Comparisons anchored on DuckDB, the MIT-licensed embedded analytical database, against databases and engines teams already run.
Two embedded databases built for opposite jobs: SQLite's row store for application state and many small transactions against DuckDB's columnar engine for analytical queries over large data. Covers concurrency rules, file formats, extensions and when an application should use both.
When to run analytics in DuckDB rather than in the PostgreSQL database you already operate: columnar versus row execution, single-writer embedding versus a multi-user server, DuckDB's postgres extension for querying PostgreSQL tables directly, and where each belongs in a reporting stack.
Single-machine analytics against a cluster engine: how far DuckDB on one large server gets on Parquet, Iceberg and Delta data, when Spark's distributed execution, streaming and cluster managers are worth their operating cost, and what that means for a self-hosted data platform budget.
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