Postgres

Stylized ledger book with debits and credits balanced on facing pages.

Architecting Double-Entry Ledger Systems: Schema, Concurrency, and Auditability for Financial Integrity

How to design a double-entry ledger that stays correct under concurrency: event-sourced schema, Postgres constraints, and append-only audit trails.

Diagram of a Postgres-backed job queue with workers, retries, and a dead-letter table.

Building a Durable Job Queue in Postgres: A Portfolio Project That Signals Real Systems Skill

Build a production-flavored job queue on Postgres from scratch: schema, worker loop, retries with exponential backoff, and a dead-letter queue. A portfolio project that demonstrates real distributed systems thinking.

Architecture diagram of a Postgres-backed durable job queue

Build a Durable Postgres Job Queue: A Portfolio Project That Signals Real Systems Skill

Build a production-flavored job queue on Postgres with SKIP LOCKED, exponential backoff, and a dead-letter queue. A substantive portfolio project that demonstrates real backend systems skill.

A schematic of PostgreSQL's Write-Ahead Log pipeline.

Deep Dive into the Postgres Write-Ahead Log: Ensuring Durability and Data Integrity for Production Systems

A production‑ready guide to PostgreSQL’s WAL, covering its internals, configuration knobs, and monitoring practices that safeguard durability and data integrity.

Scaling Vector Databases for Real-Time AI Applications Beyond Faiss and Postgres

Table of Contents Introduction Why Real‑Time Matters for Vector Search The Limits of Faiss and PostgreSQL for Production Workloads Core Requirements for Scalable Real‑Time Vector Stores Alternative Vector Database Architectures 5.1 Milvus 5.2 Pinecone 5.3 Vespa 5.4 Weaviate 5.5 Qdrant 5.6 Redis Vector Design Patterns for Scaling 6.1 Sharding & Partitioning 6.2 Replication & High Availability 6.3 Caching Strategies 6.4 Hybrid Indexing (IVF + HNSW) Deployment Strategies: Cloud‑Native, Kubernetes, Serverless Performance Tuning Techniques 8.1 Quantization & Compression 8.2 Optimizing Index Parameters 8.3 Batch Ingestion & Asynchronous Writes Practical Example: Real‑Time Recommendation Engine 9.1 Data Model 9.2 Ingestion Pipeline (Python + Qdrant) 9.3 Query Service (FastAPI) 9.4 Scaling Out with Kubernetes Observability, Monitoring, and Alerting Security, Multi‑Tenancy, and Governance Future Trends: Retrieval‑Augmented Generation & Hybrid Search Conclusion Resources Introduction Vector databases have moved from research curiosities to production‑critical components of modern AI systems. Whether you’re powering a recommendation engine, a semantic search portal, or a Retrieval‑Augmented Generation (RAG) pipeline, the ability to store, index, and retrieve high‑dimensional embeddings in milliseconds is non‑negotiable. ...