KALEAO solutions for Data Analytics

Leverage KALEAO’s high speed all flash architecture and low energy architecture to harness the enormous volume and variety of big data assets in the most efficient and cost effective way.  
KALEAO’s solutions for data analytics enable faster decision making, actionable insight discovery and better predictive business planning.

The Kaleao advantage

 

HIGH SPEED PERFORMANCE (>10M IOPS PER 3U CHASSIS)

HIGH CAPACITY (370 TB PER 3U CHASSIS)

REDUCE STORAGE FOOTPRINT

ELIMINATE MANAGEMENT SILOS
 

PREDICTABLE SCALE

LEVERAGE A PREVALIDATED PLATFORM

EASE OF MANAGEMENT

LOW POWER CONSUMPTION
 



Tame the data animal

At the dawn of the zettabyte era, the proliferation of data coming from the web, connected devices and IoT converge to redefine the market place . To tame the data animal, organizations need to approach next generation data analtycs, with the benefit of more agility and operational efficiency.

Finding trends, actionable insights or new business opportunities from large datasets requires rethinking of not only the application stack, but also the compute and storage infrastructure. KALEAO systems enable a true converged software defined hardware accelerated infrastructure that obtains performance equivalent to bare metal deployments from virtualized big data installations.

This is combined with the advantage of high density and best in class energy efficiency, factors that contribute to further reduce TCO.
 
 


Leverage true convergence

 

KALEAO’s true converged servers and appliances are the first 64-bit ARM based all-flash systems to integrate storage, servers, networking and lean virtualization into a single system, simplifying deployment and management and obtaining high performance and energy efficiency. Unlike other hyperconverged solutions, KALEAO avoids expensive software licenses, keeping convergence at hardware level for higher performance while maintaining flexibility and agility.
 
Unlike other servers and converged solutions, KALEAO has unique hardware design traits like the feature to free CPU from storage virtualization and management. This allows costly data path operations like data replication to remote SSDs, or data copies for volume snapshots to be handled by dedicated active components thus maximizing compute CPU cycles available to useful application tasks.