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  2. Vector database - Wikipedia

    en.wikipedia.org/wiki/Vector_database

    A vector database, vector store or vector search engine is a database that can store vectors (fixed-length lists of numbers) along with other data items. Vector databases typically implement one or more Approximate Nearest Neighbor algorithms, [1] [2] [3] so that one can search the database with a query vector to retrieve the closest matching database records.

  3. Milvus (vector database) - Wikipedia

    en.wikipedia.org/wiki/Milvus_(vector_database)

    Column-oriented database; Four supported data consistency levels, including strong consistency and eventual consistency. [13] Data sharding; Streaming data ingestion, which allows to process and ingest data in real-time as it arrives; A dynamic schema, which allows inserting the data without a predefined schema; Independent storage and compute ...

  4. List of in-memory databases - Wikipedia

    en.wikipedia.org/wiki/List_of_in-memory_databases

    Java, C#, C, Python, Go, Node.js, Perl, libevent, PHP, Ruby, Rust Open Source (AGPL) Flash-optimized in-memory open source NoSQL database. ALTIBASE HDB: Altibase Corporation 1999 Java, C, C++, JDBC, ODBC, SQL Proprietary Altibase is a hybrid DBMS that combines an in-memory database with a conventional disk-resident database in a single unified ...

  5. Category:Vector databases - Wikipedia

    en.wikipedia.org/wiki/Category:Vector_databases

    Main page; Contents; Current events; Random article; About Wikipedia; Contact us; Pages for logged out editors learn more

  6. Database schema - Wikipedia

    en.wikipedia.org/wiki/Database_schema

    The database schema is the structure of a database described in a formal language supported typically by a relational database management system (RDBMS). The term " schema " refers to the organization of data as a blueprint of how the database is constructed (divided into database tables in the case of relational databases ).

  7. TypeDB - Wikipedia

    en.wikipedia.org/wiki/TypeDB

    The data model of TypeDB is based on primitives from conceptual data modeling, which are implemented in a type system (see § Data and query model). The type system can be extended with user-defined types , type dependencies , and subtyping , which together act as a database schema .

  8. Schema matching - Wikipedia

    en.wikipedia.org/wiki/Schema_matching

    The terms schema matching and mapping are often used interchangeably for a database process. For this article, we differentiate the two as follows: schema matching is the process of identifying that two objects are semantically related (scope of this article) while mapping refers to the transformations between the objects.

  9. Nested set model - Wikipedia

    en.wikipedia.org/wiki/Nested_set_model

    The Nested Set model is appropriate where the tree element and one or two attributes are the only data, but is a poor choice when more complex relational data exists for the elements in the tree. Given an arbitrary starting depth for a category of 'Vehicles' and a child of 'Cars' with a child of 'Mercedes', a foreign key table relationship must ...