11/7/2022 0 Comments Cran.r-project.org sparktable![]() ![]()
Package is an implementation of R's DBI interface using JDBC as a back-end. , an open source distributed SQL query engine for running interactive analytic queries against data sources of all sizes ranging from gigabytes to petabytes. Package implements a DBI-compliant interface to , which is a low-level, high-performance interface that is designed specifically for relational data stores. #Cran.r project.org sparktable driversPackage provides a DBI-compliant interface to drivers of #Cran.r project.org sparktable series, a time series database designed to handle high write and query loads. , a high performance analytics data store for event-driven data. Package on GitHub provides the interface to , Google's fully managed, petabyte scale, low cost analytics data warehouse. ![]() Package provides temporary and permanent message queues for R, built on top of SQLite. Package is a simple key-value database using SQLite as the backend. Package embeds the SQLite database engine in R and provides an interface compliant with the DBI package. , a self-contained, high-reliability, embedded, full-featured, public-domain, SQL database engine: Package provides convenience functions to query and browse a database through the , an open-source parallel database on top of PostgreSQL. Provides a fully DBI-compliant interface to Package provides the interface to its spatial extension Package both provide fully DBI-compliant Rcpp-backed interfaces to PostgreSQL. A modern MySQL client based on Rcpp is available from the RMariaDB package we listed above. #Cran.r project.org sparktable codeNote that this is the legacy DBI interface to MySQL and MariaDB based on old code ported from S-PLUS. Package provides a DBI-compliant interface to Package provides access to databases through an ODBC interface. It's worth noting that some packages try to follow this interface definition (DBI-compliant) but many existing packages don't. ![]() Package provides a database interface definition for communication between R and relational database management systems. This section includes packages that provides access to relational databases within R. Last but not least, thanks to Achim Zeileis who helped me get started on organizing this task view. Thanks to Dirk Eddelbuettel who made the initialįile and the Markdown conversion script available at the Github repository of CRAN Task View for High Performance Computing Suggestions and corrections by Achim Zeileis, Kirill Müller, Hannes Mühleisen, Rich FitzJohn, Dirk Eddelbuettel, and Hadley Wickham (as well as others I may have forgotten to add here) are gratefully acknowledged. #Cran.r project.org sparktable updateRespectively, installation or update of packages from a given Task View Ĭan restrict operations to packages labeled as The content presented in this Task View are undergoing rapidĬhanges in industries and academia. If there are changing requirements in the applications, non-relational databases can be much easier to use and manage. Users generally don't need to define the data schema up front. Non-relational databases became popular in recent years due to huge demand in storing unstructured data with the use ofĪs the query language. you have a user who users your softwares and those softwares have creators and contributors. ![]() To express the logic for writing and querying data. The data in relational databases is modeled as rows and columns in a series of tables with the use of Instead, people nowadays tend to store data in databases for more scalable and reliable data management.ĭatabase systems are often classified based on theīecame dominant in the 1980s. This does not include data import/export or data management.Īs datasets become larger and larger, it is impossible for people to save them in traditional file formats such as spreadsheet, raw text file, etc., which could not fit on devices with limited storage and could not be easily shared across collaborators. This CRAN task view contains a list of packages related to accessibility of different databases. ![]()
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