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In order to write business backend code Serverside JavaScript is used primarily. There are APIs to access the document oriented database and the XPages context. [5] Since XPages are based on JSF and JSF is a Java standard it is also possible to invoke standard Java SDK code from the JavaScript code and to write custom Java code using JSF ...
ArangoDB is a transactional native multi-model database supporting two major NoSQL data models (graph and document [1]) with one query language. Written in C++ and optimized for in-memory computing. In addition ArangoDB integrated RocksDB for persistent storage. ArangoDB supports Java, JavaScript, Python, PHP, NodeJS, C++ and Elixir.
It uses JSON to store data, JavaScript as its query language using MapReduce, and HTTP for an API. [2] CouchDB was first released in 2005 and later became an Apache Software Foundation project in 2008. Unlike a relational database, a CouchDB database does not store data and relationships in tables. Instead, each database is a collection of ...
MongoDB is a source-available, cross-platform, document-oriented database program. Classified as a NoSQL database product, MongoDB utilizes JSON-like documents with optional schemas. Released in February 2009 by 10gen (now MongoDB Inc.), it supports features like sharding, replication, and ACID transactions (from version 4.0).
A document-oriented database is a specialized key-value store, which itself is another NoSQL database category. In a simple key-value store, the document content is opaque. A document-oriented database provides APIs or a query/update language that exposes the ability to query or update based on the internal structure in the document. This ...
Web storage, sometimes known as DOM storage (Document Object Model storage), is a standard JavaScript API provided by web browsers. It enables websites to store persistent data on users' devices similar to cookies , but with much larger capacity [ 1 ] and no information sent in HTTP headers . [ 2 ]
Apache Cassandra is a free and open-source database management system designed to handle large volumes of data across multiple commodity servers.The system prioritizes availability and scalability over consistency, making it particularly suited for systems with high write throughput requirements due to its LSM tree indexing storage layer. [2]
Internally, Cosmos DB stores "items" in "containers", [3] with these two concepts being surfaced differently depending on the API used (these would be "documents" in "collections" when using the MongoDB-compatible API, for example). Containers are grouped in "databases", which are analogous to namespaces above containers.