Iceberg, Delta Lake e Hudi: como os formatos de tabela levaram Data Lakes à arquitetura Lakehouse

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Esta parte de uma série sobre Apache Spark examina a transição dos Data Lakes para a arquitetura Lakehouse. O texto explica que arquivos Parquet isolados não oferecem, por si só, transações, controle de versões ou consistência entre leituras e escritas concorrentes. Para resolver isso, formatos de tabela como Apache Iceberg, Delta Lake e Apache Hudi adicionam uma camada de gerenciamento sobre arquivos em armazenamento de objetos. Essa abordagem busca combinar a flexibilidade dos Data Lakes com recursos analíticos típicos de Data Warehouses, sem substituí-los, e permite acesso por diferentes mecanismos de SQL, BI e machine learning.

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