Big Data Tools for Mobile Operating Systems

Browse free open source Big Data tools and projects for Mobile Operating Systems below. Use the toggles on the left to filter open source Big Data tools by OS, license, language, programming language, and project status.

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  • 1
    Logan

    Logan

    Logan is a lightweight case logging system based on mobile platform

    Logan is a log platform with the ability to collect, store, upload and analyze front-end logs. We provide five components, including iOS SDK, Android SDK, Web SDK, analysis services Server SDK and LoganSite. In addition, we also provide a Flutter plugin Flutter Plugin. LoganSite provides a visualized way for developers to scan and search logs uploaded from App and Web. To put it simply, the traditional idea is to piece together the problems that appear in the logs of each system, but the new idea is to aggregate and analyze all the logs generated by the user to find the scenes with problems. In the future, we will provide a data platform based on Logan big data, including advanced functions such as machine learning, troubleshooting log solution, and big data feature analysis.
    Downloads: 10 This Week
    Last Update:
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  • 2
    FastoNoSQL

    FastoNoSQL

    FastoNoSQL it is GUI platform for NoSQL databases.

    Gui managment admin tool for: Redis Memcached SSDB LevelDB RocksDB UnQLite LMDB UpscaleDB ForestDB
    Downloads: 12 This Week
    Last Update:
    See Project
  • 3
    FastoRedis

    FastoRedis

    Cross-platform open source Redis DB management tool

    FastoRedis (fork of FastoNoSQL) — is a cross-platform open source Redis management tool (i.e. Admin GUI). It put the same engine that powers Redis's redis-cli shell. Everything you can write in redis-cli shell — you can write in FastoRedis! Our program works on the most amount of Linux systems, also on Windows, Mac OS X, FreeBSD and Android platforms, on desktops and embedded devices.
    Downloads: 1 This Week
    Last Update:
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  • 4
    abu

    abu

    Abu quantitative trading system (stocks, options, futures, bitcoin)

    Abu Quantitative Integrated AI Big Data System, K-Line Pattern System, Classic Indicator System, Trend Analysis System, Time Series Dimension System, Statistical Probability System, and Traditional Moving Average System conduct in-depth quantitative analysis of investment varieties, completely crossing the user's complex code quantification stage, more suitable for ordinary people to use, towards the era of vectorization 2.0. The above system combines hundreds of seed quantitative models, such as financial time series loss model, deep pattern quality assessment model, long and short pattern combination evaluation model, long pattern stop-loss strategy model, short pattern covering strategy model, big data K-line pattern Historical portfolio fitting model, trading position mentality model, dopamine quantification model, inertial residual resistance support model, long-short swap revenge probability model, strong and weak confrontation model, trend angle change rate model, etc.
    Downloads: 0 This Week
    Last Update:
    See Project
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