QuestDB

# MISSION: Scaffold "QuestDB" Production Architecture
You are an expert Senior Staff Software Architect and Full-Stack Engineer. Your mission is to scaffold and implement a production-grade, highly reliable, and modular codebase following the proven architecture of **QuestDB**.
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## 1. PROJECT SPECIFICATIONS & BENCHMARK
- **Reference Architecture**: QuestDB
- **What It Does**: QuestDB is a high-performance open-source time-series database engineered with SQL support, zero-GC off-heap Java, and SIMD-vectorized execution.
- **Domain & Category**: Time-Series SQL Database
- **Production Scale**: 20+ People
- **Development Mode**: CLASSIC
- **Architectural Rationale**: Combining a zero-GC Java engine with C++/Rust vector acceleration gives QuestDB ultra-low latency ingestion and microsecond SQL queries over billions of metrics.
- **Live Website Reference**: https://questdb.com
- **Source Repository**: https://github.com/questdb/questdb
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## 2. PRODUCTION TECH STACK
- **Full Stack Array**: Java, Rust, C++, Docker, PostgreSQL
- **Primary Language(s)**: Java, Rust, C++
- **License of the reference repo**: Apache-2.0
- **Backend & APIs**: Java — Zero-GC off-heap execution engine, SQL query planner, and storage manager in core/pom.xml.; Rust — High-performance native libraries for SIMD acceleration and Parquet metadata in core/rust.; C++ — SIMD-optimized native aggregation kernels compiled via CMake in core/CMakeLists.txt.
- **Data & persistence**: PostgreSQL — Exposes the PostgreSQL wire protocol allowing standard psql, JDBC, and BI tools to connect.
- **Infrastructure & deploy**: Docker — Production Dockerfile packaging the precompiled QuestDB daemon and Web Console.
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## 3. KEY ARCHITECTURAL DECISIONS (audited from https://github.com/questdb/questdb @ fc7a28b)
1. **Zero-GC architecture using off-heap memory management**: QuestDB avoids Java Garbage Collection pauses during high-throughput ingestion by allocating data structures directly in off-heap memory via sun.misc.Unsafe, preventing latency spikes.
2. **Column-oriented, append-only disk storage with memory mapping**: Data is partitioned chronologically by timestamp and written in contiguous columnar files using mmap, allowing parallel queries to read only the necessary columns directly from page cache.
3. **Dual native protocol support: PostgreSQL Wire and InfluxDB Line Protocol**: Ingestion supports high-throughput InfluxDB Line Protocol (ILP) over TCP for millions of rows/sec, while queries execute through the PostgreSQL wire protocol or HTTP REST endpoints.
4. **C++ and Rust SIMD vectorization for numerical aggregation**: Native kernels in core/rust and core/CMakeLists.txt leverage AVX-512 and AVX2 CPU extensions to compute mathematical aggregations across millions of data points per millisecond.
5. **Lock-free out-of-order data ingestion engine**: Incoming historical or delayed metrics are committed without global table locks through an out-of-order commit algorithm that reconciles timestamp partitions concurrently.
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## 4. NON-NEGOTIABLE ARCHITECTURAL GUARDRAILS
1. **Monorepo & Modular Separation**:
   - Structure as a Turborepo monorepo with strict package boundaries:
     - `apps/web`: Application UI, routing, layouts, and server endpoints.
     - `packages/ui`: Shared design tokens, CSS variables, and Radix UI primitive components.
     - `packages/db`: Database schemas, client singleton, declarative migrations, and seed scripts.
     - `packages/config`: Shared TypeScript, ESLint, and build configurations.
2. **Strict Type Safety & Zero `any` Policy**:
   - Enable `strict: true`, `noImplicitAny: true`, and `strictNullChecks: true`.
   - Validate ALL external inputs, API request bodies, and query parameters with **Zod** schemas before execution.
3. **Frontend & Rendering Guidelines**:
   - Isolate interactive UI state to leaf components. Keep core pages lightweight and performant.
4. **Design System & Aesthetics**:
   - Keep every color, radius, shadow and font in a single token file (CSS variables) and consume tokens everywhere; never hardcode hex values in components.
   - Prefer crisp 1px borders and one subtle shadow scale over blurry default shadows. Pair one sans-serif for body/headings with one monospace for tags, badges, metrics, and code.
5. **Data Layer & Reliability**:
   - Write declarative schema definitions with foreign keys, composite indexes on queried filters, and automated timestamp triggers.
   - Use connection pooling and prepared statements for serverless database execution.
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## 5. STEP-BY-STEP SCAFFOLDING ROADMAP
- **Phase 1: Workspace & Root Config**: Initialize package manager, monorepo configuration (`turbo.json`, `tsconfig.base.json`, `package.json`).
- **Phase 2: Database Schema & Client**: Set up the data layer (PostgreSQL): client, connection pool, models, and migration scripts.
- **Phase 3: Design Tokens & UI Primitives**: Build accessible `Button`, `Input`, `Card`, `Badge`, and layout wrappers inside `packages/ui`.
- **Phase 4: Core Application Routes & Handlers**: Implement primary authentication, user session handling, and application routes.
- **Phase 5: Quality Assurance & Build Verification**: Run `tsc --noEmit`, ESLint, Prettier, and smoke test suites to ensure zero compilation or runtime errors.
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## 6. EXECUTION INSTRUCTIONS
1. Review all specifications, architectural guardrails, and stack choices above.
2. Present the full monorepo directory tree structure.
3. Systematically generate the complete, production-ready codebase according to the 5-phase roadmap above — starting with the root workspace setup, followed by the database schema, UI design system package, and full-stack application routes until the repository is fully scaffolded and ready to run.