Showing 11 open source projects for "high performance computing"

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  • 1
    CogDB

    CogDB

    Micro Graph Database for Python Applications

    Cog is a lightweight, embedded graph database for Go that provides a simple interface for storing and querying graph-based data structures, making it useful for knowledge representation and graph analytics.
    Downloads: 21 This Week
    Last Update:
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  • 2
    OpenViking

    OpenViking

    Context database designed specifically for AI Agents

    OpenViking is an open-source context database engineered for efficient indexing and retrieval of large amounts of unstructured or semi-structured context data used by AI applications. It’s primarily designed to serve as a high-performance, scalable backend for storing app context, embeddings, conversational histories, and other textual artifacts that need rapid lookup and semantic search, which makes it especially useful for systems like chatbots or memory-augmented agents. The project is implemented with performance in mind, often leveraging optimized data structures that balance fast reads and writes with minimal resource consumption. ...
    Downloads: 1 This Week
    Last Update:
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  • 3
    ZeusDB Vector Database

    ZeusDB Vector Database

    Blazing-fast vector DB with similarity search and metadata filtering

    ZeusDB is a vector database built for fast, scalable similarity search with strong production ergonomics. It combines high-performance approximate nearest neighbor indexes with clean APIs and metadata filtering so applications can retrieve semantically relevant items at low latency. The storage layer is designed for durability and growth, supporting sharding, replication, and background compaction while keeping query tails predictable. Developers get multiple ingestion paths—batch, streaming, and upsert—making it easy to keep embeddings synchronized as content changes. ...
    Downloads: 2 This Week
    Last Update:
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  • 4
    Motor

    Motor

    The async Python driver for MongoDB and Tornado or asyncio

    Motor is an asynchronous Python driver for MongoDB that enables developers to work with MongoDB using non-blocking I/O patterns, making it ideal for high-performance and scalable applications. Built on top of Python’s Tornado and asyncio frameworks, Motor lets you issue database operations without blocking the event loop, enabling concurrency in web servers, real-time systems, and microservices. It provides a familiar API surface similar to the official synchronous PyMongo driver, so you can migrate or write MongoDB code in Python without having to learn a completely new interface. ...
    Downloads: 0 This Week
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  • 5
    Full Stack FastAPI and PostgreSQL

    Full Stack FastAPI and PostgreSQL

    Full stack, modern web application generator

    Generate a backend and frontend stack using Python, including interactive API documentation. Production ready Python web server using Uvicorn and Gunicorn. Very high performance, on par with NodeJS and Go (thanks to Starlette and Pydantic). Great editor support. Completion everywhere. Less time debugging. Designed to be easy to use and learn. Less time reading docs. Minimize code duplication. Multiple features from each parameter declaration. Get production-ready code. With automatic interactive documentation. ...
    Downloads: 0 This Week
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  • 6
    Arctic TimeSeries and Tick store

    Arctic TimeSeries and Tick store

    High performance datastore for time series and tick data

    Arctic is a timeseries/dataframe database that sits atop MongoDB. Arctic supports serialization of a number of datatypes for storage in the mongo document model. Serializes a number of data types eg. Pandas DataFrames, Numpy arrays, Python objects via pickling etc. so you don't have to handle different datatypes manually. Uses LZ4 compression by default on the client side to get big savings on network / disk. Allows you to version different stages of an object and snapshot the state (In some...
    Downloads: 1 This Week
    Last Update:
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  • 7
    aiopg

    aiopg

    aiopg is a library for accessing a PostgreSQL database

    aiopg is an asynchronous PostgreSQL database driver for Python built on top of asyncio and psycopg2. It provides support for asynchronous query execution and connection pooling, enabling efficient, non-blocking database access in Python applications. aiopg is well-suited for web services and microservices that require concurrency without threads.
    Downloads: 0 This Week
    Last Update:
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  • 8
    BlackRay is a persistent in-memory high performance relational database written in C++. It combines regular database features with search engine like performance. Please visit https://forge.softmethod.de for the main development site.
    Downloads: 1 This Week
    Last Update:
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  • 9
    blackray
    BlackRay is a high performance relational database, which combines regular database features with search engine like performance. Full transaction support, SQL and version controlled persisted snapshots characterize BlackRay.
    Downloads: 0 This Week
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  • 10
    PDO: Python Database Objects. Database Module for Python based upon DB-API 2.0: featuring column access by name and high performance. Similar in API to ADO, JDBC.
    Downloads: 0 This Week
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  • 11
    PyCache is analog Memcached, is a high-performance, distributed memory object caching system, generic in nature, but intended for use in speeding up dynamic web applications by alleviating database load.
    Downloads: 0 This Week
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