DuckDB
DuckDB is an embedded columnar database that runs in-process, with no server to operate. These guides cover why it suits analytical reads, how it compares to ClickHouse and PostgreSQL, using it from Node.js, pairing it with Parquet for cheap cold storage, and the query patterns that keep dashboards responsive as event volume grows.
9 guides on duckdb.
Hot and Cold Storage for Analytics Without a Data Warehouse
Recent data should be fast; old data should be cheap. How to tier analytics storage between a local DuckDB file and Parquet on S3, and query across both in one SQL statement.
Benchmarking Analytics Queries Honestly
Most published analytics benchmarks are marketing. Cold vs warm cache, realistic data distributions, measuring percentiles not averages, and publishing the harness so people can check.
DuckDB Performance Tuning: Ten Techniques That Work
Practical DuckDB optimization — memory limits, projection and filter pushdown, reading EXPLAIN ANALYZE, join order, Parquet pruning, and when materialization beats views.
Building an Incremental Sync from PostgreSQL to DuckDB
How to stream new rows from PostgreSQL into DuckDB without duplicates or gaps — keyset cursors, batch checkpointing, backfills, and idempotent restarts.
Using DuckDB in Node.js: A Practical Guide
How to run DuckDB inside a Node.js service — connection handling, parameterized queries, bulk inserts, Parquet, and the mistakes that cause corruption or leaks.
Columnar vs Row Storage: Why OLAP Queries Get 100× Faster
A from-first-principles explanation of columnar storage — how data layout, compression, and vectorized execution combine to make analytical queries dramatically faster.
DuckDB + Parquet: Cheap Cold Storage for Analytics Data
How to tier analytics data between a hot DuckDB table and cold Parquet files on S3 or R2, and stitch them into one queryable view with UNION ALL.
DuckDB vs ClickHouse vs PostgreSQL for Analytics: How to Choose
A practical comparison of DuckDB, ClickHouse, and PostgreSQL for analytical workloads — operational cost, query shape, concurrency, and when each one is the right call.
Why We Built Analytics on PostgreSQL + DuckDB (Architecture Deep-Dive)
A technical deep-dive into the dual-database analytics architecture behind InsightsTrack: PostgreSQL for writes, DuckDB for reads, and how it answers 90-day queries in under 100 ms.