2024-12-23 01:23:48
Author: SequoiaDB / 2023-07-25 15:52 / Source: SequoiaDB

SequoiaDB Listed in KPMG's "China's Leading Financial Technology 50 Enterprises"

GUANGZHOU,China,Feb. 27,2023 -- On January 16,the "2022 KPMG China Fintech Enterprises 50" event was held simultaneously online and offline in Beijing,Shanghai,and Shenzhen. SequoiaDB has been successfully selected as "2022 China's Leading Financial Technology 50 Enterprises".

SequoiaDB Listed in KPMG's "China's Leading Financial Technology 50 Enterprises"


SequoiaDB Listed in KPMG's "China's Leading Financial Technology 50 Enterprises"

The list selects companies based on core dimensions such as science and data,innovation and change,popularization of financial services,capital market recognition,and industry development foresight. After several months of evaluation,KPMG fully recognized the achievements of SequoiaDB in breaking through the pain points of traditional financial services with technology,making SequoiaDB the only distributed database vendor selected on the list.

In KPMG's report,it proposed that traditional relational databases will gradually transform into stream-batch integration,lake-house integration,AI-integration,and self-service big data analysis and mining architecture. The unified management and control of semi-structured and unstructured data is conducive to building shared and open data layer storage. At the same time,KPMG predicts that Fintech architecture will gradually evolve towards the organic integration of centralized and distributed.

Faced with the big data stored in the financial and banking industry,SequoiaDB uses its original engine-level multi-mode architecture to realize multi-mode data integration management capabilities and cross-engine ACID consistency,and provides a cloud service architecture that separates storage and computing. The system can be expanded on demand to achieve multi-data center disaster recovery and cross-cloud platform deployment. It also provides Multi-Master multi-master node cluster expansion capabilities.

At the same time,the computing layer and storage layer can be independently scaled out,which is more conducive to micro-services and data centers. The innovative development of modernization realizes hybrid multi-mode data storage and high-concurrency query and processing of massive data on the same database system.

SequoiaDB is driven by the new "Data-Core" to achieve effective and accurate data processing. It has been used by more than 100 financial bank customers on a large scale,covering state-owned banks,joint-stock banks,provincial rural credit cards,city commercial banks,Insurance,securities and other financial customers have provided over millions of people with the data support behind finance,travel and life.

Since its release in 2016,the selection of "KPMG China's 50 Leading Financial Technology Enterprises" has been successfully held for seven consecutive sessions. Focus on scientific and technological innovation in the field,promote industry interaction and communication,and promote the development of financial technology.

Over the past ten years,SequoiaDB has been focusing on the financial and banking industry. Based on its deep understanding of the industry,it has continuously strengthened its core capabilities,provided the financial and banking industry with self-developed high-quality products,and created a high-standard benchmarking effect.

At present,SequoiaDB has officially produced the largest running cluster in the system,with a data volume of 1.4 trillion rows,a capacity of 3PB,and a scale of more than 500 servers. The customer who has been stably producing and running SequoiaDB for as long as 8 years. In the future,SequoiaDB will continue to deepen the financial and banking industry,enhance the core competitiveness of products,achieve breakthroughs in cutting-edge technology,and continue to empower the digital transformation and development of financial institutions.

SequoiaDB Listed in KPMG's "China's Leading Financial Technology 50 Enterprises"

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Tags: Banking/Financial Service Computer/Electronics Data Analytics Financial Technology

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