Technology
Performance at scale
A streaming architecture that generates millions of rows with \u2264 256 MB peak RAM.
Start FreePerformance benchmarks
Scale without memory constraints.
LiteSeed's chunk-based streaming architecture means generation speed and memory usage are independent of dataset size.
1M+
rows generated
≤ 256 MB
peak RAM at any scale
10K
rows per chunk
3
export formats
How it works
Chunk-based streaming
Generation, quality scoring and export all operate on chunks of 10,000 rows. No full dataset is ever held in memory.
- \u2192CHUNK_SIZE = 10,000 rows constant
- \u2192Each chunk generated, scored and written independently
- \u2192Memory usage is O(chunk_size), not O(dataset_size)
- \u2192Peak RAM ≤ 256 MB for 5M+ row runs
Streaming export writers
All three export formats use streaming writers that write rows as they are generated.
- \u2192CSV: Node.js stream with csv-stringify
- \u2192JSONL: line-by-line write, no buffering
- \u2192Parquet: row-by-row via parquetjs-lite appendRow()
- \u2192Export starts before generation completes
Mulberry32 PRNG performance
A high-performance, deterministic pseudo-random number generator optimised for JavaScript.
- \u2192~500M samples/second in V8
- \u219232-bit state — minimal memory footprint
- \u2192Deterministic: same seed = same sequence
- \u2192No external dependencies