Showing 4 open source projects for "learning classifier system"

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    QuestDB

    QuestDB

    An open source SQL database designed to process time series data

    QuestDB is a high-performance, open-source SQL database for applications in financial services, IoT, machine learning, DevOps and observability. It includes endpoints for PostgreSQL wire protocol, high-throughput schema-agnostic ingestion using InfluxDB Line Protocol, and a REST API for queries, bulk imports, and exports. QuestDB implements ANSI SQL with native extensions for time-oriented language features. These extensions make it simple to correlate data from multiple sources using...
    Downloads: 2 This Week
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  • 2
    KuzuDB

    KuzuDB

    Embeddable property graph database management system

    KuzuDB is a high-performance graph database optimized for analytical queries, built from the ground up with a columnar storage engine. It is designed to efficiently process large-scale graph workloads, making it ideal for data science, machine learning, and knowledge graph applications.
    Downloads: 0 This Week
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  • 3
    manticoresearch

    manticoresearch

    Easy to use open source fast database for search

    Manticore Search is an easy to use open source fast database for search. Modern MPP architecture and smart query parallelization capabilities allow to fully utilize all your CPU cores to lower response time as much as possible, when needed. Powerful and fast full-text searching which works fine for small and big datasets. Columnar storage support via the Manticore Columnar Library for bigger datasets (much bigger than can fit in RAM). SQL-first: Manticore's native syntax is SQL. It speaks...
    Downloads: 0 This Week
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  • 4
    NoisePage

    NoisePage

    Self-Driving Database Management System

    NoisePage is a relational database management system (DBMS) designed from the ground up for autonomous deployment. It uses integrated machine learning components to control its configuration, optimization, and tuning. The system will support automated physical database design (e.g., indexes, materialized views, sharding), knob configuration tuning, SQL tuning, and hardware capacity/scaling.
    Downloads: 0 This Week
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