m
Our Mission Statement
This is Photoshop's version of Loremer Ipsn gravida nibh vel velit auctoregorie sam alquet.Aenean sollicitudin, lorem quis bibendum auci elit consequat ipsutis sem nibh id elit.
Follow Us
Top
Real-time Analytics | VoltDB
6338
page-template-default,page,page-id-6338,page-child,parent-pageid-6218,mkd-core-1.0,highrise-ver-1.0,,mkd-smooth-page-transitions,mkd-ajax,mkd-grid-1300,mkd-blog-installed,mkd-header-standard,mkd-sticky-header-on-scroll-up,mkd-default-mobile-header,mkd-sticky-up-mobile-header,mkd-dropdown-slide-from-bottom,mkd-dark-header,mkd-header-style-on-scroll,mkd-full-width-wide-menu,mkd-header-standard-in-grid-shadow-disable,mkd-search-dropdown,mkd-side-menu-slide-from-right,wpb-js-composer js-comp-ver-5.2.1,vc_responsive
 
VoltDB / Why VoltDB? / Real-time Analytics

Real-time Analytics

Real-time analytics applications often provide a summary of an incoming data stream. These applications are used to discover real-time insights from fast flowing data produced by social media, mobile devices, sensors, connected IoT devices, infrastructure, and more. VoltDB offers high speed transactional ACID performance and the ability to process thousands to millions of discrete incoming events per second.

Learn More about Real-time Analytics
in our Max CDN Case Study

Real-time Analytics and VoltDB

Implementing VoltDB to handle fast ingestion of data and interact on data to perform real-time analytics provides the ability to create applications that can make data-driven decisions on each event as it enters the data pipeline.

Real-time Analytics Decision Engine

VoltDB enables real-time SQL analytics against fast streams of data. VoltDB analytics use cases fall into three categories: moving windows and aggregation of real-time data for BI dashboards and external applications; per-event analytics to detect fraud or enforce policy; and caching of OLAP analytics to scale high concurrency querying and serving.

Get the VoltDB Technical Overview