Overview

One of the most important characteristics of Big Data is access to structured and unstructured information. Through MATLAB it is possible to access large data sets from non-relational and relational databases. Likewise, you can access numeric, text and graphic information, regardless of their original format. Another important feature of Big Data is the implementation of parallel computing and multi-processing for simultaneous access of several users to the same database. MATLAB lets you access multiple databases simultaneously within a single sesion and enables segmented import of large data sets using DatabaseDatastore. You can Split SQL queries and parallelize access to data. In this way, the work with large distributed databases is implemented. MATLAB supports relational databases like Oracle, SAS, MySQL, Microsoft SQL Server, Microsoft Access, and PostgreSQL. You can create, query, and manipulate native SQLite relational databases without additional software or database drivers. MATLAB also supports nonrelational databases like Neo4j and MongoDB. The Neo4j interface lets you access data stored as graphs or queried using nongraph operations. The NoSQL database interface to MongoDB provides access to unstructured data. Search the Neo4j graph database using functions provided by the MATLAB interface toNeo4j. You can explore the graph data or perform graph network analysis using MATLAB directed graphs. To analyze your data using SQL in MATLAB without access to a database or driver, use the MATLAB interface to SQLite. After installing Database Toolbox, you can use theMATLAB interface to SQLite to move data between MATLAB and a SQLite databasefile. The SQLite connection is different from a database connection created using a JDBCdriver. MATLAB performs the above tasks through functions and apps provides in Database Toolbox.

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