Relational Database Scaling: Master-Replica Architecture & Partitioning in PostgreSQL
Kowshik Valipireddy
Full Stack Developer & AI Engineer
Scaling relational databases requires decoupling read traffic, partitioning hot tables, and pooling TCP sockets.
1. Scaling Read Workloads with Streaming Replicas
Directing heavy analytics and read queries to streaming read replicas frees the primary database node to focus purely on ACID write transactions.
2. Declarative Table Partitioning by Range and Hash
Partitioning tables by date or tenant ID ensures that query execution plans scan only relevant partition child tables rather than giant billions-row heaps.
3. Connection Pooling with PgBouncer
PgBouncer transaction-mode pooling enables tens of thousands of concurrent client connections to share a lean set of physical PostgreSQL backend processes.
Related Topics & Technologies
Kowshik Valipireddy
AuthorFull Stack Developer & AI Engineer
Full Stack Developer specializing in React, Next.js, Node.js, and AI workflows. Passionate about building fast, accessible, and SEO-optimized web experiences.
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