500 Blog Posts To Learn About Database

2026-05-05 · Source: HackerNoon · Field: Technology & Digital — Data Science & Analytics, Software Development & Engineering, Cloud Computing & IT Infrastructure · Depth: Intermediate, extended

Summary

This compilation offers 500 HackerNoon blog posts, ordered by reader engagement, providing extensive knowledge on "Database" technologies. It covers a wide array of database types, including SQL (MySQL, PostgreSQL, Oracle, MariaDB), NoSQL (MongoDB, Cassandra, DynamoDB, Elasticsearch), Graph (Neo4j), Time-Series (InfluxDB), and emerging Vector databases. The articles delve into critical concepts such as data modeling, schema design, ACID properties, normalization, indexing, sharding, replication, and performance optimization. Furthermore, the collection provides practical guides on installation, CRUD operations, data migration, backup strategies, security, and integration with modern architectures like cloud, microservices, GraphQL, and AI/ML tools.

Key takeaway

This extensive collection of 500 HackerNoon articles offers comprehensive insights into database technologies, covering SQL, NoSQL (MongoDB, Cassandra, Redis), and specialized systems like PostgreSQL, MySQL, and Apache Doris. Professionals can explore topics from database design, performance optimization (e.g., PostgreSQL partitioning, MySQL loose scan, Apache Doris's 10x faster data transfers with Arrow Flight SQL), and migration strategies (Oracle to PostgreSQL, ClickHouse to Apache Doris) to advanced concepts like distributed databases, data lakes, GraphQL APIs, and AI-powered Text2SQL engines. This resource is invaluable for developers, data engineers, DBAs, and business intelligence professionals seeking to enhance their understanding, troubleshoot issues, or make informed architectural decisions across various data management challenges.

Topics

• SQL Databases
• NoSQL Databases
• Database Performance Optimization
• Data Modeling
• Data Migration

Code references

• hackernoon/learn

Best for: Software Engineer, Data Engineer, Machine Learning Engineer

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Editorial summary, takeaway, and curation by AIssential. Original article published by HackerNoon.