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MongoDB can be used as a file system, called GridFS, with load-balancing and data-replication features over multiple machines for storing files. This function, called a grid file system, [36] is included with MongoDB drivers. MongoDB exposes functions for file manipulation and content to developers.
Presto (including PrestoDB, and PrestoSQL which was re-branded to Trino) is a distributed query engine for big data using the SQL query language. Its architecture allows users to query data sources such as Hadoop, Cassandra, Kafka, AWS S3, Alluxio, MySQL, MongoDB and Teradata, [1] and allows use of multiple data sources within a query.
Polymorphic databases such as MongoDB and SQLite can store the native value directly into the object field. Thus, SPARQL provides a full set of analytic query operations such as JOIN , SORT , AGGREGATE for data whose schema is intrinsically part of the data rather than requiring a separate schema definition.
Amazon DocumentDB is a managed proprietary NoSQL database service that supports document data structures, with some compatibility with MongoDB version 3.6 (released by MongoDB in 2017) and version 4.0 (released by MongoDB in 2018). As a document database, Amazon DocumentDB can store, query, and index JSON data. It is available on Amazon Web ...
In addition, MongoDB's architecture unifies source data, metadata, operational data, and vector data in an all-in-one platform, updating the need for multiple database systems and complex back-end ...
In a relational database, data is first categorized into a number of predefined types, and tables are created to hold individual entries, or records, of each type. The tables define the data within each record's fields, meaning that every record in the table has the same overall form
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]
A database shard can be placed on separate hardware, and multiple shards can be placed on multiple machines. This enables a distribution of the database over a large number of machines, greatly improving performance. In addition, if the database shard is based on some real-world segmentation of the data (e.g., European customers v.