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2 مستودعات

Awesome GitHub RepositoriesApache Spark Connectors

Distributed processing connectors that exchange data between databases and Spark clusters.

Distinct from Big Data Processing: Distinct from Big Data Processing: specifically focuses on the connector layer for Apache Spark rather than the general processing framework.

Explore 2 awesome GitHub repositories matching data & databases · Apache Spark Connectors. Refine with filters or upvote what's useful.

Awesome Apache Spark Connectors GitHub Repositories

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  • vesoft-inc/nebulaالصورة الرمزية لـ vesoft-inc

    vesoft-inc/nebula

    12,239عرض على GitHub↗

    Nebula is a distributed graph database designed for storing and querying massive volumes of interconnected vertices and edges across a horizontally scalable cluster. It functions as a Kubernetes-native database and a distributed graph analytics engine, utilizing a Raft-based distributed store to ensure strong consistency and high availability. The system features an OpenCypher query engine for performing complex graph traversals and pattern matching. It distinguishes itself with a decoupled compute-storage architecture and a shared-nothing distributed design, allowing query processing and dat

    Provides a distributed processing connector for exchanging data between the database and Apache Spark clusters.

    C++big-datacppdatabase
    عرض على GitHub↗12,239
  • apache/pinotالصورة الرمزية لـ apache

    apache/pinot

    6,098عرض على GitHub↗

    Pinot is a distributed, columnar analytical database designed for high-concurrency, low-latency query processing. It functions as a real-time OLAP datastore, enabling interactive, user-facing analytics by ingesting and querying massive datasets from both streaming and batch sources. The system architecture relies on a centralized controller for cluster coordination and a distributed segment-based storage model to ensure horizontal scalability. The platform distinguishes itself through a hybrid ingestion pipeline that unifies real-time event streams and historical batch data into a single quer

    Processes files and converts them into segment files for database ingestion using Spark.

    Java
    عرض على GitHub↗6,098
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