Showing 3 open source projects for "fast performance"

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  • Find Hidden Risks in Windows Task Scheduler Icon
    Find Hidden Risks in Windows Task Scheduler

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  • Vibes don’t ship, Retool does Icon
    Vibes don’t ship, Retool does

    Start from a prompt and build production-ready apps on your data—with security, permissions, and compliance built in.

    Vibe coding tools create cool demos, but Retool helps you build software your company can actually use. Generate internal apps that connect directly to your data—deployed in your cloud with enterprise security from day one. Build dashboards, admin panels, and workflows with granular permissions already in place. Stop prototyping and ship on a platform that actually passes security review.
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  • 1
    PgAgroal

    PgAgroal

    High-performance connection pool for PostgreSQL

    pgagroal is a high-performance PostgreSQL connection pooler written in C, designed for minimal latency and efficient resource usage. It provides features like secure authentication, hot reloading, and support for multiple databases, making it suitable for low-latency applications and microservice architectures. pgagroal is optimized for fast startup, low overhead, and easy integration.
    Downloads: 0 This Week
    Last Update:
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  • 2
    River SQL

    River SQL

    Fast and reliable background jobs in Go

    River is a durable background job system for Ruby on Rails, designed for reliability, observability, and simplicity. It provides persistent queues, native Active Job support, automatic retries, and real-time job monitoring through its admin interface. River focuses on clear diagnostics, performance, and minimal configuration, making it ideal for production-ready job handling in Rails apps.
    Downloads: 1 This Week
    Last Update:
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  • 3
    Apache AGE

    Apache AGE

    Graph database optimized for fast analysis

    Apache AGE (A Graph Extension) is a PostgreSQL extension that adds support for graph database functionality using the openCypher query language. AGE allows users to store and query graph-structured data alongside traditional relational data in a single database. Built for performance and scalability, it brings the power of graph queries to the robustness of PostgreSQL, making it suitable for use cases like social networks, recommendation systems, and fraud detection.
    Downloads: 0 This Week
    Last Update:
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