C++ Semantic Search Tools

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Browse free open source C++ Semantic Search Tools and projects below. Use the toggles on the left to filter open source C++ Semantic Search Tools by OS, license, language, programming language, and project status.

  • Cloud-hosted construction project information management for improved communication, and increased efficiency. Icon
    Cloud-hosted construction project information management for improved communication, and increased efficiency.

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  • Business password and access manager solution for IT security teams Icon
    Business password and access manager solution for IT security teams

    Simplify Access, Secure Your Business

    European businesses use Uniqkey to simplify password management, reclaim IT control and reduce password-based cyber risk. All in one super easy-to-use tool.
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  • 1
    OceanBase seekdb

    OceanBase seekdb

    The AI-Native Search Database

    seekdb is an AI-native search database from OceanBase that unifies vector, full-text, relational, JSON, and GIS data into a single query engine. The system is designed to support hybrid search workloads and in-database AI workflows without requiring multiple specialized databases. It enables developers to perform semantic search, keyword search, and structured SQL queries within the same platform, simplifying modern AI application stacks. seekdb also embeds AI capabilities directly in the database layer, including embedding generation, reranking, and LLM inference for end-to-end RAG pipelines. Built on the OceanBase engine, it maintains ACID compliance and MySQL compatibility while delivering real-time analytical performance. Overall, seekdb positions itself as a unified data foundation for next-generation AI applications that require both transactional and semantic retrieval capabilities.
    Downloads: 6 This Week
    Last Update:
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  • 2
    Zvec

    Zvec

    A lightweight, lightning-fast, in-process vector database

    Zvec is an open-source, lightweight, in-process vector database designed to embed directly into applications and serve fast similarity search workloads without the overhead of a separate server process. Developed by Alibaba’s Tongyi Lab, it positions itself as the “SQLite of vector databases” by being easy to integrate, minimal in dependencies, and capable of handling high throughput with low latency on edge devices or small systems. Zvec excels at approximate nearest neighbor search and retrieval tasks that power features like semantic search, recommendation systems, and retrieval-augmented generation (RAG) setups. Its performance benchmarks show it achieving high queries-per-second and fast index build times compared to similar tools. Because it runs in-process, developers can embed it in native apps, microservices, or edge computing scenarios where traditional server-based vector databases might be overkill.
    Downloads: 2 This Week
    Last Update:
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  • 3
    MyScaleDB

    MyScaleDB

    A @ClickHouse fork that supports high-performance vector search

    MyScaleDB is an open-source SQL vector database designed for building large-scale AI and machine learning applications that require both analytical queries and semantic vector search. The system is built on top of the ClickHouse database engine and extends it with specialized indexing and search capabilities optimized for vector embeddings. This design allows developers to store structured data, unstructured text, and high-dimensional vector embeddings within a single database platform. MyScaleDB enables developers to perform vector similarity searches using standard SQL syntax, eliminating the need to learn specialized vector database query languages. The database is optimized for high performance and scalability, allowing it to handle extremely large datasets and high query loads typical of production AI applications.
    Downloads: 0 This Week
    Last Update:
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