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The project dimension serves both control and accounting ends. The project needs to stay on schedule. There is a financial need to see projects integrally—not period by period, but from inception to date—and, most important, to measure earned value and estimate profit and loss
The Projects applications apply a project dimension to Purchasing, Payables, Order Management, Receivables, and Inventory. Project Manufacturing links it with the rest of the Manufacturing suite
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In this paper, we examine a number of SQL and socalled “NoSQL” data stores designed to scale simple OLTP-style application loads over many servers. Originally motivated by Web 2.0 applications, these systems are designed to scale to thousands or millions of users doing updates as well as reads, in contrast to traditional DBMSs and data warehouses. We contrast the new systems on their data model, consistency mechanisms, storage mechanisms, durability guarantees, availability, query support, and other dimensions. These systems typically sacrifice some of these dimensions, e.g. database-wide transaction consistency, in order to achieve others, e.g. higher availability and scalability. Note: Bibliographic references for systems are not listed, but URLs for more information can be found in the System References table at the end of this paper. Caveat: Statements in this paper are based on sources and documentation that may not be reliable, and the systems described are “moving targets,” so some statements may be incorrect. Verify through other sources before depending on information here. Nevertheless, we hope this comprehensive survey is useful! Check for future corrections on the author’s web site cattell.net/datastores. Disclosure: The author is on the technical advisory board of Schooner Technologies and has a consulting business advising on scalable databases.
Oracle NoSQL Database and MongoDB server are both licensed under AGPL while MongoDB has certain client drivers under the Apache 2.0 license. Oracle NoSQL Database is in many respects, as a NoSQL Database implementation leveraging BerkeleyDB in its storage layer, a commercialization of the early NoSQL implementations which lead to the adoption of this category of technology. Several of the earliest NoSQL solutions were based on BerkeleyDB and some are still to this day e.g. LinkedIn’s Voldemort. The Oracle NoSQL Database is a Java based key-value store implementation that supports a value abstraction layer currently implementing Binary and JSON types. Its key structure is designed in such a way as to facilitate large scale distribution and storage locality with range based search and retrieval. The implementation uniquely supports built in cluster load balancing and a full range of transaction semantics from ACID to relaxed eventually consistent. In addition, the technology is integrated with important open source technologies like Hadoop / MapReduce, an increasing number of Oracle software solutions and tools and can be found on Oracle Engineered Systems.