13 docs tagged with "User Case"

Author: Zhang Yujie, Database Engineer with BOSS Zhipin

Feng Guangpu, head of the Dmall database team, is responsible for the stability of OceanBase, TiDB, MySQL, Redis, and other databases of Dmall and the construction of its database platform as a service (PaaS) model. Feng has a wealth of experience in multi-active database architecture and data synchronization schemes.

Background

About the author: Bao Guiming, Senior Big Data Engineer at KUAYUE EXPRESS (KYE), works on the research and introduction of real-time data R&D platforms and data lakes. Focusing on advancing the best practices and solutions of real-time/offline data warehouse architectures, Bao is committed to providing his company with accessible and efficient big data infrastructure systems, such as real-time computing systems and data lakes.

Introduction: AXA SPDB Investment Managers Co., Ltd. (AXA SPDB), a Sino-French joint venture fund company established in 2007, requires easy-to-use and efficient business data management tools that deliver high storage performance, ensure quick response, and support real-time data processing. As the original Oracle + Cloudera Distributed Hadoop (CDH) solution could not meet its expectations, AXA SPDB sought to optimize its database architecture and evaluated OceanBase Database, TiDB, Hive, and Oracle. After comprehensive comparisons and tests, the company decided on OceanBase Database. In this article, the technical development department of AXA SPDB shared their experience in database selection.

About the author: Liu Qiang, a member of Zuoyebang's infrastructure database administrator (DBA) team, works on the exploration and implementation of distributed databases. He collaborates with the R&D team in promoting the deployment of distributed databases in Zuoyebang's business system.

Introduction: This article is based on the speech made by Zhang Jie, Big Data Architect of KUAYUE EXPRESS (hereinafter referred to as KYE), at the DTCC conference. The speech introduced the pain points faced by KYE in data analysis and the company's ideas and practices in the development of its query engine solution.

About the author: Ji Haodong, head of the database division at Momo, part of the Hello Group. He is now responsible for the database teams of Momo and Tantan and the database storage and operation throughout the Hello Group. He has a wealth of professional experience and practical know-how in the fields of large-scale data source stability construction, team building, cost optimization, and IDC migration.

As a platform serving tens of millions of monthly active users (MAU), E-surfing Pay not only provides a variety of everyday life services, but also needs to store and process relevant data. Due to issues with its original database solution, such as insufficient storage space, high analysis latency, difficulties in cost control, and increased O&M complexity, the company must replace the original database architecture with a new one to ensure the long-term business stability.

Kwai is a short video app boasting more than 10 million daily active users. How does it efficiently process highly concurrent user requests? Kwai once deployed multiple MySQL clusters in the backend to support high traffic with large data storage and satisfactory performance. What are the weak points of this conventional sharding solution? What pushed Kwai to select distributed databases and eventually deploy OceanBase Database? In this post, Xiaochong, the head of Kwai's O&M team, shared the team’s reflection and experience in implementing the OceanBase Database solution.

Introduction: This article introduces Sichuan Hwadee's practice of migrating its data computing platform from Hadoop to OceanBase Database. This case demonstrates the advantages of OceanBase Database in terms of performance and storage costs. With OceanBase Database, hardware costs are reduced by 60% and the O&M work is significantly cut down, relieving maintenance personnel from responsibility for the many Hadoop components. OceanBase Database enables Hwadee to meet the needs of hybrid transaction/analytical processing (HTAP) scenarios with just one system, simplifying O&M for the company.

Che Dongxing: Currently employed at Sunshine Insurance, Che has been working in the IT field within the insurance industry for 12 years, and has acquired profound knowledge of IT infrastructure practices in this industry. Also, he is familiar with various database products, and has great experience in database O&M.

Introduction: As Yonyou Network Technology (Yonyou) grows, it uses XXL-JOB as the task scheduling platform and Nacos as the configuration management center to standardize and automate IT O&M. However, the underlying MySQL system seemed to be increasingly overburdened in coping with more and more clusters built for XXL-JOB and Nacos. To relieve its O&M workload, the company started looking for a database that can manage all its clusters with high availability in a unified way. In this article, Yonyou's database administrators shared their story of database selection.