Showing 6 open source projects for "cluster computing"

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  • 1
    Apache Sedona

    Apache Sedona

    Cluster computing framework for processing large-scale geospatial data

    Apache Sedona™ is a cluster computing system for processing large-scale spatial data. Sedona extends existing cluster computing systems, such as Apache Spark and Apache Flink, with a set of out-of-the-box distributed Spatial Datasets and Spatial SQL that efficiently load, process, and analyze large-scale spatial data across machines. According to our benchmark and third-party research papers, Sedona runs 2X - 10X faster than other Spark-based geospatial data systems on computation-intensive query workloads. ...
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  • 2
    tsuru

    tsuru

    Open source and extensible Platform as a Service (PaaS)

    Tsuru is an open source Platform as a Service software, focused in Developer productivity. Tsuru goes beyond 12 factor apps. Run any application written in any language or framework. The deploy process is really simple with just one command. Grow your application dynamically allocating resources with ease. Let your developers code and understand the business instead of solving infrastructure problems or handling large configuration files. We built the platform as a service atop of...
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  • 3
    Erda

    Erda

    An enterprise-grade Cloud-Native application platform for Kubernetes

    Erda is an open-source platform created by Terminus to ensure the development of microservice applications. It provides DevOps, microservice governance, and multi-cloud management capabilities. The multi-cloud architecture based on Kubernetes and application-centric DevOps and microservice governance can make the development, operation, monitoring, and problem diagnosis of complex business applications simpler and more efficient. erda is the core repository that implements all the RESTful...
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  • 4
    A framework to run MATLAB programs as batch jobs. Features a structured input description, integrity constraints and GUI.Independent parts of a job can execute in parallel on a cluster computer. Developed at Freiburg Brain Imaging (FBI) - http://fbi.uniklinik-freiburg.de/
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  • 5
    Summingbird

    Summingbird

    Streaming MapReduce with Scalding and Storm

    Summingbird is a streaming + batch hybrid computation framework developed by Twitter. Its aim is to let developers express data aggregation pipelines in a unified way, where the same logic can run either in real time (stream) or in batch mode, and the results can be merged or reconciled. In effect, Summingbird abstracts over multiple execution engines (such as Storm, Scalding, etc.) to provide one high-level program that composes transformations and aggregations, and then executes them in...
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  • 6
    Python Integrated Parallel Programming EnviRonment (PIPPER), Python pre-parser that is designed to manage a pipeline, written in Python. It enables automated parallelization of loops. Think of it like OpenMP for Python, but it works in a computer cluster
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