TAILIEUCHUNG - Oracle NoSQL Database

Heterogeneity of information sources: Data may originate at a few authoritative sources, or alternatively, every participant might be allowed (or expected) to contribute data to the community. The level of heterogeneity of the data influences the degree to which a system can ensure uniform, global semantics for the data. A P2P system might impose a single schema on all participants to enforce uniform, global semantics, but for some applications this will be too restrictive. Alternatively, a limited number of data sources and schemas may be allowed, so traditional schema and data integration techniques will likely apply (with the restriction that there is no central authority) | An Oracle White Paper September 2011 Oracle NoSQL Database ORACLE Oracle NoSQL Database Introduction NoSQL databases represent a recent evolution in enterprise application architecture continuing the evolution of the past twenty years. In the 1990 s vertically integrated applications gave way to client-server architectures and more recently client-server architectures gave way to three-tier web application architectures. In parallel the demands of web-scale data analysis added map-reduce processing into the mix and data architects started eschewing transactional consistency in exchange for incremental scalability and large-scale distribution. The NoSQL movement emerged out of this second ecosystem. NoSQL is often characterized by what it s not - depending on whom you ask it s either not only a SQL-based relational database management system or it s simply not a SQL-based RDBMS. While those definitions explain what NoSQL is not they do little to explain what NoSQL is. Consider the fundamentals that have guided data management for the past forty years. RDBMS systems and large-scale data management have been characterized by the transactional ACID properties of Atomicity Consistency Isolation and Durability. In contrast NoSQL is sometimes characterized by the BASE acronym Basically Available Use replication to reduce the likelihood of data unavailability and use sharding or partitioning the data among many different storage servers to make any remaining failures partial. The result is a system that is always available even if subsets of the data become unavailable for short periods of time. Soft state While ACID systems assume that data consistency is a hard requirement NoSQL systems allow data to be inconsistent and relegate designing around such inconsistencies to application developers. Eventually consistent Although applications must deal with instantaneous consistency NoSQL systems ensure that at some future point in time the data assumes a consistent state. In .

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