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

GbyAI
GbyAI
酷 壳 – CoolShell
酷 壳 – CoolShell
宝玉的分享
宝玉的分享
IT之家
IT之家
Recent Announcements
Recent Announcements
T
The Blog of Author Tim Ferriss
雷峰网
雷峰网
阮一峰的网络日志
阮一峰的网络日志
CTFtime.org: upcoming CTF events
CTFtime.org: upcoming CTF events
M
MIT News - Artificial intelligence
D
Docker
C
CERT Recently Published Vulnerability Notes
月光博客
月光博客
奇客Solidot–传递最新科技情报
奇客Solidot–传递最新科技情报
Recorded Future
Recorded Future
博客园 - 司徒正美
D
DataBreaches.Net
Last Week in AI
Last Week in AI
U
Unit 42
人人都是产品经理
人人都是产品经理
博客园_首页
Blog — PlanetScale
Blog — PlanetScale
量子位
大猫的无限游戏
大猫的无限游戏
博客园 - Franky
T
Tailwind CSS Blog
小众软件
小众软件
Y
Y Combinator Blog
WordPress大学
WordPress大学
B
Blog RSS Feed
C
Check Point Blog
H
Help Net Security
The Last Watchdog
The Last Watchdog
F
Full Disclosure
腾讯CDC
V
Visual Studio Blog
Google Online Security Blog
Google Online Security Blog
钛媒体:引领未来商业与生活新知
钛媒体:引领未来商业与生活新知
T
Troy Hunt's Blog
N
News and Events Feed by Topic
F
Fortinet All Blogs
B
Blog
cs.CV updates on arXiv.org
cs.CV updates on arXiv.org
J
Java Code Geeks
K
KPMG report finds enterprise disconnect between AI and its ROI | CIO
有赞技术团队
有赞技术团队
博客园 - 三生石上(FineUI控件)
TaoSecurity Blog
TaoSecurity Blog
I
InfoQ
V
Vulnerabilities – Threatpost

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
Building a Rental Aggregator When Daft.ie Already Exists
Caspar Banni · 2026-05-27 · via DEV Community

Caspar Bannink

Building a Rental Aggregator When Daft.ie Already Exists

When people find out I'm building a rental search platform for Dublin, the first question is usually some version of: "But why? Daft is already there."

It's a fair question. Daft.ie has dominant market share, brand recognition, a large team, and a listings database built over two decades. If I'm building something in the same space, I need a reason that goes beyond "I'll make it better." Better at what? By whose measure? And what's stopping Daft from just adding that feature?

Here's how I actually thought about it, and what the technical implications turned out to be.

What Daft does that I can't replicate

Before anything else: what Daft has that I don't have is supply-side lock-in. Landlords and letting agencies list on Daft because that's where renters look. Renters look on Daft because that's where landlords list. This is a genuine two-sided network effect that took years to build and can't be engineered around.

I'm not going to out-list Daft. My product doesn't have a listings CMS, a landlord login, or a monetized ad product. I don't want those things. That's not the game I'm playing.

The gap that aggregation addresses

Daft has a lot of listings. It doesn't have all of them.

The Dublin rental market has listings spread across Rent.ie, MyHome, smaller agency portals, property management company websites, and secondary platforms. Some letting agencies and landlords don't post to Daft at all. Others post there but also post to their own site with photos or descriptions that differ slightly.

When I was looking for a flat myself, I was checking six separate sites manually. That's the gap: not better listings, but a unified view of the listings that already exist.

The question then becomes: can I build a technical product that's genuinely better at aggregation than a user doing manual searches? And is that worth doing?

The aggregation architecture

The core is a crawler that runs on a schedule, pulling listing data from Daft.ie and Rent.ie. The challenges that weren't obvious until I was in it:

Source heterogeneity. Each source has its own structure. Daft has a clean API-like interface. Small letting agency sites are often hand-built with inconsistent HTML. Property management company sites sometimes generate listings dynamically in JavaScript, which complicates standard scraping. You end up with a per-source adapter layer that handles idiosyncrasies, feeding a shared normalization layer.

Deduplication. The same apartment often appears on three or four sources simultaneously. Without deduplication, a user sees the same property four times and thinks the market has more supply than it does. Deduplication based on address alone doesn't work reliably because addresses aren't formatted consistently. I use a combination of address fuzzy matching, price comparison, and image fingerprinting (when photos are available) to group duplicates. It's not perfect. False positives (merging two distinct listings) are worse than false negatives (showing a duplicate), so I tune conservative.

Change detection. Knowing that a listing is new requires knowing what was there before. Knowing that a listing is gone requires distinguishing "temporarily de-listed" from "taken." I keep a snapshot of each crawl and diff it against the previous one. Listings that are absent for two consecutive crawl cycles get marked as likely gone rather than immediately. This reduces false "this listing was taken" alerts.

Price normalization. Some sources list weekly prices, some monthly. Some include bills, some don't. All prices in the system get converted to monthly EUR before storage. This sounds trivial and took an embarrassing amount of time to get right across all sources.

Why not just build on top of Daft's data?

The obvious question. Daft has terms of service that prohibit scraping. More practically, building your entire product on one source you don't control creates a single point of failure that a cease-and-desist, a terms change, or a UI redesign can eliminate overnight.

The multi-source architecture is a risk hedge as much as a product feature. Any single source can break or become unavailable. Crawlers fall behind when sites update their structure. Source diversity means no individual source going offline kills the product.

Where this actually competes with Daft

It doesn't compete on listing volume for properties that are Daft-exclusive. It competes on:

Cross-source coverage. If a letting agency posts a property on their own site and nowhere else, my system finds it. Daft doesn't.

Search. Daft's search is filter-based: price range, beds, area from a dropdown. My search accepts natural language and handles the translation to structured filters. "2-bed near Ranelagh Luas, under 1900, pet-friendly" resolves to a structured query without the user having to manually set each filter.

Alerts. My alerts cover Daft.ie and Rent.ie simultaneously. A user doesn't have to set up and maintain separate alert logic on both portals.

Features Daft hasn't prioritized. AI lease review, application tracking, email composer. Features that are useful for the renter's workflow beyond just finding listings.

None of these make me "better than Daft" on Daft's terms. On the specific things I'm competing on, the product is genuinely different.

The strategic frame

The word "competing" is actually a bit wrong here. My product wraps publicly available listing data from Daft.ie and Rent.ie into a faster search and alert workflow. Daft is a source of inventory, not just a competitor. The relationship is asymmetric: they don't know or care I exist; I depend on continued public availability.

This creates a dependency risk I think about seriously. The mitigation is source diversity, features that add value beyond the listings themselves, and building enough user value that switching away from Daft's data specifically wouldn't kill the product.

I wrote a longer breakdown of the full comparison between portals and aggregators at https://homescout.io/guide/better-than-daft-dublin-rentals if you want the user-facing version of this.


Caspar Bannink. Founder of HomeScout.io. Building AI-powered rental search for Dublin.