Doppar Bloom Filter is a sophisticated, production-ready implementation of Bloom filters - space-efficient probabilistic data structures that test whether an element is a member of a set. Perfect for large-scale applications where memory efficiency and fast membership testing are critical. This library is an extended version of the denismitr/laravel-bloom package, adjusted for the Doppar framework.

Read the documentation from doppar official site Doppar Bloom

• Storage Backends - Redis
• Configurable Accuracy - Adjustable false positive rates and memory usage
• Dual Hashing Algorithms - MD5 (consistent) and Murmur (high-performance)
• Batch Operations - Efficient bulk additions and checks
• Memory Efficient - Optimized bit manipulation and connection pooling
• Fluent API - Clean, intuitive interface for everyday use

• Duplicate Detection - Prevent duplicate user actions, URLs, or content
• Cache Warming - Check if data exists before expensive database queries
• Spam Filtering - Quickly check if email/URL is known spam
• Recommendation Systems - Track viewed items without storing entire history
• Database Optimization - Reduce unnecessary lookups

Benchmarks based on default configuration with Redis backend

Thank you for considering contributing to the Doppar framework! The contribution guide can be found in the Doppar documentation.

In order to ensure that the Doppar community is welcoming to all, please review and abide by the Code of Conduct.

Please review our security policy on how to report security vulnerabilities.

The Doppar framework is open-sourced software licensed under the MIT license.