4 projects for "class scheduling system using java" with 2 filters applied:

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    The database for AI-powered applications.

    MongoDB Atlas is the developer-friendly database used to build, scale, and run gen AI and LLM-powered apps—without needing a separate vector database. Atlas offers built-in vector search, global availability across 115+ regions, and flexible document modeling. Start building AI apps faster, all in one place.
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  • 1
    Orbada - Database manager

    Orbada - Database manager

    Database SQL, query tool, using JDBC for Oracle,SQLite,PostgreSQL,etc

    ORBADA is a database, SQL, query client using JDBC drivers. It is a tool to administrate and manage database structure. It Is for Oracle, SQLite, Firebird, HSQLDB, DerbyDB, MySQL, PostgreSQL and other databases.
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    Downloads: 15 This Week
    Last Update:
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  • 2
    Generic Object Oriented Database System Distributed thick-client OODBMS using aspect-oriented approach to build transparent interface to database from OO programming languages (C++, Java, C#)
    Downloads: 0 This Week
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  • 3
    Technology Explorer for IBM DB2
    The Technology Explorer for IBM DB2 is a light weight, web based console for DB2 that helps you learn about DB2 using demonstrations and tutorials. The TE is designed from the ground up to be easy to use and customize to suit your needs.
    Downloads: 0 This Week
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  • 4
    Tracks project details using a variety of data options. Primarily designed to contain and organize software requirements in a multi-project, multi-user, environment using a networked SQL compliant database management system while tracking changes.
    Downloads: 0 This Week
    Last Update:
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  • Cloud data warehouse to power your data-driven innovation Icon
    Cloud data warehouse to power your data-driven innovation

    BigQuery is a serverless and cost-effective enterprise data warehouse that works across clouds and scales with your data.

    BigQuery Studio provides a single, unified interface for all data practitioners of various coding skills to simplify analytics workflows from data ingestion and preparation to data exploration and visualization to ML model creation and use. It also allows you to use simple SQL to access Vertex AI foundational models directly inside BigQuery for text processing tasks, such as sentiment analysis, entity extraction, and many more without having to deal with specialized models.
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