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MongoDB is a source-available, cross-platform, document-oriented database program. Classified as a NoSQL database product, MongoDB uses 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).
Oracle has its own spin where creating a user is synonymous with creating a schema. Thus a database administrator can create a user called PROJECT and then create a table PROJECT.TABLE. Users can exist without schema objects, but an object is always associated with an owner (though that owner may not have privileges to connect to the database).
MongoDB, Inc. is an American software company that develops and provides commercial support for the source-available database engine MongoDB, a NoSQL database that stores data in JSON-like documents with flexible schemas.
Pandas is built around data structures called Series and DataFrames. Data for these collections can be imported from various file formats such as comma-separated values, JSON, Parquet, SQL database tables or queries, and Microsoft Excel. [8] A Series is a 1-dimensional data structure built on top of NumPy's array.
MySQL (/ ˌ m aɪ ˌ ɛ s ˌ k juː ˈ ɛ l /) [6] is an open-source relational database management system (RDBMS). [6] [7] Its name is a combination of "My", the name of co-founder Michael Widenius's daughter My, [1] and "SQL", the acronym for Structured Query Language.
Both a developer and a commercial edition [9] was released, along with a business license [10] for integrating with other database management systems such as PostgreSQL. [11] [12] In Spring 2019, MongoDB acquired Realm for 39 million USD. [13] In September 2023, the Realm database was rebranded to be called "Atlas Device SDKs".
The function names for queries differ across geodatabases. The following are a few of the functions built into PostGIS, a free geodatabase which is a PostgreSQL extension (the term 'geometry' refers to a point, line, box or other two or three dimensional shape): [7] Function prototype: functionName (parameter(s)) : return type
In an EAV data model, each attribute–value pair is a fact describing an entity, and a row in an EAV table stores a single fact. EAV tables are often described as "long and skinny": "long" refers to the number of rows, "skinny" to the few columns. Data is recorded as three columns: The entity: the item being described.