惯性聚合 高效追踪和阅读你感兴趣的博客、新闻、科技资讯
阅读原文 在惯性聚合中打开

推荐订阅源

罗磊的独立博客
www.infosecurity-magazine.com
www.infosecurity-magazine.com
V
Visual Studio Blog
T
The Blog of Author Tim Ferriss
GbyAI
GbyAI
Y
Y Combinator Blog
雷峰网
雷峰网
Last Week in AI
Last Week in AI
Jina AI
Jina AI
月光博客
月光博客
G
Google Developers Blog
让小产品的独立变现更简单 - ezindie.com
让小产品的独立变现更简单 - ezindie.com
Webroot Blog
Webroot Blog
Google DeepMind News
Google DeepMind News
博客园 - 三生石上(FineUI控件)
Hacker News - Newest:
Hacker News - Newest: "LLM"
N
News | PayPal Newsroom
H
Heimdal Security Blog
Recorded Future
Recorded Future
cs.AI updates on arXiv.org
cs.AI updates on arXiv.org
腾讯CDC
AWS News Blog
AWS News Blog
NISL@THU
NISL@THU
奇客Solidot–传递最新科技情报
奇客Solidot–传递最新科技情报
Cyber Security Advisories - MS-ISAC
Cyber Security Advisories - MS-ISAC
博客园 - 【当耐特】
P
Privacy International News Feed
I
Intezer
V
Vulnerabilities – Threatpost
The GitHub Blog
The GitHub Blog
L
LINUX DO - 最新话题
S
Schneier on Security
C
CXSECURITY Database RSS Feed - CXSecurity.com
小众软件
小众软件
博客园 - 聂微东
V2EX - 技术
V2EX - 技术
W
WeLiveSecurity
Security Latest
Security Latest
PCI Perspectives
PCI Perspectives
The Hacker News
The Hacker News
T
Threatpost
C
Check Point Blog
Threat Intelligence Blog | Flashpoint
Threat Intelligence Blog | Flashpoint
Latest news
Latest news
L
LINUX DO - 热门话题
J
Java Code Geeks
A
Arctic Wolf
cs.CL updates on arXiv.org
cs.CL updates on arXiv.org
K
KPMG report finds enterprise disconnect between AI and its ROI | CIO
T
Troy Hunt's Blog

DEV Community

Authentication Security Deep Dive: From Brute Force to Salted Hashing (With Java Examples) Why AI Systems Don’t Fail — They Drift Spilling beans for how i learn for exam😁"Reinforcement Learning Cheat Sheet" I Replaced Chrome with Safari for AI Browser Automation. Here's What Broke (and What Finally Worked) How Python Borrows Other People's Work The $40 Architecture: Processing 1 Billion API Requests with 99.99% Uptime Vibe Coding: A Workflow Guide (From Zero to SaaS) Most webhook security guides protect the wrong side. The scary part is delivery. Headless CMS for TanStack Start: Build a Blog with Cosmic EU Age Verification App "Hacked in 2 Minutes" — What Actually Happened Comfy Cloud’s delete function does not actually remove files Running AI Models on GPU Cloud Servers: A Beginner Guide Event-driven media intelligence with AWS Step Functions and Bedrock I scored 500 AI prompts across 8 quality dimensions — here's what broke How to Call Google Gemini API from Next.js (Free Tier, No Backend Needed) The Portal Protocol: Reclaiming Human Connection in the Age of AI How to Fix Your Team's Scattered Knowledge Problem With a Self-Hosted Forum Intro to tc Cloud Functors: A Graph-First Mental Model for the Modern Cloud Designing Multi-Tenant Backends With Both Ownership and Team Access I Built a Neumorphic CSS Library with 77+ Components — Here's What I Learned PostgreSQL Performance Optimization: Why Connection Pooling Is Critical at Scale Cómo construí un SaaS multi-rubro para gestionar expensas en Argentina con FastAPI + Vue 3 🚀 I Built an Ethical Hacking Scanner Tool – Open Source Project I Replaced /usage and /context in Claude Code With a Single Statusline A Pythonic Way to Handle Emails (IMAP/SMTP) with Auto-Discovery and AI-Ready Design I Collected 8.9 Million Polymarket Price Points — Here's What I Found About How Markets Really Move EcoTrack AI — Carbon Footprint Tracker & Dashboard Everyone's Using AI. No One Agrees How. 5 self-hosted ebook managers worth trying in 2026 Building Your First AI Agent with LangChain: From Chatbot to Autonomous Assistant Common SOC 2 Failures (Real World) Stop Vibe-Checking Your AI App: A Practical Guide to Evals How to Use SonarQube and SonarScanner Locally to Level Up Your Code Quality Your Next To-Do App Is Dead — I Replaced Mine with an OpenClaw AI Sign a Nostr event in 60 lines of Python using coincurve — no nostr-sdk, no nbxplorer, no rust toolchain ITGC Audit Explained Like You’re in Big 4 Patch Tuesday abril 2026: Microsoft parcha 163 vulnerabilidades y un zero-day en SharePoint Stop scraping everything: a better way to track competitor price changes Listing on MCPize + the Official MCP Registry while routing payments OUTSIDE the marketplace — how I kept 100% of my x402 revenue Building an AI-Powered Risk Intelligence System Using Serverless Architecture Why We Ripped Function Overloading Out of Our AI Toolchain Testing AI-Generated Code: How to Actually Know If It Works SaaS Churn Is Killing Your Business. Here Is What to Do About It (Without a Support Team) The Speed of AI Is No Longer Linear - And Self-Improving Models Are Why How to Implement RBAC for MCP Tools: A Practical Guide for Engineering Teams From Standard Quote to Persuasive Proposal: AI Automation for Arborists I built a CLI that scaffolds complete multi-tenant SaaS apps Axios CVE-2025–62718: The Silent SSRF Bug That Could Be Hiding in Your Node.js App Right Now The dashboard that ended our friendship Data Pipelines Explained Simply (and How to Build Them with Python) The Hidden Cost of AI Systems Nobody Talks About. undefined vs undeclared, and how typeof behaves Switching from file-based jobs to NATS/Kafka in Rust without changing code io_uring Adventures: Rust Servers That Love Syscalls Why Agentic AI is Killing the Traditional Database The POUR principles of web accessibility for developers and designers Quantum Neural Network 3D — A Deep Dive into Interactive WebGL Visualization How To Install Caveman In Codex On macOS And Windows Automation Pipeline Reliability: Why Your Workflow Breaks When Nobody Is Watching I Built an 'Open World' AI Coding Agent — It Works From ANY Folder From Freelancing to Product: A Tech Service Company's SaaS Transformation China's AI Giants: Adding Tencent Hunyuan & ByteDance Doubao to AI University (74 Providers) On the Vibe Coders and Their Lies clerk: Auto-Summarize Your Claude Code Sessions AI Weekly — 2026/04/10–04/17 | The Model Lockdown Is Here, but the Toolchain Is the Real Battleground AI 週報 — 2026/04/10–2026/04/17 模型封鎖潮來了,但工具鏈才是真戰場 Maybe this is how Open-Source apps are born... 🚀 Fine-Tune LLMs with LoRA and QLoRA: 2026 Guide tRPC v11 + Next.js App Router: End-to-End Type Safety Without the Boilerplate ShadCN UI in 2026: Why I Stopped Installing Component Libraries and Started Owning My Components SaaS Billing in React Server Components: Stripe + Supabase Without a Single `useEffect` Join our DEV Weekend Challenge — $1,000 in Prizes Across TEN winners! Submissions Due April 20 at 6:59 AM UTC. Implementing FSRS Spaced Repetition in Flutter + Supabase — Adding Memory Science to an AI Learning App "I Texted My Localhost From the Train — Claude Code Fixed the Bug Before I Got Home" I Built a Sales Prep AI and It Went Deeper Than Expected Design to Code #2: One JSON, Eleven Outputs Solving the 100M-Row Problem: A Summary Table Pattern for High-Volume Push Notification Logs Flutter Web With Wasm: What Actually Changes For Developers I Built 50 Royalty-Free Soundtracks for My Side Project in a Weekend Using AI Music Generation The Vibe Coding Security Checklist: 7 Things to Check Before You Ship Stop Letting Googlebot Guess Fix Your React App's SEO Right Desconstruindo o Streaming do LinkedIn: Como Criar um Engine de Extração de Vídeo de Alta Performance com HLS e FFmpeg (EDA Part-1) EDA (Exploratory Data Analysis) Explained With Real Life — Why Looking at Your Data Is the Most Important Step in Machine Learning Brand Relationship Management at Scale: Our 4-Touch Outreach System for 200+ Brands Why String.fromEnvironment() Might Return an Empty String in Dart JGuardrails 1.0.0 — Hardening Java LLM Apps Against Jailbreaks, Toxicity, and Prompt Injection Plan and Schedule a Full Week of Threads Content From One Claude Conversation Coding Cat Oran Ep3, Five Tables Changed Everything Updated: BFF Pattern I'm done watching freelancers get buried by 200 proposals. So I'm building the alternative. This is my first post BFS Algorithm in Java Step by Step Tutorial with Examples Tracking LLM Pricing Monthly: An Open Dataset for 22 AI Models How We Measure Content ROI on a Comparison Site: Revenue Attribution Without Perfect Data Introducing Nova AI Ops: The AI-Native Operating System for SRE Teams I built a free desktop video downloader for Windows — Grabbit How Talkie OCR Helps Vision-Impaired & Dyslexic Users Read the World Around Them VRCFaceTracking安装和iPhone面捕配置教程,有bug Even CrowdStrike Can't See Your Agents The Automation Gold Rush: What n8n Workflows and Claude Are Opening Up for Developers Right Now
Part 08: Designing Tables, Data Types and Constraints
Mohamed Idris · 2026-05-30 · via DEV Community

Part of the "SQL: Zero to Ninja" series, for junior web devs who want SQL to finally click.

Up to now, the tables already existed. You just queried them. But who decided that price holds numbers and email holds text? Who made sure two users can never share the same email? That was the person who designed the table. Today that person is you.

The idea in one line

CREATE TABLE builds a table, data types say what kind of thing each column holds, and constraints are rules the database promises to enforce so bad data can never sneak in.

The metaphor: a table is a sign-up form

Think of a table definition like a good sign-up form on a website.

  • Each field has the right input type. The birthday field is a date picker, not a free text box where someone types "next Tuesday".
  • Some fields are required. You cannot submit without an email.
  • Some fields must be unique. You cannot sign up with an email someone already used.
  • Some fields have a default. If you leave "newsletter" alone, it is set for you.

Constraints are exactly that form validation, except the database guarantees it. Even if a buggy app or a careless script tries to push in junk, the database says "no".

A column definition  =  one field on the form
A data type          =  the input type (date picker, number box, text box)
A constraint         =  the validation rule (required, unique, default)

CREATE TABLE, the shape

Here is the basic shape. Each line is one column: a name, a type, then any rules.

CREATE TABLE products (
  id       SERIAL PRIMARY KEY,
  name     VARCHAR(100) NOT NULL,
  price    NUMERIC(10, 2) NOT NULL,
  category VARCHAR(50)
);

Read it top to bottom and it is almost English. Let's unpack the pieces.

Common data types (pick the right input box)

  • INTEGER and BIGINT: whole numbers. Use these for counts and ids. BIGINT is just a bigger range for when you expect a lot of rows.
  • VARCHAR(n) and TEXT: words. VARCHAR(100) is text with a max length of 100. TEXT is text with no fixed limit (good for long blog posts or comments).
  • BOOLEAN: true or false. Perfect for is_active or email_verified.
  • DATE and TIMESTAMP: points in time. DATE is just a day. TIMESTAMP is a day plus a time.
  • NUMERIC (also called DECIMAL): exact numbers with decimals. This is the one for money.

The money trap (please read this one)

It is tempting to store money as FLOAT. Do not. Floats are approximate, and math on them goes weird:

-- with FLOAT, this can come out as 0.30000000000000004
SELECT 0.1 + 0.2;

That tiny error adds up across millions of orders and your totals stop matching. Use NUMERIC (or DECIMAL) for any money column. It stores the exact value.

price NUMERIC(10, 2)   -- up to 10 digits, 2 after the dot. Exact. Safe for money.

Store dates as real dates, not text

Another trap. Do not store a date as a string like '2026-05-29' in a VARCHAR. If you do, sorting breaks, comparing breaks, and 'next week' could end up in there too. Use a real DATE or TIMESTAMP. Then the database understands it is time, and you get sorting and date math for free.

Wrong:  created_at VARCHAR(20)     -- "it's just text, right?" ... pain later
Right:  created_at TIMESTAMP       -- the database knows this is a moment in time

Primary keys and auto-increment

Every row needs a way to be pointed at uniquely. That is the primary key, almost always called id. It must be unique and never empty, and the database can fill it in automatically.

  • In Postgres: SERIAL (or the newer IDENTITY) auto-numbers it for you.
  • In MySQL: AUTO_INCREMENT does the same job.
-- Postgres
id SERIAL PRIMARY KEY

-- MySQL
id INT AUTO_INCREMENT PRIMARY KEY

You never type the id yourself. You insert a row, the database hands you the next number.

Constraints: rules the database keeps for you

These are the form-validation rules. Put them on a column and the database enforces them forever.

  • NOT NULL: this field is required. No empty allowed.
  • UNIQUE: no two rows can share this value. Classic for email.
  • DEFAULT: if you do not give a value, use this one.
  • CHECK: the value must pass a condition you write.
status     VARCHAR(20) DEFAULT 'pending',
created_at TIMESTAMP   DEFAULT now(),
total      NUMERIC(10, 2) CHECK (total >= 0)

That CHECK (total >= 0) means an order total can never be negative. Try to insert -5 and the database refuses. You did not write any app code for that. The database just guards it.

FOREIGN KEY: no orphans allowed

An order belongs to a user. A foreign key says "this column must point to a real row in another table." If orders.user_id is a foreign key to users.id, then you cannot create an order for user 999 if no user 999 exists. The database refuses the orphan.

user_id INTEGER NOT NULL REFERENCES users(id)

This keeps your data honest. We go much deeper on relationships in Part 09, including what happens when you delete a user who still has orders.

A full example, our shared schema

Here are users and orders built for real, using everything above.

CREATE TABLE users (
  id         SERIAL PRIMARY KEY,
  name       VARCHAR(100) NOT NULL,
  email      VARCHAR(255) NOT NULL UNIQUE,
  country    VARCHAR(2),
  created_at TIMESTAMP NOT NULL DEFAULT now()
);

CREATE TABLE orders (
  id         SERIAL PRIMARY KEY,
  user_id    INTEGER NOT NULL REFERENCES users(id),
  total      NUMERIC(10, 2) NOT NULL DEFAULT 0 CHECK (total >= 0),
  status     VARCHAR(20) NOT NULL DEFAULT 'pending',
  created_at TIMESTAMP NOT NULL DEFAULT now()
);

Read it like a form. Email is required and unique. Total is money (NUMERIC), defaults to 0, and can never go negative. Every order must belong to a real user. Created_at fills itself in. That is a lot of safety baked right into the design.

Gotchas juniors hit

  1. FLOAT for money. It looks fine in tests, then your totals drift. Use NUMERIC.
  2. Dates as strings. Sorting and date math quietly break. Use DATE or TIMESTAMP.
  3. No constraints, "the app will handle it". Apps have bugs. Scripts run at 2am. The database is the one wall that always holds. Add NOT NULL, UNIQUE, and CHECK at the table level.

Recap

  • CREATE TABLE builds a table. Each column is a name, a type, and optional rules.
  • Pick the right type: INTEGER/BIGINT for whole numbers, VARCHAR/TEXT for words, BOOLEAN, DATE/TIMESTAMP for time, NUMERIC for money (never FLOAT).
  • A primary key (id) is auto-filled by SERIAL (Postgres) or AUTO_INCREMENT (MySQL).
  • Constraints are form validation the database guarantees: NOT NULL, UNIQUE, DEFAULT, CHECK.
  • A FOREIGN KEY stops orphan rows, like an order with no real user.

Your turn

Design a products table from the shared schema. Make id a primary key, name required, price exact money that can never be negative, and category optional. Write the CREATE TABLE. If you can say out loud why price is NUMERIC and not FLOAT, you nailed it.

Next up, Part 09: Relationships and Normalization, where those foreign keys grow into the full story of how tables connect.