Showing 8 open source projects for "olap"

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  • 1
    Pinot

    Pinot

    Apache Pinot - A realtime distributed OLAP datastore

    Realtime distributed OLAP datastore, designed to answer OLAP queries with low latency. Pinot is designed to answer OLAP queries with low latency on immutable data and mutable data(Upsert Support) Pluggable indexing technologies - Sorted Index, Bitmap Index, Inverted Index, StarTree Index, Bloom Filter, Range Index, Text Search Index(Lucence/FST), Json Index, Geospatial Index.
    Downloads: 0 This Week
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  • 2
    Pretty Damn Quick (PDQ) analytically solves queueing network models of computer and manufacturing systems, data networks, etc., written in conventional programming languages. Generic or customized reports of predicted performance measures are output.
    Downloads: 0 This Week
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  • 3
    qb4j (pronounced 'cube for j') is the first open source multi-dimensional logging framework for Java coupled with an OLAP analytical platform. qb4j doesn't create log files. It creates log cubes (or cube logs).
    Downloads: 0 This Week
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  • 4
    Standalone Java application to view any hierarchical data structures in a JTree. Keys and names to show in the tree are solely driven by SQL statements. The same applies to the additional node's data, which is shown in a separate table panel aside.
    Downloads: 1 This Week
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  • 5
    Easy BI family contains engine(generater) for reporting , charting, tabulardata, olap. All parts is separated. Either change any part of them or customize develop is simple and fun.
    Downloads: 0 This Week
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  • 6
    JPivot is a JSP custom tag library that renders an OLAP table and chart. Users can perform typical OLAP navigations like drill down, slice and dice. It uses Mondrian and XMLA as its OLAP engines.
    Downloads: 2 This Week
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  • 7
    Jira and Bugzilla reporting solution that provides useful software quality metrics, reports, and analysis. Track progress and metrics historically.
    Downloads: 0 This Week
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  • 8
    This project aims at providing an implementation of some state-of-the-art techniques for summarizing multi-dimensional data. Multi-dimensional data summarization can effectively support query optimization algorithms and OLAP applications.
    Downloads: 0 This Week
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