Showing 5 open source projects for "compiler python linux"

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  • 1
    MongoEngine

    MongoEngine

    A Python Object-Document-Mapper for working with MongoDB

    MongoEngine is a Python Object-Document Mapper for working with MongoDB.
    Downloads: 4 This Week
    Last Update:
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  • 2
    PyMongo

    PyMongo

    PyMongo - the Official MongoDB Python driver

    The PyMongo distribution contains tools for interacting with MongoDB database from Python. The bson package is an implementation of the BSON format for Python. The pymongo package is a native Python driver for MongoDB. The gridfs package is a gridfs implementation on top of pymongo.
    Downloads: 2 This Week
    Last Update:
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  • 3
    ArcticDB

    ArcticDB

    ArcticDB is a high performance, serverless DataFrame database

    Built for the modern Python Data Science ecosystem, ArcticDB transforms your ability to handle complex real-world data with an Incredibly fast proven Petabyte scale. ArcticDB is designed with quant users in mind. It allows you to self-manage your data leveraging your preferred infrastructure. Giving you the keys to protect your most valuable asset. Supports large concurrent writes to many tables ensuring datasets can be onboarded fast and in the most convenient format. Scale-out architecture...
    Downloads: 28 This Week
    Last Update:
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  • 4
    iBoxDB Resources

    iBoxDB Resources

    Relative Examples and Resources of iBoxDB, etc...

    IOs, Graph Database Wrapper and more examples for iBoxDB Download Mirrors https://sourceforge.net/settings/mirror_choices?projectname=application-database&filename=iboxdb411.zip&selected=pilotfiber
    Downloads: 4 This Week
    Last Update:
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    Cosmos DB Spark

    Cosmos DB Spark

    Apache Spark Connector for Azure Cosmos DB

    Azure Cosmos DB Spark is the official connector for Azure CosmosDB and Apache Spark. The connector allows you to easily read to and write from Azure Cosmos DB via Apache Spark DataFrames in Python and Scala. It also allows you to easily create a lambda architecture for batch-processing, stream-processing, and a serving layer while being globally replicated and minimizing the latency involved in working with big data.
    Downloads: 0 This Week
    Last Update:
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