Oracle SecureFiles System
PVLDB(2008)
摘要
Over the last decade, the nature of content stored on computer storage systems has evolved from being relational to being semi-structured, i.e., unstructured data accompanied by relational metadata. Average data volumes have increased from a few hundred megabytes to hundreds of terabytes. Simultaneously, data feed rates have also increased with increase in processor, storage and network bandwidths. Data growth trends seem to be following Moore's law and thereby imply an exponential explosion in content volumes and rates in the years to come. The near future poses requirements for data management systems to provide solutions that provide unlimited scalability in execution, availability, recoverability and storage usage of semi-structured content. Traditionally, filesystems have been preferred over database management systems for providing storage solutions for unstructured data, while databases have been the preferred choice to manage relational data. Lack of consolidated semi-structured content management architecture compromises security, availability, recoverability, and manageability among other features. We introduce a system without compromises, the Oracle SecureFiles System, designed to provide highly scalable storage and access execution of unstructured and structured content as first-class objects within the Oracle relational database management system. Oracle SecureFiles breaks the performance barrier that has kept such content out of databases. The architecture provides capability to maximize utilization of storage usage through compression and de-duplication and achieves robustness by preserving transactional atomicity, durability, availability, read-consistent query-ability and security of the database management system.
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关键词
relational data,data management system,storage usage,consolidated semi-structured content management,data growth trend,average data volume,oracle securefiles system,content volume,computer storage system,database management system,unstructured data
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