RainStor, whose database solution runs natively on Hadoop and provides massive scalability, has received two U.S. patents for its Big Data technology.
One of the biggest ironies of Big Data storage is that most of the database platforms at its core were designed well before the Big Data era. RainStor, a database vendor with an unusual history, says it is changing that by creating "built for Big Data" database technology. This week, it obtained two major U.S. patents to advance that mission.
The story behind RainStor's database platform, unlike those for MySQL and other popular databases, starts with the British military, which in the early 2000s developed a database platform from scratch to store field operations information efficiently. RainStor's technology grew out of that code, and focuses on "the sole purpose of efficiently storing large volumes of data and always being available for query," according to the company.
On July 23, RainStor announced the acquisition of two patents in the United States. The first is a database archiving patent that covers "how the RainStor technology efficiently stores all historical data, which could be sourced from a relational, transactional or other database type, yet still makes the data available for query at any time."
The second patent deals with schema changes and "describes RainStor’s unique capability to allow for multiple system changes occurring on the source database system, such as the addition of new fields and tables. Rainstor supports these schema changes while still providing the ability to run accurate point-in-time query and reporting, across huge data volumes," RainStor said in a statement.
In many senses, the database wars are only just beginning, as advocates of MySQL and other traditional platforms vie for a share of the market with the growing array of newer NoSQL-type systems. The proprietary nature of RainStor's technology may give some enterprises pause, but with native support for Hadoop and broad scalability, however, the company's database solution already has important advantages for Big Data applications.