GBASE Debuts at the 4th Gen Intel® Xeon® Scalable Processor Launch

Published on 2023-01-30

 

On January 11, Intel (China) Co., Ltd. successfully held the "Chip Acceleration, Going Far" — 4th Gen Intel launch event. GBASE (General Data Technology), as Intel's long-term strategic partner, jointly launched the GBase 8a large-scale distributed massively parallel processing (MPP) database cluster solution. Zhang Shaoyong, General Manager of GBASE's Data Intelligence Product Division, was invited to appear at the Intel ecosystem launch ceremony and together lit the way for chip-accelerated innovation.

Intel Ecosystem Launch Ceremony

At this event, Intel joined hands with 49 ecosystem partners to launch the 4th Gen Intel® Xeon® Scalable Processors, and brought in-depth technical analysis of the new products, industry solutions, and success practice sharing, directly addressing the pain points and challenges in enterprise digital transformation.

About GBase 8a MPP Cluster Database

GBase 8a MPP Architecture Diagram

GBase 8a MPP Cluster is a distributed database cluster system independently developed by GBASE (General Data Technology). It offers significant performance advantages over traditional databases, supporting datasets ranging from terabytes to tens of petabytes, and enabling concurrent access for over 300 users. I/O wait time can be as low as 10% of that in conventional databases, and data analysis speed can be over 10 times faster.

In terms of scalability, each server in GBase 8a MPP Cluster uses local resources and builds on a peer-to-peer flat architecture, providing excellent horizontal scalability. The cluster’s computing performance and storage capacity scale nearly linearly as the cluster expands, and the entire expansion process requires no business downtime.

GBase 8a MPP Cluster features a new columnar storage engine, high data compression ratios, maintenance-free coarse-grained indexes, and many other big data processing technologies and features. Combined with MPP’s efficient distributed computing model and a cost-based distributed intelligent optimizer, GBase 8a MPP Cluster can support petabyte-scale structured data analytics applications. Additionally, through intra-cluster replica synchronization, active-active cluster technology, cross-region data transmission synchronization, and virtual cluster technology, the system ensures high availability and multi-cluster support for big data, enabling deployments across multiple data centers.

Harnessing the Advantages of Intel® Xeon® Scalable Processors for High-Performance, Highly Scalable, and Highly Available Database Solutions

The Intel® Select Solution based on GBase 8a MPP Cluster can help data-intensive industries improve data analytics performance and significantly shorten application response times. By leveraging select Intel® Xeon® Scalable processors, the solution fully unlocks the performance potential of GBase 8a MPP Cluster while delivering excellent total cost of ownership (TCO). Enterprises can build their GBase 8a MPP Cluster solution using verified and tested Intel® Xeon® Scalable processors. The solution covers both hardware and software, and has undergone extensive compatibility and stability validation, helping organizations significantly reduce upfront selection and testing costs and achieve rapid system deployment. For businesses seeking greater flexibility in large-scale distributed database systems, this solution provides a highly detailed reference architecture. Even if the cluster involves hardware from multiple vendors or requires future replacement of hardware vendors, customers can still freely scale and choose based on this configuration framework.

GBASE will continue to partner with Intel to create even more valuable joint solutions, empowering users in finance, telecommunications, energy, and other industries to efficiently process massive volumes of structured data, confidently tackle complex business environments and database challenges, safeguard critical operations, and lay a solid foundation for digital transformation.