Apache Parquet vs. YAML 1.2 — Interactive Cost & Performance Calculator
Compare Apache Parquet vs YAML 1.2 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
YAML 1.2
Best for: Kubernetes manifests, CI/CD pipelines & infrastructure configs
Side-by-Side Technical & Commercial Breakdown: Apache Parquet vs. YAML 1.2
| Dimension | Apache Parquet | YAML 1.2 |
|---|---|---|
| Standard / Maintainer | Apache Foundation | YAML.org |
| Relative Size Ratio | 14% of raw baseline | 82% of raw baseline |
| Decode / Parse Throughput | ~1850 MB/sec | ~140 MB/sec |
| Schema & Typing | Strictly Typed Columnar + Dictionary Encoding | Implicit scalar inference |
| Human Readability | No (Binary Columnar) | Yes (Indentation-based with comments) |
| Best Engineering Use Case | Data lakes, DuckDB, BigQuery & analytical OLAP scans | Kubernetes manifests, CI/CD pipelines & infrastructure configs |
Frequently Asked Questions
Which is more cost-effective in 2026: Apache Parquet or YAML 1.2?
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 YAML 1.2 (Kubernetes manifests, CI/CD pipelines & infrastructure configs) have different unit economics that cross over as volume scales.
When should an engineering team choose Apache Parquet over YAML 1.2?
Choose Apache Parquet when your primary priority is: Data lakes, DuckDB, BigQuery & analytical OLAP scans. Choose YAML 1.2 when you prioritize: Kubernetes manifests, CI/CD pipelines & infrastructure configs.