Showing 5 open source projects for "google-visualization-python"

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  • 1
    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: 16 This Week
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    MongoEngine

    MongoEngine

    A Python Object-Document-Mapper for working with MongoDB

    MongoEngine is a Python Object-Document Mapper for working with MongoDB.
    Downloads: 6 This Week
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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.
    Downloads: 21 This Week
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  • 4
    Nebula Graph

    Nebula Graph

    A distributed, fast open-source graph database

    The graph database built for super large-scale graphs with milliseconds of latency. Optimized SUBGRAPH and FIND PATH for better performance. Optimized query paths to reduce redundant paths and time complexity. Optimized the method to get properties for better performance of MATCH statements. Nebula Graph adopts the Apache 2.0 license, one of the most permissive free software licenses in the world. Free as in freedom, because, under the Apache 2.0 license, you can use, copy, modify and...
    Downloads: 11 This Week
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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
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