In 2019, we will enter a critical period of digital transformation.

The so-called "troubleshooting period" is the digital transformation 2.0 stage, which requires tackling the issues of cloud migration and digital transformation of key business operations of enterprises.

A report by market research company IDC pointed out: Since IDC proposed digital transformation in 2014, it has seen that companies have invested a lot of manpower and material resources in digital transformation, but the results are not ideal. Some companies have successfully stood at the forefront of the trend.

, some companies are moving upstream, and some companies can only move forward passively in the wave.

For enterprises, digital transformation is a long road ahead.

IDC believes that at the current stage, what enterprises urgently need to solve is the improvement of digital capabilities, including: in-depth integration with business capabilities; data processing and mining capabilities; and IT technology operation and management capabilities.

Especially data processing and mining capabilities, because digital transformation promotes the transformation of enterprises from process-centered to data-centered, the ability to process and mine massive, heterogeneous, and multi-type data is the prerequisite for releasing the value of data, and the entire life of data

Periodic control and governance are the guarantee for releasing the value of data.

As digital transformation introduces a large number of new technologies, IT complexity becomes higher. Enterprise IT technical operation and management capabilities are the key to improving enterprise "IT productivity".

To tackle the "big road" of digital transformation, we need a digital platform with three major characteristics: integration, intelligence, and inheritance.

This is the view put forward in the white paper "Embracing Change and Outsmarting the Future—Digital Platforms Disrupt Enterprise Digital Transformation" jointly launched by Huawei and IDC in March 2019.

Integration mainly refers to the combination of traditional technologies and innovative technologies; intelligence mainly refers to platform intelligence and intelligent capability output; inheritance mainly refers to the architecture created by concepts such as decoupling, function reuse, and configurability.

Carrying these three major perspectives is the new generation of distributed enterprise-level technology.

On May 15, 2019, Huawei released the industry's first new-generation intelligent distributed database GaussDB and distributed storage FusionStorage 8.0 that support ARM architecture. As a new generation of data infrastructure, Huawei explains the three major characteristics of integration, intelligence, and inheritance.

digital platform.

Wang Tao, Huawei's Managing Director and President of ICT Strategy and Marketing, said at the press conference that various industries are accelerating the process of intelligence, and more and more companies have realized that data infrastructure is the key to the success of intelligence.

Huawei is redefining data infrastructure around the three fields of computing, storage, and data processing to accelerate the move into the intelligent era.

Behind the concepts such as cloud and industrial Internet discussed today is the arrival of a new era, which is the great migration of system architecture.

Traditional enterprise-level technology is used in single applications and stand-alone environments to ensure high reliability, high availability, and high stability of data storage, calling and other operations, especially to meet the ACID (atomicity, consistency, isolation, and isolation) requirements for financial-level transaction processing.

Durability) requirements to provide data management support for key business operations of the enterprise.

As enterprise technology migrates to cloud architecture, database technology is also facing transformation.

In 2018, distributed databases based on cloud computing technology became a hot topic in the industry.

To simply understand, cloud computing technology replaces the "stand-alone" environment with a distributed computing environment composed of X86 server clusters.

The computing tasks that were originally completed by several minicomputers need to be distributed to hundreds or even thousands of X86 servers, and may also be operated across data centers. The challenges can be imagined.

In particular, financial-level services such as online payments cannot make mistakes when the network is disconnected or have problems with the network connection, nor can the user experience be affected by slow response speeds.

In August 2018, the China Payment and Clearing Association and the China Academy of Information and Communications Technology jointly held the "Financial Distributed Transaction Database Seminar" to discuss the path to distributed transformation of core databases with industry manufacturers and users. At the same time, they released the "Financial Distributed Transaction Database Seminar"

Distributed Transaction Database" white paper.

The advancement of the financial distributed transaction database provides industrial support for distributed databases to enter key business systems of enterprises.

As an enterprise ICT solution provider, Huawei began to develop a data warehouse for big data analysis as early as 2012. Based on the traditional relational database SQL engine and strong transaction consistency, Huawei has carried out distributed and parallel computing.

The transformation took 6 years to create a distributed database for petabyte-level massive data analysis.

In addition to the OLAP data warehouse, Huawei has cooperated with industry users to develop distributed transaction databases for OLTP.

In 2017, Huawei and China Merchants Bank jointly established a distributed database joint innovation laboratory to develop a high-performance enterprise-level kernel, fully support distributed transactions, meet the financial industry's strong data consistency requirements, and have a single-machine transaction processing capability of up to 100 transactions per minute.

Ten thousand level OLTP distributed database.

The new GaussDB database products released this time include: online transaction processing OLTP database, online analytical processing OLAP database, and hybrid transaction and analysis processing HTAP database.

Huawei's GaussDB database integrates AI technology into database design, development, verification, tuning, operation and maintenance, etc., and can realize AI-based self-tuning, self-diagnosis, self-healing, and self-operation and maintenance, making the database more efficient and intelligent, leading the way.

Development of database architecture.