GCash is the leading finance super app in the Philippines, operated by Mynt, a fintech company backed by Globe, Ayala, and Ant International. Since its launch in 2004, GCash has grown into one of the country’s most widely used digital financial platforms, providing a broad range of mobile-first services, including payments, transfers, and other digital financial solutions.
As GCash scaled, the pressure on its legacy MySQL-based data infrastructure increased sharply. Rapid data growth, rising storage costs, operational complexity, and sensitivity to traffic spikes made it harder for the platform to support continued business growth efficiently. To address these challenges, GCash adopted OceanBase to modernize its payment data foundation.
With OceanBase, GCash consolidated hundreds of legacy MySQL instances into a smaller number of distributed clusters, reduced storage usage, improved operational efficiency, and strengthened high-availability protection for critical payment services.
The Challenges
By the end of 2020, GCash's data volumes were growing at roughly 10% per month, and the MySQL cloud databases underpinning its payment platform were hitting hard limits.
Meanwhile, the DBA team was stretched thin managing hundreds of MySQL instances. Routine maintenance tasks like data sharding, tablespace reorganization, and cleanup consumed significant engineering time without solving the underlying scalability problem.
Rising infrastructure and operational costs
GCash was processing more than one million transactions a day, while data volume in the legacy system was growing by roughly 10% each month. Because of MySQL cloud database specification limits, storage expansion often required CPU upgrades as well, leading to inefficient resource allocation and increasing monthly infrastructure costs.
Architecture limitations created availability risk
As data accumulated, weaknesses in the MySQL-based architecture became increasingly exposed, particularly in core payment and transaction systems. Stability issues that were manageable at a smaller scale , needed to be addressed to ensure continuous, uninterrupted business operations as the platform continued to grow.
Need for greater performance under traffic surges
GCash's payment system regularly faced traffic spikes where thousands of concurrent SQL requests arrived in milliseconds. The legacy MySQL cluster supported a limited number of connections and was highly sensitive to high-concurrency SQL requests. Even small increases in latency could directly affect the payment experience for end users.
The Solution
GCash adopted OceanBase because it combined distributed scalability, strong MySQL compatibility, tenant-based consolidation, and multi-zone high availability in a single platform. OceanBase worked with GCash on a transformation centered on migration, consolidation, and resilience.
Zero-downtime migration and data compression
OceanBase used OceanBase Migration Service (OMS) to support a smooth migration from the source databases to the new environment. The migration approach synchronized incremental data, connected applications to the target system, and enabled the transition with zero downtime. At the same time, . OceanBase's LSM-tree-based storage engine then applied lossless compression to the migrated data — reducing each database's footprint to roughly one-tenth of its original MySQL size.
Consolidation through multitenant architecture
OceanBase Cloud's multi-tenancy capability allowed GCash to consolidate hundreds of MySQL instances into approximately 10 OceanBase clusters. This enabled resource pooling while isolating workloads for core and general business systems in different clusters. As a result, instability in one cluster would affect only a limited portion of the overall database system instead of propagating more broadly.
A Three-Zone High Availability Architecture
OceanBase deployed a three-zone high-availability architecture to improve resilience for core payment services. This architecture helps maintain service continuity even if one zone fails. After the migration, the number of connections supported by a single OceanBase node was approximately 5 to 8 times that of the legacy MySQL database, and a multi-node cluster provided much stronger capacity to absorb traffic spikes.
The Results
Since migrating to OceanBase Cloud, GCash has achieved measurable improvements across cost efficiency, operational simplicity, and resilience:
- 70% reduction in total data storage, 40% lower costs. OceanBase's LSM-tree compression reduced each database to one-tenth of its original MySQL size. The combined storage savings eliminated the wasteful CPU-tied scaling model and cut annual database resource costs by 40%.
- 80% fewer data nodes, dramatically simpler operations. Consolidating hundreds of MySQL instances into ~10 OceanBase clusters reduced the node count by 80%. OceanBase Cloud Platform (OCP) provides online DDL operations and intelligent diagnostics, freeing the DBA team from the manual sharding and tablespace management that previously consumed their time.
- Financial-grade disaster recovery with zero data loss.
The three-zone HA architecture delivers RPO zero and RTO under 30 seconds — meeting financial-industry continuity standards. Connection capacity increased 5-8x per node, eliminating high-concurrency instability and ensuring a seamless user experience during peak traffic.
Conclusion
As GCash grew into one of the most widely used digital financial platforms in the Philippines, the limits of its legacy MySQL footprint became harder to manage. Rising data volume, higher costs, greater operational complexity, and sensitivity to traffic surges made it clear that incremental fixes were no longer enough.
With OceanBase, GCash moved from scaling through operational workarounds to scaling on a more resilient distributed architecture. By consolidating database instances, reducing storage overhead, and strengthening high-availability protection, GCash built a stronger foundation for future growth in high-concurrency payment scenarios.
