MemSQL’s distributed in-memory database is capable of providing JSON analytics for delivering a consolidated view across structured and semi-structured data, including standard enterprise and social media data.
This feature will allow organizations to combine two disparate data sources to derive valuable input for operational analytics, network security, real-time recommendations and risk management.
Eric Frenkiel, CEO of MemSQL said, “With support for JSON, our distributed in-memory database is poised to have the same effect on databases that VMware had on servers.”
JSON or Java Script object notation is the syntax that is used for storing and exchanging semi-structured data from social-media networks such as Facebook, Twitter (News - Alert) and Instagram. This information is not being used in conjunction with structured data, thereby providing an incomplete view of entire customer bases of companies.
Also, the NoSQL databases used these days can offer support for JSON including the querying and parsing of JSON structures. However real-time analytics inputs are minimal. But SQL does not provide native support for JSON which delays the data query process of popular data types. Organizations are not able to leverage real-time, big data analytics because of such a lack of integration.
Zynga (News - Alert), Morgan Stanley, and Shutterstock are using MemSQL in production environments, which support thousands of nodes and huge volumes of data in the range of terabytes. MemSQL enables these organizations to leverage real-time data to make informed decisions and engage customers more ideally and also identify competitive advantages.
The presence of JSON analytics helps the company to consolidate the database market and avoid dependence on other middleware solutions.
“By setting the foundation for database consolidation, organizations will soon reap the benefit of lower total cost of ownership and achieve significant efficiency gains by eliminating the difficulty of moving data around. In fact, our ability to combine structured and semi-structured data together could dramatically impact the need for NoSQL in the future,” Frenkiel added.
MemSQL’s in-memory database features improved index scan performance; online ALTER table; online point-in-time backup store and restore; and better improved SQL and subquery support for distributed query execution.
Research conducted by IT market research firm enterprise strategy group (ESG) reveals that MemSQL delivers outstanding performance and linear scalability, superior reliability and durability, and the ability to support rapid data growth. ESG Lab performed the assessment via hands-on tests with a data set and queries designed to emulate real-world applications. This establishes MemSQL’s distributed in memory database as the standard for real-time, big data analytics.