Implementing Columnar Databases With R
With the growing data volume, we are now facing use cases where data stored on disk, as files, is too large for the systems to handle and manage, and needs to be stored outside of the system, in a database, so that one can connect to the database, when needed, to retrieve only the chunks needed for the current analysis. This paper tries to solve the problem where a system or application, built over R, can communicate to a database with massive data volume, residing on a remote system, to retrieve only the chunks of data needed for current analysis to gain scalability and speed by leveraging the data management and querying speed of the databases.
Explore more tags from this article
About the Author(s)
Manikant Prasad
Contact us
We’re here to help you break through complex challenges and achieve next-level success.
Implementing Columnar Databases With R
This paper tries to solve the problem where a system or application, built over R, can communicate to a database with massive data volume, residing on a remote system, to retrieve only the chunks of data needed for current analysis to gain scalability and speed by leveraging the data management and querying speed of the databases.