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When to use DuckDB
- Processing and storing tabular datasets, e.g. from CSV or Parquet files
- Interactive data analysis, e.g. Joining & aggregate multiple large tables
- Concurrent large changes, to multiple large tables, e.g. appending rows, adding/removing/updating columns
- Large result set transfer to client
When to not use DuckDB
- High-volume transactional use cases (e.g. tracking orders in a webshop)
- Large client/server installations for centralized enterprise data warehousing
- Writing to a single database from multiple concurrent processes
- Multiple concurrent processes reading from a single writable database
Articles
"DuckDB: In-Process Python Analytics for Not-Quite-Big Data"
Tags:
storage
relational
tool
embedded
Last modified 28 April 2025