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DuckDB WASM

DuckDB WASM for in-browser analytics.

DatabaseModerate

Stack Components

DBDuckDB 1.1 WASM
Client@duckdb/duckdb-wasm 1
QuerySQL

Why

OLAP in browser, Parquet, zero server. PostgreSQL is used by nearly 50% of professional developers, making it the most popular database (Stack Overflow 2024).

SQLite powers 1 trillion+ active databases (every iOS/Android device), and DuckDB emerged as the fastest OLAP engine for analytics, 5-10x faster than ClickHouse for single-node queries.

When

Use for client-side analytics. Avoid for large data.

How

1. npm i @duckdb/duckdb-wasm 2. Create DuckDB instance 3. Register files 4. Query with SQL 5. Add environment configuration — cp .env.example .env && edit values 6. Run tests — npm test or pnpm test to verify setup 7. Deploy — git push to trigger CI/CD or manual deploy

Example

const db = new DuckDB() await db.registerFileText('data.csv', csvText) const result = await db.query('SELECT COUNT(*) FROM read_csv("data.csv")')

Common Problems

  • ⚠WASM size — lazy load the bundle
  • ⚠Worker — use for non-blocking
  • ⚠Configuration drift between environments — use infrastructure-as-code (Terraform/Pulumi) to keep dev/staging/prod identical

Best Practices

  • ✓Use Parquet for columnar data
  • ✓Leverage Arrow for results
  • ✓Set up health checks and graceful shutdown — handle SIGTERM to drain in-flight requests before exit

FAQ

What is DuckDB WASM and what projects is it for?

DuckDB WASM for in-browser analytics. It pairs layered technologies for end-to-end type safety and out-of-the-box deploys, fitting everything from MVPs to production SaaS.

How do I spin up a working demo with DuckDB WASM in 10 minutes?

Two steps: (1) npm i @duckdb/duckdb-wasm; (2) Create DuckDB instance. Get the local dev server running, then wire one real data source to verify the end-to-end loop.

What is the most common pitfall with DuckDB WASM and how do I avoid it?

The most common pitfall is: WASM size — lazy load the bundle. Avoid it by adding the matching checklist to your PR template and running type-check + lint + unit tests in CI — three gates before merge.

What are the best practices for DuckDB WASM?

Best practices for DuckDB WASM include: Use Parquet for columnar data; Leverage Arrow for results; Set up health checks and graceful shutdown — handle SIGTERM to drain in-flight requests before exit. The first one — "Use Parquet for columnar data" — should be set up at project init to avoid costly rework later.

When should I NOT choose DuckDB WASM?

Pick something else in three cases: (1) the team has zero experience with the core framework and the deadline is tight (learning-curve risk); (2) it's a pure content/marketing site (Astro is lighter); (3) you need very high throughput (>10k RPS) or strict-consistency microservices (Go/Rust). DuckDB WASM shines for mid-to-high complexity full-stack and API work — don't over-engineer simple static pages with it.