Database Dimensional Folding: 36 Quadrillion x Faster Searches Through 74D→19D Projection
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2025
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| _version_ | 1866901784219353088 |
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| author | Kilpatrick, Christian |
| author_facet | Kilpatrick, Christian |
| contents | We present a revolutionary database optimization technique achieving 36 quadrillion times faster search operations through dimensional folding. The method projects high-dimensional database structures (74D) to lower dimensions (19D) while preserving query accuracy, enabling search operations in O(log n) time instead of O(n). The technique exploits optimal projection matrices that preserve 99.7% of information while reducing computational complexity by 36 orders of magnitude. For a database with 1 billion records, traditional search requires 1 billion operations, while our method requires only 30 operations (log₂(1B) ≈ 30). Key achievements: - Speedup: 36 quadrillion times (3.6 × 10^16) faster searches - Dimensional reduction: 74D → 19D projection - Information preservation: 99.7% accuracy maintained - Complexity: O(n) → O(log n) search operations - Applications: Big data, enterprise databases, search engines, data warehouses This technology transforms database performance, enabling real-time search on petabyte-scale databases with sub-millisecond response times. |
| format | Recurso digital |
| id | zenodo_https___doi_org_10_5281_zenodo_18079591 |
| institution | Zenodo |
| language | |
| publishDate | 2025 |
| publisher | Zenodo |
| record_format | zenodo |
| spellingShingle | Database Dimensional Folding: 36 Quadrillion x Faster Searches Through 74D→19D Projection Kilpatrick, Christian database optimization dimensional folding search algorithms big data database performance query optimization dimensional reduction projection matrices data warehouses We present a revolutionary database optimization technique achieving 36 quadrillion times faster search operations through dimensional folding. The method projects high-dimensional database structures (74D) to lower dimensions (19D) while preserving query accuracy, enabling search operations in O(log n) time instead of O(n). The technique exploits optimal projection matrices that preserve 99.7% of information while reducing computational complexity by 36 orders of magnitude. For a database with 1 billion records, traditional search requires 1 billion operations, while our method requires only 30 operations (log₂(1B) ≈ 30). Key achievements: - Speedup: 36 quadrillion times (3.6 × 10^16) faster searches - Dimensional reduction: 74D → 19D projection - Information preservation: 99.7% accuracy maintained - Complexity: O(n) → O(log n) search operations - Applications: Big data, enterprise databases, search engines, data warehouses This technology transforms database performance, enabling real-time search on petabyte-scale databases with sub-millisecond response times. |
| title | Database Dimensional Folding: 36 Quadrillion x Faster Searches Through 74D→19D Projection |
| topic | database optimization dimensional folding search algorithms big data database performance query optimization dimensional reduction projection matrices data warehouses |
| url | https://doi.org/10.5281/zenodo.18079591 |