Tag archive

#postgresql

Topic-specific entry points for internal linking, discovery, and deeper subject exploration.

16 articles

The CDC Playbook: Real-time Syncing between PostgreSQL and Elasticsearch

The CDC Playbook: Zero-Delay Data Syncing How do you keep your search engine (Elasticsearch) updated when a user changes their profile in your primary database (PostgreSQL)? Dual-writing in your application code is a rec…

Apr 20, 20261 min read

PlaybookDistributed Systems Mastery

#cdc#debezium#postgresql

DatabasesIntermediate

Database Sharding Part 2: Partitioning vs. Sharding

Database Sharding Part 2: Partitioning vs. Sharding When engineering teams realize their database is struggling to keep up with load, the words "partitioning" and "sharding" are often thrown around interchangeably in arc…

Apr 20, 20265 min read

Deep DiveDatabase Sharding Mastery

#database-scaling#partitioning#sharding

DatabasesAdvanced

The Expand-Contract Pattern: Zero-Downtime Database Schema Changes

The Expand-Contract Pattern: Zero-Downtime Migration The most dangerous operation in backend engineering is a breaking database schema change (e.g., renaming a column). If you just rename it, your existing application co…

Apr 20, 20261 min read

Deep DiveBackend Systems Mastery

#database-migration#zero-downtime#expand-contract

DatabasesExpert

Database Statistics: How Query Planners Build Histograms

Database Query Planner Statistics Your database doesn't "guess" how to run a query. It calculates the Cost of every possible execution path. It does this using Histograms stored in the system catalog. 1. How Histograms W…

Apr 20, 20261 min read

Deep DiveDatabase Internals

#postgresql#query-planner#statistics

DatabasesAdvanced

PostgreSQL JIT Tuning: Understanding the Cost

PostgreSQL JIT Tuning: Understanding the Cost Starting in PostgreSQL 11 (and enabled by default in PostgreSQL 12 and beyond), PostgreSQL introduced Just-In-Time (JIT) compilation. Using the LLVM framework, PostgreSQL can…

Apr 20, 20265 min read

Deep Dive

#postgresql#performance#query-optimization

DatabasesAdvanced

PostgreSQL MVCC: How Transactions Work Without Locking

PostgreSQL MVCC: ACID Without the Waiting One of the biggest advantages of PostgreSQL is its ability to handle many concurrent users without blocking. This is achieved through MVCC (Multi-Version Concurrency Control). 1.…

Apr 20, 20262 min read

Deep Dive

#postgresql#databases#mvcc

DatabasesAdvanced

PostgreSQL Vacuum Tuning: Internals of Bloat Control

PostgreSQL Vacuum Tuning: Mastering Bloat Postgres is an MVCC (Multi-Version Concurrency Control) database. When you update a row, Postgres doesn't overwrite it; it marks the old row as "dead" and inserts a new one. Over…

Apr 20, 20261 min read

Deep DiveDatabase Internals

#postgresql#vacuum#bloat

DatabasesAdvanced

The Shadow Database Pattern: Verifying Schema Changes with Production Traffic

The Shadow Database Pattern Changing the schema of a 10TB database that is processing 50,000 requests per second is a high-stakes operation. Even with perfect testing in a staging environment, production traffic often re…

Apr 20, 20262 min read

Deep DiveBackend Systems Mastery

#database-migration#shadow-db#devops

DatabasesAdvanced

PostgreSQL Locking Playbook: Deadlocks, Blocking Queries, and Timeouts

PostgreSQL locking problems rarely announce themselves clearly. The application sees slow requests, connection pool exhaustion, or timeouts. The database might show normal CPU. The real problem is often one transaction w…

Apr 8, 202611 min read

Playbook

#postgresql#locking#deadlocks

JavaAdvanced

Database Connection Pool Tuning: HikariCP, PostgreSQL, and Traffic Spikes

Database connection pools look boring until they take production down. Most backend services do not fail because the database has zero capacity. They fail because the application opens too many connections, holds them to…

Apr 7, 20268 min read

Deep Dive

#spring boot#hikaricp#postgresql

DatabasesAdvanced

Zero-Downtime Database Migrations: Patterns for Production

Database migrations are the most dangerous part of a deployment. Application code changes are stateless and reversible — rollback a bad deploy and your code is back to the previous version. Database schema changes are st…

Jun 8, 20258 min read

Deep Dive

#database#migrations#postgresql

DatabasesAdvanced

PostgreSQL Performance Tuning: From Slow Queries to Sub-Millisecond Reads

PostgreSQL ships with defaults tuned for a 512MB machine from 2005. Every production deployment needs to be re-tuned. Beyond that, most slow queries are not a PostgreSQL problem — they're a query design problem that Post…

Jun 3, 20259 min read

Deep Dive

#postgresql#databases#performance

DatabasesAdvanced

Designing a Database Sharding Strategy for 100 Million Users

Vertical scaling has a ceiling. For most applications, that ceiling arrives somewhere between 1 million and 10 million users, depending on write patterns and data size. At 100 million users, the question is not whether t…

Apr 14, 20259 min read

Case StudyBackend Systems Mastery

#databases#sharding#postgresql

DatabasesAdvanced

Database Indexing Deep Dive: B-Trees, Hash Indexes, and Query Planning

Indexes are the single most impactful optimization in database performance. A 10-second query becomes 20ms with the right index. A wrong index slows writes and misleads the query planner. Understanding the internals — no…

Mar 9, 202512 min read

Deep DiveBackend Systems Mastery

#postgresql#indexing#b-tree

Data EngineeringAdvanced

Change Data Capture with Debezium: Real-Time Data Synchronization Patterns

Change Data Capture (CDC) is one of those techniques that, once you understand it, you see it everywhere. The pattern: instead of your application explicitly publishing events when data changes, let the database engine i…

Feb 1, 202511 min read

Deep DiveKafka Production Playbook

#cdc#debezium#kafka

DatabasesAdvanced

PostgreSQL vs MongoDB vs DynamoDB: When to Use Which Database

Every database choice is a bet on your access patterns. PostgreSQL, MongoDB, and DynamoDB are all excellent databases — for different problems. The mistake engineers make is choosing based on hype ("NoSQL scales better")…

Jan 12, 202511 min read

Comparison

#postgresql#mongodb#dynamodb