Samba Siva Reddy

Working on core PostgreSQL internals including the Planner, Executor, COPY framework, and connection management to support Zoho's distributed database architecture, ensuring correctness, scalability, and performance.

• Designed and implemented a cursor-based pagination system inspired by NoSQL access patterns, eliminating OFFSET-based inefficiencies and enabling efficient, scalable pagination across distributed shards.
• Developed a PostgreSQL extension to cache join orders using queryId, reducing planning overhead for complex queries (8+ joins) while preserving cost-based optimization behavior.
• Upgraded critical database internals by migrating Planner and Executor modules from PostgreSQL 11.4 to 17.2, ensuring long-term compatibility with the evolving open-source ecosystem.
• Optimized the COPY framework for high-throughput data transfer, integrating SCP and Netcat with LZ4/Snappy compression, achieving up to 1.5× improvement in query execution performance.
• Designed and executed a zero-downtime PostgreSQL cluster migration using a Blue-Green deployment strategy, ensuring uninterrupted production traffic while transitioning between major PostgreSQL versions.
• Introduced three new transactional consistency modes, providing developers fine-grained control over query execution in scenarios involving cache invalidation.
• Integrated PostgreSQL join optimization techniques into the distributed architecture to improve join query execution efficiency across the system.
• Diagnosed and resolved critical planner, executor, and distributed execution bugs, improving system stability, correctness, and production reliability.
• Built a query generation and validation framework that auto-generates distribution-aware queries, executes them across cluster configurations, and validates correctness via CI/CD-integrated checks.
• Built a query validation system to compare execution results across old and new PostgreSQL clusters and Blue-Green deployment environments, ensuring correctness during upgrades and schema evolution.
• Investigated and fixed distributed query performance issues including excessive memory usage from unnecessary shard execution, connection congestion during inter-node COPY operations — resolved by optimizing shard targeting and introducing SCP + LZ4-based transfer pipelines.