Open-source alternatives to Groupdate

Carbon is a Go library for semantic date and time calculations, formatting, and parsing. It provides a semantic interface to simplify temporal data handling and improve the readability of date and time manipulations. The library is distinguished by its support for multi-calendar date conversion, allowing transformations between Gregorian, Chinese Lunar, Persian, and Hebrew calendar systems. It also includes a localized temporal framework that uses ISO 639-1 codes to format dates and relative time differences across multiple language locales. Additional capabilities cover global time zone man

OpenTSDB is a distributed time series database and metrics engine designed for storing and managing massive volumes of high-cardinality system metrics. It functions as a data store and analytics platform that enables large-scale metric ingestion and infrastructure performance monitoring across a distributed cluster. The system distinguishes itself through a distributed storage abstraction that supports multiple backends such as HBase, Cassandra, and Google Bigtable. It utilizes a hierarchical metric tree to organize time series and employs numeric identifier indexing to reduce storage footpri

mini-graph-card is a customizable dashboard card and sensor widget for Home Assistant designed to visualize historical telemetry and sensor data. It functions as a time-series data visualizer that renders historical numeric and binary sensor data as line or bar graphs using an SVG graphing component. The project differentiates itself through the ability to extract specific nested attributes from entities and map non-numeric states into numeric values for visualization. It supports dynamic visual styling via color thresholds, logarithmic scales, and filling effects, alongside a multi-axis coor

Cube is a time-series analytics platform and event data store designed for real-time performance monitoring. It functions as a metrics engine that ingests timestamped event streams and persists raw logs to enable the computation of statistical summaries, quantiles, and histograms. The system distinguishes itself through a reactive processing model that automatically invalidates metric caches when new events arrive, ensuring query results remain current. It supports both real-time event streaming via persistent connections and the calculation of post hoc statistics from stored event sets. The

Star History is a suite of utilities for visualizing the growth of GitHub repositories over time. It functions as a star growth visualizer, a repository comparison tool, a metric embedder for external websites, and a trending analytics dashboard. The project enables the analysis of star acquisition rates for multiple repositories on a single chart to determine relative growth. It also provides the ability to rank repositories by growth windows to identify rising projects. The system covers project analytics and open source benchmarking by generating time-series charts and growth reports. It

GreptimeDB is a distributed, open-source time-series database built for unified observability. It stores and queries metrics, logs, and traces together in a single columnar engine, supporting both SQL and PromQL for analysis. The database is designed as a Kubernetes-native operator with a decoupled compute and storage architecture, enabling horizontal scaling and multi-region deployment. What distinguishes GreptimeDB is its role as a multi-protocol ingestion gateway, accepting data through OpenTelemetry, Prometheus Remote Write, InfluxDB, Loki, Elasticsearch, Kafka, and MQTT protocols without

Angle Grinder is a command line log processor and analytics tool used for parsing, filtering, and aggregating logs through a pipeline of text transformations. It functions as a text transformation pipeline that converts unstructured logs, as well as JSON and logfmt serialized data, into structured fields for analysis. The tool enables the computation of summary statistics, including running totals, counts, averages, and percentiles. It specifically supports time series log processing by partitioning data into discrete time windows to analyze event frequency and system behavior. The processin

Apache IoTDB is a time-series database designed for the Internet of Things, purpose-built to ingest high-volume data from millions of low-power devices and store timestamp-value pairs with configurable data types and encoding schemes. It organizes time series data and device metadata in a tree-like hierarchy, enabling efficient management of complex industrial sensor networks. The database supports rich querying capabilities, including time-aligned data retrieval across multiple devices, time-based aggregation like downsampling, and frequency-domain signal analysis. It provides high-throughpu

OpenPanel is a self-hosted product analytics platform designed for tracking user behavior and visualizing product metrics on private infrastructure. It provides a comprehensive system for collecting events across web, mobile, and server environments while ensuring complete ownership of data. The platform distinguishes itself through a privacy-first approach, utilizing cookieless event tracking and regional data residency to simplify regulatory compliance. It integrates large language models via the Model Context Protocol, enabling users to query behavioral data and analyze trends using natura

GluonTS is a framework for probabilistic time series forecasting, designed to predict future values as probability distributions with confidence intervals. It supports both traditional model training and zero-shot forecasting, where pretrained models generate predictions for new series without additional training. The project distinguishes itself by integrating a wide variety of forecasting approaches into a unified workflow. This includes deep learning architectures such as recurrent neural networks and causal convolutions, as well as the integration of external statistical models, the Proph

GluonTS is a probabilistic time series library and deep learning forecasting framework. It provides a toolkit for building, training, and evaluating neural network architectures that predict future values as probability distributions to quantify uncertainty. The project distinguishes itself by supporting zero-shot forecasting and integrating diverse modeling approaches, including deep probabilistic neural networks and wrappers for external statistical libraries such as Prophet and R forecast. It implements specialized architectural primitives like causal convolutions and invertible residual n

This project is a pharmaceutical supply chain and public health data analyzer designed to track the historical distribution and quality of medical products across regional jurisdictions. It functions as a monitoring tool for vaccine distribution, analyzing supply patterns and quality variances over time. The system converts pharmaceutical sales records into regional heatmaps and spatial density maps to visualize the geographic concentration of product distribution. It includes a time-series analysis tool to track historical product movement and identify trends in regional supply and demand.

This project is a comprehensive library of practical Python code examples and patterns. It provides a collection of scripts and snippets designed to demonstrate a wide range of programming tasks, from basic syntax to advanced implementation patterns. The repository focuses on several core domains, including the implementation of concurrency and multithreading examples, data analysis snippets for cleaning and manipulating tabular data, and various data visualization examples. It also covers automation scripts for file system management and a variety of general programming patterns. Additional

This PyTorch-based deep learning library provides a framework for analyzing and forecasting temporal data. It implements specialized architectures for time series forecasting, anomaly detection, data imputation, and classification. The project distinguishes itself through the inclusion of zero-shot inference capabilities, allowing large-scale temporal models to be evaluated on unseen datasets without requiring task-specific fine-tuning. The framework covers a broad range of analytical capabilities, including the recovery of missing values in incomplete datasets, the identification of irregul

Nezha is a multi-server infrastructure monitor and website uptime monitor that provides a centralized dashboard for tracking real-time resource utilization and system health. It functions as a protocol server and alerting engine, utilizing remote agents to collect telemetry data across multiple operating systems. The system distinguishes itself with a web-based remote administration interface, allowing users to execute maintenance commands and manage scheduled tasks on remote hosts via a browser-based terminal. It also integrates a Model Context Protocol server to provide a secure HTTP entry

Redis is a high-performance in-memory key-value store that functions as a distributed cache, message broker, and NoSQL database. It provides sub-millisecond read and write access to data stored in RAM and can operate as a vector database for indexing high-dimensional embeddings. The system supports a wide range of data storage and synchronization primitives, including the management of strings, hashes, lists, sets, and JSON documents. It enables real-time data operations through atomic transactions, hybrid persistence using snapshots and append-only logs, and high-availability configurations

m3 is a distributed time series database designed for high-resolution metrics and high-cardinality data management. It functions as a scalable storage system and a multi-cluster query engine, providing a distributed metrics aggregator capable of downsampling and summarizing data before it is committed to storage. The project distinguishes itself through a coordinated cluster model using etcd for node membership and shard placement. It supports multiple ingestion protocols, including the Prometheus remote write protocol, InfluxDB line protocol, and Graphite Carbon plaintext protocol, and provi

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

Plow is a suite of utilities used for generating HTTP load, measuring network performance, and visualizing live metrics. It functions as both an HTTP load generator and a benchmarking tool that measures latency and throughput by sending concurrent requests at configurable rates. The project includes a Socks5 and HTTP proxy client, allowing benchmark traffic to be routed through proxies to test services located behind network gateways. It also provides a real-time performance dashboard via web and terminal interfaces to visualize live metrics and latency histograms during active sessions. The

FreeSql is a .NET object-relational mapper and data access layer that translates object-oriented code into SQL for multiple relational database providers. It functions as a fluent SQL query builder and database schema synchronizer, allowing developers to align database table and index structures with entity class definitions. The framework is specifically optimized for .NET Native AOT to ensure reduced memory footprints and faster startup times. It includes a database traffic manager to distribute load through read-write splitting, dynamic table sharding, and tenant-based data isolation. Bro

MoreLINQ is a functional programming toolkit and extension library for .NET that augments LINQ to Objects with advanced operators for sequence manipulation and analysis. It provides a set of tools for declarative data transformation, leveraging lazy evaluation and composition to handle complex object sequences. The library is distinguished by its specialized capabilities for combinatorial generation, including the production of permutations, subsets, and Cartesian products. It also provides advanced sequence joining options, such as full, left, and right outer joins, and supports complex data

moment-timezone is a JavaScript library and date manipulation extension designed for parsing and converting timestamps across different geographic regions. It serves as a JavaScript implementation of the Internet Assigned Numbers Authority database to manage global time offsets and daylight saving rules. The library provides regional localization and historical time zone analysis by mapping timestamps to geographic regions using official IANA data. It enables the translation of date and time strings between various zones while accounting for chronological records of clock transitions. The pr

kotlinx-datetime is a multiplatform library for handling date, time, and calendar operations across different targets. It provides a consistent set of data types for representing instants and local date-times, serving as a standardized API for temporal management. The toolkit focuses on ISO 8601 compliance for parsing and formatting date and time strings. It implements a multiplatform approach to ensure that timestamps and calendar logic remain consistent across all supported platforms. The library covers temporal data modeling, calendar arithmetic for calculating durations and periods, and

This project is a proposal for a new immutable date and time API in JavaScript. It serves as a precision time-tracking library and a multi-calendar date engine designed to replace the legacy Date object. The system is distinguished by its support for multiple calendar systems beyond the ISO standard and its use of IANA-based time zone resolution. It provides a framework for managing daylight saving transitions and UTC offsets while maintaining nanosecond precision for global timestamps. The API covers broad functional areas including complex date and time arithmetic, locale-aware formatting,

weiboSpider is a Python web scraper and social media crawler designed to extract user profiles, posts, and engagement metrics from Sina Weibo. It functions as an automated data pipeline for academic research and trend analysis, collecting long-form text and multimedia content. The tool distinguishes itself through the use of browser session cookies to authenticate requests and access protected profiles. It implements randomized request pacing and global pauses to manage traffic and avoid platform rate limits, while supporting incremental crawling to capture only new content based on timestamp

hl is a set of command-line interface tools for filtering, aggregating, streaming, and visualizing structured log data across multiple sources. It functions as a log filter, file aggregator, real-time streamer, and structured log viewer. The project specializes in transforming JSON and logfmt data into human-readable formats for visual analysis. It enables the merging of multiple log files and compressed archives into a single chronologically sorted stream, while supporting live tracking of multiple sources into a unified real-time view. Capabilities include field-based filtering via key-val

Darts is a Python time series library designed for forecasting, anomaly detection, and the preprocessing of univariate and multivariate temporal data. It serves as a comprehensive framework for training and evaluating a wide range of statistical, machine learning, and deep learning models to predict future numerical values. The toolkit is distinguished by its support for global time series modeling, allowing a single model to be trained across multiple different series to leverage shared patterns. It also features a hierarchical time series manager to ensure consistency between aggregate and