ITTIA updates DB SQL for Big Data | Automation.com

ITTIA updates DB SQL for Big Data

April 30, 2014 - ITTIA updated DB SQL to store a large volume of data in-memory for processing and analysis. Applications use this technology to find specific details in a very large data set and perform complex queries in seconds.

Storing and retrieving large amounts of data constitutes an important aspect of managing any business. Decision-makers are constantly challenged to extract insight from real-time data to increase productivity. This is even more true when there is no obvious way to organize the data for efficient search. For example, when an airline company announces new rates, the immediate impact of that decision can easily be lost in the sea of information that is collected globally.

To solve this challenge, ITTIA DB SQL offers a powerful in-memory data storage solution that enables developers and decision-makers in sectors such as network appliances, enterprise infrastructure, and healthcare to search for key data points in hundreds of millions. By leveraging systems with tens or even hundreds of gigabytes of RAM, ITTIA DB SQL can process millions of rows in a matter of seconds. Application developers use SQL to express queries that search for relevant records, aggregate the results, and calculate important statistics with a predictable, real-time response.

Another application for in-memory data storage is a social media website. For example, to quickly locate people with similar interests, relevant data can be cached in a memory database that is continuously updated as new members join the site and update their profiles. By filtering and scanning these records, ITTIA DB SQL can find and list relevant members for each page view.

To test these scenarios, ITTIA's engineering team successfully queried an in-memory database containing over a hundred million records, completing a substring matching search in a matter of seconds. The results of this benchmark show that in-memory performance allows companies to access critical data efficiently, and analyze that data for further decision-making and market evaluation – which can translate directly into increased productivity. At the same time, the popularity of SQL makes it an easy tool to maintain and facilitates interoperability with other embedded systems, devices, and the cloud.

 

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