{"id":21186,"date":"2024-09-29T23:48:53","date_gmt":"2024-09-30T06:48:53","guid":{"rendered":"https:\/\/www.pingcap.com\/?post_type=case-study&p=21186"},"modified":"2024-10-06T20:29:04","modified_gmt":"2024-10-07T03:29:04","slug":"flipkart-transforming-database-management-and-reducing-complexity-with-tidb","status":"publish","type":"case-study","link":"https:\/\/www.pingcap.com\/ko\/case-study\/flipkart-transforming-database-management-and-reducing-complexity-with-tidb\/","title":{"rendered":"Flipkart: Transforming Database Management and Reducing Complexity with TiDB"},"content":{"rendered":"
Flipkart, India’s largest e-commerce company, serves over 400 million users and facilitates over 10 million daily page visits. With Walmart as its majority stakeholder, Flipkart is known for its robust operations, handling over 8 million monthly shipments across 22 warehouses. During its annual shopping festival, “The Big Billion Days,” Flipkart manages billions of visits and achieves billions in gross merchandise value (GMV). Flipkart maintains an extensive MySQL fleet spanning 700 clusters to support its massive operations.<\/p>\n\n\n\n
<\/span>The Challenge: Flipkart\u2019s Growing MySQL Crisis<\/span><\/h2>\n\n\n\n
Massive applications and services generate petabytes of data in various types and formats. Flipkart\u2019s tech stack (MySQL, Redis, and Aerospike) became ever more complex to process and store this amount and variety of data. However, as its business kept growing, the previous database solutions started to hit their limits, posing three significant challenges:<\/p>\n\n\n\n
\ud655\uc7a5\uc131<\/h3>\n\n\n\n
With over 400 applications and thousands of microservices, Flipkart\u2019s MySQL setup spanned more than 700 clusters, managing petabytes of diverse data. As traffic and data loads increased, the MySQL clusters struggled to handle the continuously growing throughput. Adding more nodes or re-sharding data was time-consuming and complex, resulting in operational bottlenecks. This inability to scale efficiently became a major roadblock to business growth, especially during high-traffic events like their shopping festivals, when systems needed to accommodate massive spikes in user activity.<\/p>\n\n\n\n
Reliability<\/h3>\n\n\n\n
High reliability was critical, particularly during shopping events with billions of dollars in GMV. The MySQL fleet required constant monitoring to ensure stability across clusters. With such a complex setup, any single-node failure had the potential to impact customer experience significantly. The system\u2019s resilience was under constant strain, requiring frequent failover coordination. However, MySQL struggled to meet the high availability demands, especially in disaster scenarios like node or region failures. A database outage could result in substantial losses and customer dissatisfaction, even for a few minutes. <\/p>\n\n\n\n
Operational Efficiency<\/h3>\n\n\n\n
Managing such a vast MySQL fleet was becoming increasingly costly and inefficient. Flipkart\u2019s MySQL architecture comprised multiple shards, each requiring its own master, read replicas, and failover replicas, leading to operational complexity. Monitoring and maintaining the health of these shards, ensuring replication across clusters, and handling data consistency became a logistical nightmare. In addition, the rising costs associated with keeping this infrastructure were unsustainable. Flipkart needed a solution that simplified management and reduced the operational costs of handling data at such a scale.<\/p>\n\n\n\n
<\/span>The Solution: TiDB\u2019s Scalable and Reliable Database Transformation<\/span><\/h2>\n\n\n\n
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