SQLite Benchmark Compares Five Tagging Strategies
On March 20, 2026, a micro-benchmark compared five tagging strategies in SQLite on a dataset of 100,000 rows with 100 tags and an average 6.5 tags per row. Indexed approaches—materialized JSON lookup tables and classic many-to-many tables—outperformed others, serving single-tag queries in under 1.5 milliseconds; raw JSON with json_each() and LIKE-based full scans were much slower. Results guide developers choosing trade-offs between query speed, storage, and implementation complexity.
Key Points
- 1Showcases benchmark across five SQLite tagging strategies on 100,000 rows, 100 tags, 6.5 tags/row.
- 2Finds indexed approaches (materialized JSON lookups, many-to-many tables) deliver sub-1.5ms single-tag queries.
- 3Implies use of indexed tables for production tagging to optimize query speed and storage trade-offs.
Scoring Rationale
Provides practical, directly usable benchmark results; limited by single-source micro-benchmark and sparse methodological detail reporting.
Sources
Public references used for this report.
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