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3 रिपॉजिटरी

Awesome GitHub RepositoriesStorage Usage Estimation

Tools for calculating the disk space occupancy of specific ranges of data.

Distinguishing note: Shortlist candidates are completely unrelated (MITM frameworks, robot simulators).

Explore 3 awesome GitHub repositories matching data & databases · Storage Usage Estimation. Refine with filters or upvote what's useful.

Awesome Storage Usage Estimation GitHub Repositories

AI के साथ बेहतरीन रिपॉजिटरी खोजें।हम AI का उपयोग करके सबसे सटीक रिपॉजिटरी खोजेंगे।
  • google/leveldbgoogle का अवतार

    google/leveldb

    39,152GitHub पर देखें↗

    LevelDB is an embedded database library and persistent storage engine that provides a sorted key-value store. It uses a log-structured merge-tree architecture to map byte arrays to values, running directly within a process to provide storage without the need for a separate server process. The system is distinguished by its use of custom comparison functions to define key ordering, enabling efficient range scans and sequenced lookups. It ensures data reliability through atomic batch execution, consistent snapshot generation, and log-based recovery after failures. The engine covers broad capab

    Calculates the approximate number of bytes used on the filesystem for specific key ranges.

    C++
    GitHub पर देखें↗39,152
  • cortexproject/cortexcortexproject का अवतार

    cortexproject/cortex

    5,751GitHub पर देखें↗

    Cortex is an open-source, horizontally scalable metrics platform that ingests, stores, and queries Prometheus-compatible time-series data with multi-tenant isolation. It accepts metrics via Prometheus remote write and OpenTelemetry, executes PromQL queries against both recent and historical data, and provides a Prometheus-compatible alerting and recording rule engine with an integrated Alertmanager. The system is built as a set of independently scalable microservices that use hash-ring-based sharding, gossip-based cluster membership, and tenant-aware object storage to distribute workloads acro

    Estimates daily storage requirements per million series for capacity planning.

    Gocncfhacktoberfestkubernetes
    GitHub पर देखें↗5,751
  • hosseinmoein/dataframehosseinmoein का अवतार

    hosseinmoein/DataFrame

    2,917GitHub पर देखें↗

    DataFrame is a C++ tabular data library and manipulation engine designed for managing heterogeneous data in contiguous memory. It functions as a statistical analysis framework and time series analysis toolkit, providing the means to store, index, and transform multidimensional datasets. The project distinguishes itself through a high-performance execution model that utilizes column-major storage, SIMD-aligned memory allocation, and a thread-pool for parallel computations. It employs a visitor-based algorithm dispatch system and policy-driven transformations to decouple data processing logic f

    Calculates estimated byte usage for specific columns and their associated indices to monitor memory footprint.

    C++aicppdata-analysis
    GitHub पर देखें↗2,917
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सब-टैग एक्सप्लोर करें

  • Per-Series Storage EstimatorsEstimates daily storage at 15 GB of chunks and 4 GB of index per million series, multiplied by retention period. **Distinct from Storage Usage Estimation:** Distinct from Storage Usage Estimation: focuses on per-series storage estimation for metrics, not general disk space calculation.