Apache Parquet vs. DuckDB Columnar File — Interactive Cost & Performance Calculator
Compare Apache Parquet vs DuckDB Columnar File side-by-side. Use our interactive calculator to estimate exact monthly costs, savings, and performance trade-offs at your scale.
Apache Parquet
Best for: Data lakes, DuckDB, BigQuery & analytical OLAP scans
DuckDB Columnar File
Best for: In-process analytics, fast aggregations & local BI
Side-by-Side Technical & Commercial Breakdown: Apache Parquet vs. DuckDB Columnar File
| Dimension | Apache Parquet | DuckDB Columnar File |
|---|---|---|
| Standard / Maintainer | Apache Foundation | DuckDB Foundation |
| Relative Size Ratio | 14% of raw baseline | 18% of raw baseline |
| Decode / Parse Throughput | ~1850 MB/sec | ~2200 MB/sec |
| Schema & Typing | Strictly Typed Columnar + Dictionary Encoding | Vectorized columnar OLAP blocks |
| Human Readability | No (Binary Columnar) | No (Compressed analytical file) |
| Best Engineering Use Case | Data lakes, DuckDB, BigQuery & analytical OLAP scans | In-process analytics, fast aggregations & local BI |
Frequently Asked Questions
Which is more cost-effective in 2026: Apache Parquet or DuckDB Columnar File?
It depends on your workload volume. Use the interactive sliders above to model your exact monthly scale. Apache Parquet (Data lakes, DuckDB, BigQuery & analytical OLAP scans) and DuckDB Columnar File (In-process analytics, fast aggregations & local BI) have different unit economics that cross over as volume scales.
When should an engineering team choose Apache Parquet over DuckDB Columnar File?
Choose Apache Parquet when your primary priority is: Data lakes, DuckDB, BigQuery & analytical OLAP scans. Choose DuckDB Columnar File when you prioritize: In-process analytics, fast aggregations & local BI.