCl\u00e1usula ORDER BY; igual ao SQL.<\/td>\n<\/tr>\n
        Cosmosdb<\/td>\nCl\u00e1usula ORDER BY; igual ao SQL.<\/td>\n<\/tr>\n
        Couchbase<\/td>\nCl\u00e1usula ORDER BY; igual ao SQL.<\/td>\n<\/tr>\n
        MongoDB<\/td>\ndb.t1.find().sort({a:1, b:-1});<\/p>\n

        aggregate() tem $sort para especificar a ordem do resultado.<\/td>\n<\/tr>\n<\/tbody>\n<\/table>\n

        SELECT: Cl\u00e1usula LIMIT, OFFSET<\/b><\/p>\n\n\n\n\n\n\n\n
        SQL<\/td>\nUsado para pagina\u00e7\u00e3o do conjunto de resultados<\/td>\n<\/tr>\n
        Cassandra<\/td>\n\"LIMIT \u00e9 compat\u00edvel.<\/p>\n

        OFFSET n\u00e3o \u00e9 compat\u00edvel.\"<\/td>\n<\/tr>\n

        CosmosDB<\/span><\/td>\nCl\u00e1usula LIMIT (TOP) e OFFSET; semelhante ao SQL<\/td>\n<\/tr>\n
        Couchbase<\/td>\nCl\u00e1usula LIMIT e OFFSET; igual ao SQL<\/td>\n<\/tr>\n
        MongoDB<\/td>\nm\u00e9todos skip(), limit() com find(). $offset, $limit com aggregate().<\/td>\n<\/tr>\n<\/tbody>\n<\/table>\n

        SELECT: Cl\u00e1usula JOIN<\/b><\/p>\n\n\n\n\n\n\n\n
        SQL<\/td>\nINNER JOIN, jun\u00e7\u00f5es externas LEFT\/RIGHT\/FULL.<\/td>\n<\/tr>\n
        Cassandra<\/td>\nN\u00e3o h\u00e1 suporte para uni\u00f5es. Os aplicativos ter\u00e3o que modelar os dados para evitar jun\u00e7\u00f5es ou fazer as jun\u00e7\u00f5es na camada do aplicativo.<\/td>\n<\/tr>\n
        Cosmosdb<\/td>\nSomente self JOINs. N\u00e3o h\u00e1 jun\u00e7\u00f5es INNER\/LEFT\/RIGHT\/etc.<\/td>\n<\/tr>\n
        Couchbase<\/td>\nOferece suporte a INNER, LEFT OUTER, NEST, UNNEST e RIGHT outer limitado. A mesma sintaxe do SQL. N\u00e3o h\u00e1 suporte para jun\u00e7\u00e3o FULL OUTER.<\/td>\n<\/tr>\n
        MongoDB<\/td>\nLEFT OUTER JOIN limitado somente por meio do operador $lookup. N\u00e3o h\u00e1 jun\u00e7\u00e3o em elementos de matriz ou express\u00f5es.<\/td>\n<\/tr>\n<\/tbody>\n<\/table>\n

        SELECT: Agrega\u00e7\u00e3o<\/b><\/p>\n\n\n\n\n\n\n\n
        SQL<\/span><\/td>\nAgrega\u00e7\u00e3o<\/span><\/td>\n<\/tr>\n
        Cassandra<\/span><\/td>\nH\u00e1 suporte para a agrega\u00e7\u00e3o simples em todo o resultado. A agrega\u00e7\u00e3o com GROUP BY n\u00e3o \u00e9 compat\u00edvel.<\/span><\/td>\n<\/tr>\n
        CosmosDB<\/span><\/td>\nH\u00e1 suporte para a agrega\u00e7\u00e3o simples em todo o resultado. A agrega\u00e7\u00e3o com GROUP BY n\u00e3o \u00e9 compat\u00edvel.<\/span><\/td>\n<\/tr>\n
        Couchbase<\/span><\/td>\nSUM, AVG, COUNT, MAX, MIN, VARIANCE: igual ao SQL<\/span><\/td>\n<\/tr>\n
        MongoDB<\/span><\/td>\n$sum, $count, $avg com suporte a agrupamento<\/span><\/td>\n<\/tr>\n<\/tbody>\n<\/table>\n

        SELECT: fun\u00e7\u00f5es agregadas<\/b><\/p>\n\n\n\n\n\n\n\n
        SQL<\/span><\/td>\n H\u00e1 suporte para a agrega\u00e7\u00e3o simples em todo o resultado. A agrega\u00e7\u00e3o com GROUP BY n\u00e3o \u00e9 compat\u00edvel.<\/span><\/td>\n<\/tr>\n
        Cassandra<\/span><\/td>\nSem suporte<\/span><\/td>\n<\/tr>\n
        Cosmosdb<\/span><\/td>\nSem suporte<\/span><\/td>\n<\/tr>\n
        Couchbase<\/span><\/td>\nOferece suporte \u00e0s fun\u00e7\u00f5es anal\u00edticas da janela SQL Standard na vers\u00e3o 6.5.<\/span><\/td>\n<\/tr>\n
        MongoDB<\/span><\/td>\nSem suporte<\/span><\/td>\n<\/tr>\n<\/tbody>\n<\/table>\n

        SELECT : Fun\u00e7\u00f5es de janela (anal\u00edticas\/agrega\u00e7\u00e3o)<\/b><\/p>\n\n\n\n\n\n\n\n
        SQL<\/span><\/td>\nFun\u00e7\u00f5es de janela para executar totais usando a cl\u00e1usula OVER()<\/span><\/td>\n<\/tr>\n
        Cassandra<\/span><\/td>\nSem suporte<\/span><\/td>\n<\/tr>\n
        CosmosDB<\/span><\/td>\nSem suporte<\/span><\/td>\n<\/tr>\n
        Couchbase<\/span><\/td>\nOferece suporte \u00e0s fun\u00e7\u00f5es anal\u00edticas da janela SQL Standard na vers\u00e3o 6.5.<\/span><\/p>\n

        Ver detalhes: https:\/\/www.couchbase.com\/blog\/json-to-insights-fast-and-easy\/<\/a><\/p>\n

        https:\/\/www.couchbase.com\/blog\/get-a-bigger-picture-with-n1ql-window-functions-and-cte\/<\/a><\/td>\n<\/tr>\n

        MongoDB<\/span><\/td>\nSem suporte<\/span><\/td>\n<\/tr>\n<\/tbody>\n<\/table>\n

        INSERT: inser\u00e7\u00e3o de uma \u00fanica linha\/documento.<\/b><\/p>\n\n\n\n\n\n\n\n
        SQL<\/span><\/td>\nInserir uma \u00fanica linha<\/span><\/td>\n<\/tr>\n
        Cassandra<\/span><\/td>\nDeclara\u00e7\u00e3o INSERT<\/span><\/td>\n<\/tr>\n
        CosmosDB<\/span><\/td>\nInser\u00e7\u00e3o de API<\/span><\/td>\n<\/tr>\n
        Couchbase<\/span><\/td>\nDeclara\u00e7\u00e3o INSERT<\/span><\/td>\n<\/tr>\n
        MongoDB<\/span><\/td>\ndb.t1.save()<\/span><\/td>\n<\/tr>\n<\/tbody>\n<\/table>\n

        INSERT: inser\u00e7\u00e3o de v\u00e1rias linhas\/documentos.<\/b><\/p>\n\n\n\n\n\n\n\n
        SQL<\/td>\nDeclara\u00e7\u00e3o INSERT<\/td>\n<\/tr>\n
        Cassandra<\/td>\nSem suporte<\/td>\n<\/tr>\n
        Cosmosdb<\/td>\nSem suporte<\/td>\n<\/tr>\n
        Couchbase<\/td>\nINSERT com v\u00e1rios documentos<\/td>\n<\/tr>\n
        MongoDB<\/td>\ndb.t1.insert()<\/td>\n<\/tr>\n<\/tbody>\n<\/table>\n

        Declara\u00e7\u00e3o DELETE<\/b><\/p>\n\n\n\n\n\n\n\n
        SQL<\/td>\nExcluir um ou mais documentos<\/td>\n<\/tr>\n
        Cassandra<\/td>\nDeclara\u00e7\u00e3o DELETE; igual ao SQL<\/td>\n<\/tr>\n
        Cosmosdb<\/td>\nExclus\u00e3o da API<\/td>\n<\/tr>\n
        Couchbase<\/td>\nDeclara\u00e7\u00e3o DELETE; igual ao SQL<\/td>\n<\/tr>\n
        MongoDB<\/td>\ndb.t1.delete()<\/td>\n<\/tr>\n<\/tbody>\n<\/table>\n

        Declara\u00e7\u00e3o UPSERT<\/b><\/p>\n\n\n\n\n\n\n\n
        SQL<\/td>\nINSERIR. UPDATE se existir.<\/td>\n<\/tr>\n
        Cassandra<\/td>\nSem suporte<\/td>\n<\/tr>\n
        Cosmosdb<\/td>\nSem suporte<\/td>\n<\/tr>\n
        Couchbase<\/td>\nDeclara\u00e7\u00e3o UPSERT.<\/td>\n<\/tr>\n
        MongoDB<\/td>\nSem suporte<\/td>\n<\/tr>\n<\/tbody>\n<\/table>\n

        Declara\u00e7\u00e3o de atualiza\u00e7\u00e3o<\/b><\/p>\n\n\n\n\n\n\n\n
        SQL<\/span><\/td>\n<\/td>\n<\/tr>\n
        Cassandra<\/span><\/td>\nUPDATE; o mesmo que SQL<\/span><\/td>\n<\/tr>\n
        CosmosDB<\/span><\/td>\nAtualiza\u00e7\u00e3o da API<\/span><\/td>\n<\/tr>\n
        Couchbase<\/span><\/td>\nUPDATE; o mesmo que SQL<\/span><\/td>\n<\/tr>\n
        MongoDB<\/span><\/td>\ndb.t1.update()<\/span><\/td>\n<\/tr>\n<\/tbody>\n<\/table>\n

        MERGE: mescla uma rela\u00e7\u00e3o (conjunto de linhas) com outra.<\/b><\/p>\n\n\n\n\n\n\n\n
        SQL<\/td>\nMesclar um conjunto de linhas (documentos) em outro.<\/td>\n<\/tr>\n
        Cassandra<\/td>\nSem suporte<\/td>\n<\/tr>\n
        CosmosDB<\/span><\/td>\nSem suporte<\/td>\n<\/tr>\n
        Couchbase<\/td>\nDeclara\u00e7\u00e3o MERGE, igual ao SQL.<\/td>\n<\/tr>\n
        MongoDB<\/td>\nSem suporte<\/td>\n<\/tr>\n<\/tbody>\n<\/table>\n

        Declara\u00e7\u00e3o PREPARE<\/b><\/p>\n\n\n\n\n\n\n\n
        SQL<\/td>\nAnalisar, analisar e criar um plano de execu\u00e7\u00e3o.<\/td>\n<\/tr>\n
        Cassandra<\/td>\nCom suporte. Vejo exemplos de preparedStatement() no Java SDK.dd<\/td>\n<\/tr>\n
        CosmosDB<\/span><\/td>\nSem suporte<\/td>\n<\/tr>\n
        Couchbase<\/td>\nApoiado; PREPARAR<\/td>\n<\/tr>\n
        MongoDB<\/td>\nSem suporte<\/td>\n<\/tr>\n<\/tbody>\n<\/table>\n

        EXECUTAR<\/b><\/p>\n\n\n\n\n\n\n\n
        SQL<\/td>\nExecutar uma declara\u00e7\u00e3o ad-hoc ou preparada.<\/td>\n<\/tr>\n
        Cassandra<\/td>\nSuportado em Java.<\/td>\n<\/tr>\n
        Cosmosdb<\/td>\nSem suporte<\/td>\n<\/tr>\n
        Couchbase<\/td>\nSuportado, semelhante ao SQL.<\/td>\n<\/tr>\n
        MongoDB<\/td>\nSem suporte<\/td>\n<\/tr>\n<\/tbody>\n<\/table>\n

        CONCESS\u00c3O\/REVOGA\u00c7\u00c3O<\/b><\/p>\n\n\n\n\n\n\n\n
        SQL<\/td>\nConceder\/REVOGAR permiss\u00f5es para opera\u00e7\u00f5es espec\u00edficas no conjunto de dados<\/td>\n<\/tr>\n
        Cassandra<\/td>\nCONCESS\u00c3O, REVOGA\u00c7\u00c3O<\/td>\n<\/tr>\n
        CosmosDB<\/span><\/td>\nSuporte \u00e0 API<\/td>\n<\/tr>\n
        Couchbase<\/td>\nCONCEDER FUN\u00c7\u00c3O, REVOGAR FUN\u00c7\u00c3O<\/td>\n<\/tr>\n
        MongoDB<\/td>\nTBD??<\/td>\n<\/tr>\n<\/tbody>\n<\/table>\n

        Declara\u00e7\u00e3o DESCRIBE<\/b><\/p>\n\n\n\n\n\n\n\n
        SQL<\/td>\nDescreve o esquema de uma tabela<\/td>\n<\/tr>\n
        Cassandra<\/td>\nDESCREVER<\/td>\n<\/tr>\n
        Cosmosdb<\/td>\nSem suporte<\/td>\n<\/tr>\n
        Couchbase<\/td>\nO INFER descreve o esquema dos documentos<\/td>\n<\/tr>\n
        MongoDB<\/td>\nFerramenta de b\u00fassola - somente gr\u00e1fica.<\/td>\n<\/tr>\n<\/tbody>\n<\/table>\n

        Declara\u00e7\u00e3o TRUNCATE<\/b><\/p>\n\n\n\n\n\n\n\n
        SQL<\/td>\nTrunca os dados da tabela sem alterar a seguran\u00e7a ou o esquema f\u00edsico.<\/td>\n<\/tr>\n
        Cassandra<\/td>\nTRUNCAR<\/td>\n<\/tr>\n
        CosmosDB<\/span><\/td>\nSem suporte<\/td>\n<\/tr>\n
        Couchbase<\/td>\nOpera\u00e7\u00e3o FLUSH<\/td>\n<\/tr>\n
        MongoDB<\/td>\nSem suporte. Solu\u00e7\u00e3o alternativa: remover a cole\u00e7\u00e3o e recri\u00e1-la com as mesmas configura\u00e7\u00f5es de seguran\u00e7a.<\/td>\n<\/tr>\n<\/tbody>\n<\/table>\n

        L\u00f3gica de valores (valores booleanos)<\/b><\/p>\n\n\n\n\n\n\n\n
        SQL<\/td>\nTrue, False, NULL (Desconhecido)<\/td>\n<\/tr>\n
        Cassandra<\/td>\nTrue, False, NULL (Desconhecido)<\/td>\n<\/tr>\n
        Cosmosdb<\/td>\nTrue, False, NULL (Desconhecido)<\/td>\n<\/tr>\n
        Couchbase<\/td>\nTrue (Verdadeiro), False (Falso), NULL (Desconhecido), Missing (Ausente)<\/p>\n

        https:\/\/docs.couchbase.com\/server\/4.0\/n1ql\/n1ql-language-reference\/booleanlogic.html<\/a><\/td>\n<\/tr>\n

        MongoDB<\/td>\nTrue, False, NULL (Desconhecido)<\/td>\n<\/tr>\n<\/tbody>\n<\/table>\n

        Otimizador de consultas: Tipo de otimizador<\/b><\/p>\n\n\n\n\n\n\n\n
        SQL<\/td>\nOtimizador baseado em regras e em custos. Faz reescrita de consultas, sele\u00e7\u00e3o de \u00edndices, ordena\u00e7\u00e3o de jun\u00e7\u00f5es, sele\u00e7\u00e3o de tipos de jun\u00e7\u00f5es e posi\u00e7\u00e3o dos tabuladores (interno\/externo, constru\u00e7\u00e3o\/probe de tabelas de hash)<\/td>\n<\/tr>\n
        Cassandra<\/td>\nOtimizador baseado em regras. A sele\u00e7\u00e3o de \u00edndices para a tabela \u00fanica \u00e9 feita, pois n\u00e3o h\u00e1 jun\u00e7\u00f5es.<\/td>\n<\/tr>\n
        CosmosDB<\/span><\/td>\nO otimizador baseado em regras faz principalmente a sele\u00e7\u00e3o de \u00edndices.<\/td>\n<\/tr>\n
        Couchbase<\/td>\nOtimizador baseado em regras, sele\u00e7\u00e3o de \u00edndice(s). Bloqueia a jun\u00e7\u00e3o de loop aninhado por padr\u00e3o, mas oferece suporte \u00e0 jun\u00e7\u00e3o de hash por meio de dica do usu\u00e1rio na consulta.<\/td>\n<\/tr>\n
        MongoDB<\/td>\nOtimizador \"baseado em forma\" de acordo com a documenta\u00e7\u00e3o. Cada nova consulta \u00e9 combinada com uma consulta baseada na \"forma\". Na primeira vez que uma consulta \u00e9 executada, o otimizador faz a sele\u00e7\u00e3o do \u00edndice, mas quando h\u00e1 v\u00e1rios candidatos, ele executa v\u00e1rias consultas simultaneamente para ver quem retorna os resultados primeiro.<\/td>\n<\/tr>\n<\/tbody>\n<\/table>\n

        Otimizador de consultas: Sele\u00e7\u00e3o de \u00edndice<\/b><\/p>\n\n\n\n\n\n\n\n
        SQL<\/td>\nSim<\/td>\n<\/tr>\n
        Cassandra<\/td>\nSim<\/td>\n<\/tr>\n
        CosmosDB<\/span><\/td>\nSim<\/td>\n<\/tr>\n
        Couchbase<\/td>\nSim<\/td>\n<\/tr>\n
        MongoDB<\/td>\nSim<\/td>\n<\/tr>\n<\/tbody>\n<\/table>\n

        Otimizador de consultas: Reescrita de consultas<\/b><\/p>\n\n\n\n\n\n\n\n
        SQL<\/span><\/td>\nReescrever partes da consulta em um equivalente l\u00f3gico para melhorar o desempenho. Por exemplo, reescrita de subconsulta, dobramento de visualiza\u00e7\u00e3o, convers\u00e3o de tipo de jun\u00e7\u00e3o, avalia\u00e7\u00e3o de express\u00e3o constante etc.<\/span><\/td>\n<\/tr>\n
        Cassandra<\/span><\/td>\nNenhum<\/span><\/td>\n<\/tr>\n
        Cosmosdb<\/span><\/td>\nNenhuma reescrita conhecida<\/span><\/td>\n<\/tr>\n
        Couchbase<\/span><\/td>\nReescrita de consulta b\u00e1sica. LEFT OUTER para INNER quando aplic\u00e1vel, avalia\u00e7\u00e3o de express\u00f5es constantes.<\/span><\/td>\n<\/tr>\n
        MongoDB<\/span><\/td>\nNenhum<\/span><\/td>\n<\/tr>\n<\/tbody>\n<\/table>\n

        Otimiza\u00e7\u00e3o de consultas: Tipo JOIN <\/b><\/p>\n\n\n\n\n\n\n\n
        SQL<\/td>\nEscolha o \u00edndice mais eficiente, dentre os tipos de uni\u00e3o dispon\u00edveis.<\/td>\n<\/tr>\n
        Cassandra<\/td>\nN\u00e3o aplic\u00e1vel, pois n\u00e3o h\u00e1 suporte para uni\u00f5es.<\/td>\n<\/tr>\n
        CosmosDB<\/span><\/td>\nN\u00e3o est\u00e1 claramente documentado.<\/td>\n<\/tr>\n
        Couchbase<\/td>\nLoop aninhado por padr\u00e3o. Jun\u00e7\u00e3o de hash por dica de usu\u00e1rio.<\/td>\n<\/tr>\n
        MongoDB<\/td>\nApenas o loop aninhado \u00e9 suportado.<\/td>\n<\/tr>\n<\/tbody>\n<\/table>\n

        Suporte \u00e0 TRANSA\u00c7\u00c3O. \u00a0<\/b><\/p>\n\n\n\n\n\n\n\n
        SQL<\/span><\/td>\nSuporte ACID com suporte a v\u00e1rias linhas e v\u00e1rias declara\u00e7\u00f5es.<\/span><\/td>\n<\/tr>\n
        Cassandra<\/span><\/td>\nN\u00e3o<\/span><\/td>\n<\/tr>\n
        Cosmosdb<\/span><\/td>\nSim<\/span><\/td>\n<\/tr>\n
        Couchbase<\/span><\/td>\nN\u00e3o<\/span><\/td>\n<\/tr>\n
        MongoDB<\/span><\/td>\nSim, na vers\u00e3o 4.0<\/span><\/td>\n<\/tr>\n<\/tbody>\n<\/table>\n

        \u00cdndices<\/b><\/p>\n\n\n\n\n\n\n\n
        SQL<\/td>\nEstruturas de dados mantidas para acelerar o desempenho da consulta. Os \u00edndices s\u00e3o<\/td>\n<\/tr>\n
        Cassandra<\/td>\nOferece suporte a \u00edndices prim\u00e1rios, secund\u00e1rios e de matriz. \u00c9 necess\u00e1rio instalar e indexar os dados no SOLR para um \u00edndice de pesquisa.<\/td>\n<\/tr>\n
        CosmosDB<\/span><\/td>\nIndexa tudo por padr\u00e3o: escalares, matrizes. N\u00e3o h\u00e1 suporte para o \u00edndice de pesquisa.<\/td>\n<\/tr>\n
        Couchbase<\/td>\nOferece suporte a \u00edndices prim\u00e1rios, secund\u00e1rios, compostos, funcionais, adaptativos, de pesquisa, espaciais, particionados e de r\u00e9plica. Os \u00edndices s\u00e3o eventualmente consistentes.<\/td>\n<\/tr>\n
        MongoDB<\/td>\nOferece suporte a \u00edndices prim\u00e1rio, secund\u00e1rio, composto, de pesquisa, espacial, particionado e de r\u00e9plica. O \u00edndice de pesquisa \u00e9 criado de forma simplista em uma \u00e1rvore B.<\/td>\n<\/tr>\n<\/tbody>\n<\/table>\n

        SQL: Suporte a tipos de dados.<\/b><\/p>\n\n\n\n\n\n\n\n
        SQL<\/span><\/td>\nAmplo suporte a tipos de dados num\u00e9ricos, de caracteres e de data e hora.<\/span><\/td>\n<\/tr>\n
        Cassandra<\/span><\/td>\nNum\u00e9rico, decimal, duplo. Int, float, varint, Timestamp, cole\u00e7\u00e3o (set, list) <\/span><\/td>\n<\/tr>\n
        CosmosDB<\/span><\/td>\nTipos de dados JSON: num\u00e9rico, string, booleano, objeto, matrizes<\/span><\/td>\n<\/tr>\n
        Couchbase<\/span><\/td>\nTipos de dados JSON: num\u00e9rico, string, booleano, objeto, matrizes<\/span><\/td>\n<\/tr>\n
        MongoDB<\/span><\/td>\nTipos de dados JSON: num\u00e9rico, cadeia de caracteres, booleano, objeto, matrizes e extens\u00f5es personalizadas para o tipo de dados de carimbo de data\/hora.<\/span><\/td>\n<\/tr>\n<\/tbody>\n<\/table>\n

        Conclus\u00e3o:<\/strong><\/p>\n

        Os bancos de dados NoSQL populares tentaram estender e dar suporte ao SQL declarativo para os respectivos modelos e arquiteturas de dados. Portanto, \u00e9 importante entender os recursos, as limita\u00e7\u00f5es dos recursos e a arquitetura durante a avalia\u00e7\u00e3o.<\/p>\n

        Refer\u00eancias:<\/strong><\/p>\n

          \n
        1. A efic\u00e1cia irracional do SQL<\/a><\/li>\n<\/ol>","protected":false},"excerpt":{"rendered":"

          Business applications have requirements: take customer orders, deliver customer orders, track shipping, generate inventory report, end of the day\/month\/quarter business report, generate business dashboards and more. \u00a0These requirements evolve slowly. They remain even when you choose a NoSQL database. On […]<\/p>","protected":false},"author":55,"featured_media":6985,"comment_status":"open","ping_status":"open","sticky":false,"template":"","format":"standard","meta":{"_acf_changed":false,"inline_featured_image":false,"footnotes":""},"categories":[1814,2294,1819,1812],"tags":[1886,2136,1261,1590,1309],"ppma_author":[8929],"class_list":["post-6760","post","type-post","status-publish","format-standard","has-post-thumbnail","hentry","category-application-design","category-analytics","category-data-modeling","category-n1ql-query","tag-cassandra","tag-cosmosdb","tag-json","tag-microsoft","tag-mongodb"],"acf":[],"yoast_head":"\nThe Unreasonable Effectiveness of SQL in NoSQL Databases<\/title>\n<meta name=\"description\" content=\"Compare and contrast SQL language support in Cassandra, CosmosDB, Couchbase, and MongoDB via their respective implementations.\u00a0\" \/>\n<meta name=\"robots\" content=\"index, follow, max-snippet:-1, max-image-preview:large, max-video-preview:-1\" \/>\n<link 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