Showing 4 open source projects for "geo"

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    Veeam Data Platform v13.1

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  • 1
    Vespa

    Vespa

    The open big data serving engine

    Make AI-driven decisions using your data, in real-time. At any scale, with unbeatable performance. Vespa is a full-featured text search engine and supports both regular text search and fast approximate vector search (ANN). This makes it easy to create high-performing search applications at any scale, whether you want to use traditional techniques or a modern vector-based approach. You can even combine both approaches efficiently in the same query, something no other engine can do....
    Downloads: 18 This Week
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  • 2
    JuiceFS

    JuiceFS

    JuiceFS is a distributed POSIX file system built on top of Redis

    ...JuiceFS is designed to bring back the gold-old memories and experience of file systems in local disks to the cloud. JuiceFS is POSIX compliant and is fully compatible with HDFS and S3. Cloud app building or migrating, file sharing cross-geo and cross-cloud has become easier than ever before. Whether it's a public cloud, private cloud, or hybrid cloud, JuiceFS is available on any cloud of your choice and delivers flexibility, availability, scalability and strong consistency for your data-intensive applications. Purposely built to serve big data scenarios such as self-driving model training, recommendation engine, and Next-generation Gene Sequencing, JuiceFS specializes in high performance and easier management of tens of billion of files management. ...
    Downloads: 1 This Week
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  • 3
    gravitino

    gravitino

    Unified metadata lake for data & AI assets.

    Apache Gravitino is a high-performance, geo-distributed, and federated metadata lake. It manages metadata directly in different sources, types, and regions, providing users with unified metadata access for data and AI assets.
    Downloads: 0 This Week
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  • 4

    iCubing

    Several OLAP algorithms, data structures and HPC OLAP versions

    ...In this direction, we implement iCubing project with several multidimensional data cube approaches for cube indexing, querying, updating and mining. There are also several cube types, i.e. alphanumeric cubes, text cubes with unstructured data and geo cube with geo types, dimensions, measures and hierarchies, so the OLAP area continues a hard challenge after more than 20 years of the seminal paper of Jim Gray et al. in 1997. Our team has more than 15 years of experience in developing OLAP kernels.
    Downloads: 0 This Week
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