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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.
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 ...
Specialized editions for (for example) clustering, high availability, 64-bit support, and hybrid (in-memory and persistent) storage. eXtremeDB Financial Edition implements columnar data handling, vector-based statistical function library, integrated performance monitoring. H2 (DBMS) H2 Java, ODBC, JDBC
A hybrid topological data model has the option of storing topological relationship information as a separate layer built on top of a spaghetti data set. An example is the network dataset within the Esri geodatabase. [23] Vector data are commonly used to represent conceptual objects (e.g., trees, buildings, counties), but they can also represent ...
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 ).
The schema defines data and metadata tables with specified definitions, integrity assertions, format limitations and content constraints. [ 9 ] The GeoPackage standard describes a set of conventions (requirements) for storing vector features, tile matrix sets of imagery and raster maps at various scales, schema and metadata.
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]
This schema describes the object types whose data the community is interested in and which community applications must expose. For example, an application for tourism may define object types including monuments, places of interest, museums, road exits, and viewpoints in its application schema. Those object types in turn reference the primitive ...