What is Tradingview?

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While we’re charting our paths on TradingView, let’s appreciate the technological artistry behind it.

TradingView’s backend is a wild and elegant beast.
It handles insane amounts of real-time data, custom user scripts, chart rendering, and social interaction — all with buttery-smooth performance.

Let’s unpack it!

:brain: 1. Core Technologies Behind TradingView

:small_blue_diamond: Frontend (what you see):

  • TypeScript + JavaScript — Most of the UI is written in TS for type safety.
  • ReactJS — For dynamic rendering and responsive design.
  • Canvas/WebGL — For ultra-smooth chart rendering. The chart isn’t just HTML — it’s rendered on a canvas layer for performance.
  • Custom Rendering Engine — They likely have an in-house engine to optimize drawing thousands of candles, indicators, and overlays in real-time.

:small_blue_diamond: Backend (what makes it tick):

  • C++ or Rust — Critical performance-heavy services (e.g., data feed engines, real-time calculations) probably run on high-performance languages like C++ or Rust.
  • GoLang — Common for scalable APIs and websocket handling.
  • Node.js — May be used for less time-sensitive backend services or user sessions.

:small_blue_diamond: Databases & Data Layer:

  • Time-Series Databases (like InfluxDB or QuestDB) — For storing price/time data.
  • Redis / Memcached — For real-time caching.
  • PostgreSQL / ClickHouse — For user data, performance analytics, and querying large sets fast.

:small_blue_diamond: Real-Time Data:

  • WebSockets — Powers all real-time updates (candles, quotes, orders, alerts).
  • Proprietary Data Pipelines — They license direct feeds from exchanges (e.g., NYSE, NASDAQ, NSE, Crypto APIs).
  • Kafka or NATS — Pub/Sub systems to distribute data in real-time to millions of users simultaneously.

:small_blue_diamond: Cloud Infrastructure:

  • AWS / Google Cloud — Likely a hybrid setup. They use CDNs for fast global delivery.
  • Kubernetes (K8s) — For managing containers and scaling services dynamically.
  • Load balancers and microservices — To distribute traffic efficiently.

:scroll: 2. Pine Script Engine

  • Custom-built interpreter/compiler.
  • Likely runs in sandboxed environments.
  • Every script is compiled on-the-fly and executes inside controlled execution engines per user/chart.
  • Optimized to evaluate only visible candles and avoid server overload.

:chart_with_upwards_trend: 3. Chart Engine (One of Their Crown Jewels)

  • Vector-based canvas renderer.
  • Capable of drawing tens of thousands of bars, indicators, labels, trendlines smoothly.
  • Animation and crosshair syncing is super optimized.

:technologist: 4. Massive Parallelism & Caching

  • Every user gets their own set of Pine scripts and chart sessions.
  • Smart result caching and shared indicator memory helps reduce repeated calculations.
  • Pine script output is computed in chunks to avoid unnecessary redraws.

:rocket: 5. Global Scaling

  • Likely use CDNs (like Cloudflare or Akamai) for:
    • Static assets (charts, images, fonts).
    • Real-time websocket edge nodes.
  • Multiple geo-replicated data centers to reduce latency across the globe.

TL;DR:

TradingView is basically a fintech Ferrari — running on a combo of high-performance code, real-time pub/sub architecture, massive distributed systems, and custom-built tools. It’s built for speed, scale, and trader obsession.

*Note:-*strong text I am not associated directly or indirectly with tradingview.com
Just appreciate their work of technological artwork.
So researched the info and jot down few points for community.

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