There are more choices than ever in the data management market and, in the view of some industry observers, we now have an increasingly specialized market, providing a wide range of options to manage data that continues to grow in volume, variety, and velocity.
While new and bigger data environments may seem complex, the objective is always simply to exploit data for decision making. Column-oriented relational databases - which store data in columns rather than in rows - were developed in the 1990s.
In answer to exploding data volumes and the need for more ad hoc queries, which can slow response times, in-memory databases provide a way to improve query speed and reduce overhead in terms of data storage and retrieval for data warehouses and other read-intensive applications.
Similar to in-memory database technologies, columnar databases are used in verticals where data analysis speed is of critical importance such as financial services, retail, and telecommunications.
This columnar database approach is deployed with other features and capabilities - such as MPP architecture, rapid loading capabilities, and data compression in order to support high performance in BI, analytics and data warehousing for large datasets.
HERE ARE THE WINNERS OF THE 2015 DBTA READERS' CHOICE AWARDS FOR BEST COLUMNAR DATABASE
Winners' Circle by Colin Mahony, Sr. Vice President & General Manager
In our Idea Economy, data-driven organizations are thriving by creating new products and services that are trans-forming and often disrupting entire industries. This applies as much to start-ups as to traditional large enterprises that must combine vision with technological agility to turn ideas into reality or risk falling behind, and worse yet, become completely irrelevant...read on.