In-memory databases and grids have entered the enterprise mainstream. Today, new offerings are emerging in many forms—from extensions of relational database management systems to NoSQL databases to cloud-hosted NoSQL databases.
As data stores grow larger and more diverse, and more focus is placed on competing on analytics, processing data faster is becoming a critical requirement.
In-memory databases and technologies enable decision makers to get to the information they are seeking rapidly and more readily. These fast databases also are opening up enterprise data to new questions that decision makers have never been able to ask before on their slower, more cumbersome systems.
What’s changed? While in-memory technology has been on the market for many years, recently the price of memory has dropped to the point where processing data in RAM compares favorably to moving it in and out of disks.
There are also growing business demands for real-time analysis and insights that make in-memory a compelling option. Enterprises increasingly seek real-time capabilities, as well as the ability to manage information coming in from the emerging Internet of Things. As a result, in-memory is being actively deployed across many enterprises today— from online ad placement to financial trading to production systems.
HERE ARE THE WINNERS OF THE 2015 DBTA READERS' CHOICE AWARDS FOR BEST IN-MEMORY DATABASE
Winner:
SAP HANA
Finalists:
Oracle Database 12c
jBoss Data Grid