awesome-repositories.com
Blog
MCP
awesome-repositories.com

Discover the best open-source repositories with AI-powered search.

ExploreCurated searchesOpen-source alternativesSelf-hosted softwareBlogSitemap
ProjectMCP serverAboutHow we rankPress
LegalPrivacyTerms
© 2026 Bringes Technology SRL·VAT RO45896025·hello@awesome-repositories.com
·
flyerhzm avatar

flyerhzm/bullet

0
View on GitHub↗
7,327 stars·452 forks·Ruby·MIT·8 views

Bullet

Bullet is an Active Record performance monitor and query profiler for Ruby on Rails applications. It serves as a diagnostic utility to identify inefficient database access patterns, flag redundant requests, and suggest eager loading strategies to improve response times.

The tool specifically detects N+1 queries, missing counter caches, and unused eager loading. It monitors these patterns across both standard web requests and background jobs, identifying records that are fetched but never accessed to reduce memory usage and query overhead.

Analysis is supported by a system that intercepts database execution events and tracks state throughout a request. Developers receive real-time alerts via browser consoles, log files, or third-party monitoring services. The system includes noise reduction capabilities through safe-listing and stack-trace based filtering.

Features

  • Query Performance Monitors - Analyzes database execution to identify N+1 query patterns and suggest eager loading strategies to optimize efficiency.
  • ORM Performance Monitors - Provides a monitoring utility that identifies inefficient database access patterns and missing counter caches in Active Record.
  • Rails Query Profilers - Detects N+1 queries and unused eager loading within Ruby on Rails applications.
  • Counter Cache Detectors - Identifies repeated count queries on associations to suggest adding counter caches for faster data retrieval.
  • Database Optimization Tools - Flags redundant database requests and suggests eager loading strategies to improve response times.
  • Eager Loading - Detects unused database associations that are loaded but never used to lower memory consumption and query overhead.
  • Unused Eager Loading Detection - Identifies records that are fetched via eager loading but never accessed to reduce unnecessary memory usage and query overhead.
  • Event Interception - Intercepts database execution events to track query frequency and association loading patterns during a request.
  • Query Optimizations - Identifies and fixes N+1 queries and missing counter caches to improve application response times and reduce database load.
  • Post-Execution Analysis Loops - Compares the list of loaded associations against the set of actually accessed records after the response is sent.
  • Application Performance Monitoring - Tracks inefficient database access patterns in web requests and background jobs to prevent performance regressions.
  • Performance Diagnostic Tools - Provides a diagnostic utility that injects alerts into the browser or logs to highlight database bottlenecks during development.
  • Request-Scoped State - Stores a registry of executed queries and accessed associations in a temporary store that clears after every single request.
  • Development Workflow - Provides real-time alerts in browser consoles or logs to identify and resolve database inefficiencies during development.
  • Query Pattern Noise Filters - Suppresses alerts for specific queries or paths using stack trace filters to focus on relevant performance issues.
  • Request-Response Middleware - Appends performance warnings directly to the HTML body or HTTP headers before the final response reaches the client.
  • Extensibility Patterns - Uses a pluggable class system allowing users to define new logic for identifying specific database inefficiency patterns.
  • Error Stack Filtering - Analyzes the Ruby call stack for each query to determine if it matches a user-defined ignore list.
  • Database Query Profiling - Monitors database access patterns and identifies inefficiencies within asynchronous processing and background jobs.
  • Notification Noise Reduction - Excludes known or intentional query patterns from detection using a safe list to reduce notification noise.
  • Monitoring Pausing Controls - Disables detection for specific code blocks or actions to avoid noise in certain execution paths.
  • Notification Injections - Injects notifications into the page body or HTTP headers to alert developers of performance issues during requests.
  • Profiling and Benchmarking - Detects N+1 queries and unused eager loading.
  • Static Analysis Tools - Detects N+1 queries in Ruby applications.

Star history

Star history chart for flyerhzm/bulletStar history chart for flyerhzm/bullet

AI search

Explore more awesome repositories

Describe what you need in plain English — the AI ranks thousands of curated open-source projects by relevance.

Start searching with AI

Open-source alternatives to Bullet

Similar open-source projects, ranked by how many features they share with Bullet.
  • uptrace/uptraceuptrace avatar

    uptrace/uptrace

    4,098View on GitHub↗

    Uptrace is an OpenTelemetry-based observability platform designed to collect, store, and analyze distributed traces, metrics, and logs. It functions as a centralized logging backend, a distributed tracing system, and a metrics engine to monitor application performance and system health. The platform is distinguished by AI-powered operational capabilities, allowing users to query telemetry data and manage monitoring dashboards using natural language. It specifically includes specialized monitoring for generative AI pipelines, tracking token usage and response quality for LLM interactions and r

    Goapmapplication-monitoringclickhouse
    View on GitHub↗4,098
  • victoriametrics/victoriametricsVictoriaMetrics avatar

    VictoriaMetrics/VictoriaMetrics

    16,343View on GitHub↗

    VictoriaMetrics is a high-performance, scalable time series database and observability platform designed for long-term storage and analysis of metric, log, and trace data. It functions as a unified backend for monitoring ecosystems, offering full compatibility with industry-standard protocols and query languages. The system is built to handle massive data volumes through a distributed architecture that supports horizontal scaling and efficient data lifecycle management. The platform distinguishes itself through a storage engine that utilizes consistent hashing for data sharding and log-struct

    Godatabasegrafanagraphite
    View on GitHub↗16,343
  • clickhouse/clickhouseClickHouse avatar

    ClickHouse/ClickHouse

    48,229View on GitHub↗

    ClickHouse is a high-performance, columnar analytical database designed for real-time query execution and large-scale data aggregation. It functions as a distributed data warehouse capable of processing petabytes of information, while also providing an embedded engine that integrates directly into applications for native query capabilities without external dependencies. The system is built to handle high-throughput ingestion and complex analytical workloads, delivering millisecond-level latency for interactive dashboards and operational monitoring. The platform distinguishes itself through ad

    C++aianalyticsbig-data
    View on GitHub↗48,229
  • mikro-orm/mikro-ormmikro-orm avatar

    mikro-orm/mikro-orm

    9,085View on GitHub↗

    Mikro-ORM is a TypeScript-based object-relational mapping system that provides a unified persistence layer for Node.js applications. It translates TypeScript entities into relational or document-based database schemas, supporting a variety of engines including PostgreSQL, MySQL, MariaDB, MS SQL Server, SQLite, and MongoDB. The project implements the data mapper pattern to decouple in-memory domain models from the database persistence layer. It utilizes a unit of work pattern to track entity changes in memory and commit them in a single coordinated database transaction. The library covers com

    TypeScript
    View on GitHub↗9,085
See all 30 alternatives to Bullet→

Frequently asked questions

What does flyerhzm/bullet do?

Bullet is an Active Record performance monitor and query profiler for Ruby on Rails applications. It serves as a diagnostic utility to identify inefficient database access patterns, flag redundant requests, and suggest eager loading strategies to improve response times.

What are the main features of flyerhzm/bullet?

The main features of flyerhzm/bullet are: Query Performance Monitors, ORM Performance Monitors, Rails Query Profilers, Counter Cache Detectors, Database Optimization Tools, Eager Loading, Unused Eager Loading Detection, Event Interception.

What are some open-source alternatives to flyerhzm/bullet?

Open-source alternatives to flyerhzm/bullet include: uptrace/uptrace — Uptrace is an OpenTelemetry-based observability platform designed to collect, store, and analyze distributed traces,… victoriametrics/victoriametrics — VictoriaMetrics is a high-performance, scalable time series database and observability platform designed for long-term… clickhouse/clickhouse — ClickHouse is a high-performance, columnar analytical database designed for real-time query execution and large-scale… mikro-orm/mikro-orm — Mikro-ORM is a TypeScript-based object-relational mapping system that provides a unified persistence layer for Node.js… alexeymezenin/laravel-best-practices — This project is a comprehensive guide to architectural standards and coding patterns for developing maintainable… miniprofiler/rack-mini-profiler — This project is a performance analysis tool for Ruby applications using the Rack interface. It monitors request…