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MongoDB provides three ways to perform aggregation: the aggregation pipeline, the map-reduce function and single-purpose aggregation methods. [40] Map-reduce can be used for batch processing of data and aggregation operations. However, according to MongoDB's documentation, the aggregation pipeline provides better performance for most ...
It is designed to provide high availability, scalability, and low-latency access to data for modern applications. Unlike traditional relational databases, Cosmos DB is a NoSQL (meaning "Not only SQL", rather than "zero SQL") and vector database, [1] which means it can handle unstructured, semi-structured, structured, and vector data types. [2]
MapReduce is a programming model and an associated implementation for processing and generating big data sets with a parallel and distributed algorithm on a cluster. [1] [2] [3]A MapReduce program is composed of a map procedure, which performs filtering and sorting (such as sorting students by first name into queues, one queue for each name), and a reduce method, which performs a summary ...
Laminas, framework that includes a table data gateway and row data gateway implementations; Qcodo, ORM and framework, open source; Redbean, ORM layer for PHP, for creating and maintaining tables on the fly, open source, BSD; Skipper, visualization tool and a code/schema generator for PHP ORM frameworks, commercial
The company was first established in 2007 as 10gen. Based in New York City, 10gen was founded by former DoubleClick founder and CTO Dwight Merriman and former DoubleClick CEO and Gilt Groupe founder Kevin P. Ryan with former DoubleClick engineer and ShopWiki founder and CTO Eliot Horowitz and received $81 million in venture capital funding from Flybridge Capital Partners, In-Q-Tel, Intel ...
Decomposable aggregation functions are important in online analytical processing (OLAP), as they allow aggregation queries to be computed on the pre-computed results in the OLAP cube, rather than on the base data. [7] For example, it is easy to support COUNT, MAX, MIN, and SUM in OLAP, since these can be computed for each cell of the OLAP cube ...
An aggregate is a type of summary used in dimensional models of data warehouses to shorten the time it takes to provide answers to typical queries on large sets of data. The reason why aggregates can make such a dramatic increase in the performance of a data warehouse is the reduction of the number of rows to be accessed when responding to a query.
Bitemporal modeling is a specific case of temporal database information modeling technique designed to handle historical data along two different timelines. [1] This makes it possible to rewind the information to "as it actually was" in combination with "as it was recorded" at some point in time.