# Time Series Databases for Metrics

> Search results for `time series database for metrics and time-stamped data` on awesome-repositories.com. 112 total matches; showing the first 50.

Explore on the web: https://awesome-repositories.com/q/time-series-database-for-metrics-and-time-stamped-data

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## Results

- [questdb/questdb](https://awesome-repositories.com/repository/questdb-questdb.md) (17,062 ⭐) — QuestDB is a high-performance, distributed time-series database designed for the ingestion, storage, and analysis of massive datasets. It functions as a real-time analytics platform that utilizes a columnar storage engine to optimize disk input and output, enabling efficient analytical scans and complex windowing operations on streaming data.

The platform distinguishes itself through specialized capabilities for handling asynchronous time-series streams, including advanced join algorithms that align disparate data sets based on precise timestamp lookups. It supports high-volume ingestion thro
- [jaungiers/lstm-neural-network-for-time-series-prediction](https://awesome-repositories.com/repository/jaungiers-lstm-neural-network-for-time-series-prediction.md) (5,206 ⭐) — This project is a time series forecasting model implemented in Python and Keras. It is a deep learning system designed to predict future values in sequential datasets by training long short-term memory neural networks on historical numerical data.

The implementation focuses on sequential data analysis, specifically applying these models to financial market prediction to forecast price movements and trends.

The architecture covers data preprocessing through min-max feature scaling and sliding-window transformations. It utilizes recurrent neural network cells with gating mechanisms for long-te
- [apache/pinot](https://awesome-repositories.com/repository/apache-pinot.md) (6,098 ⭐) — Pinot is a distributed, columnar analytical database designed for high-concurrency, low-latency query processing. It functions as a real-time OLAP datastore, enabling interactive, user-facing analytics by ingesting and querying massive datasets from both streaming and batch sources. The system architecture relies on a centralized controller for cluster coordination and a distributed segment-based storage model to ensure horizontal scalability.

The platform distinguishes itself through a hybrid ingestion pipeline that unifies real-time event streams and historical batch data into a single quer
- [redis/go-redis](https://awesome-repositories.com/repository/redis-go-redis.md) (22,159 ⭐) — This project is a feature-rich Go client library designed for interacting with Redis. It serves as a comprehensive interface for managing remote data stores, enabling developers to execute standard database commands, handle complex data structures, and perform asynchronous operations within Go applications.

The library distinguishes itself through its support for advanced Redis capabilities, including connection pooling, pipelining, and transactional integrity. It provides specialized primitives for managing distributed clusters, including automated topology updates and request routing to sha
- [openobserve/openobserve](https://awesome-repositories.com/repository/openobserve-openobserve.md) (17,937 ⭐) — OpenObserve is a unified observability data platform designed to ingest, store, and analyze logs, metrics, and traces. It functions as a cloud-native monitoring tool that centralizes telemetry from diverse sources, including standard collectors and cloud service providers, into a single, scalable system. By utilizing a columnar storage engine backed by object storage, the platform enables efficient long-term data retention and high-performance analytical querying.

The platform distinguishes itself through deep integration with artificial intelligence, allowing users to query data using natura
- [jodaorg/joda-time](https://awesome-repositories.com/repository/jodaorg-joda-time.md) (4,984 ⭐) — Joda-Time is a Java date and time library and framework used for parsing, representing, and calculating temporal data. It provides a thread-safe temporal API that uses immutable objects to ensure concurrency safety and adheres to the ISO8601 standard.

The project is distinguished by its pluggable calendar system, which supports diverse chronologies including Gregorian, Buddhist, Coptic, Ethiopic, and Islamic calendars. It also functions as a time zone management tool, utilizing an internal IANA-based zone database to translate instants and update daylight savings rules independently of the ho
- [prometheus/prometheus](https://awesome-repositories.com/repository/prometheus-prometheus.md) (64,569 ⭐) — Prometheus is a comprehensive monitoring and alerting platform designed to track infrastructure health and application performance. It functions as a time series database that ingests, indexes, and queries high-frequency numerical data points. By utilizing a pull-based model, the system periodically collects multi-dimensional metrics from monitored targets, storing them in an optimized block storage format that supports high-throughput ingestion and efficient historical analysis.

The platform distinguishes itself through a specialized query engine that enables real-time analysis of performanc
- [m3db/m3](https://awesome-repositories.com/repository/m3db-m3.md) (4,895 ⭐) — 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
- [samcohen16/aligning-time-series](https://awesome-repositories.com/repository/samcohen16-aligning-time-series.md) (50 ⭐) — This repository consists of an implementation of the Gromov-DTW metric for time series living on incomparable spaces
- [dokploy/dokploy](https://awesome-repositories.com/repository/dokploy-dokploy.md) (34,901 ⭐) — Dokploy is a self-hosted platform-as-a-service designed to simplify the deployment and management of containerized applications and databases. It provides a centralized control plane that decouples administrative management from application workloads, allowing users to oversee infrastructure across multiple server nodes through a unified web interface or a command-line tool.

The platform distinguishes itself through an extensive library of pre-configured application templates, enabling the rapid deployment of databases, identity providers, and various productivity or development tools. It sup
- [jonschlinkert/time-stamp](https://awesome-repositories.com/repository/jonschlinkert-time-stamp.md) (110 ⭐) — Get a formatted timestamp. Used in gulp, assemble, generate, and many others.
- [quantaxis/quantaxis](https://awesome-repositories.com/repository/quantaxis-quantaxis.md) (10,720 ⭐) — QuantAxis is a quantitative trading platform and algorithmic trading framework. It provides a comprehensive local environment for backtesting strategies, managing financial market data, and executing trades across stocks, futures, and options markets.

The system distinguishes itself through a distributed task scheduler that spreads asynchronous computations and heavy mathematical workloads across a network of remote agents. It incorporates a multi-account trading interface to standardize the monitoring of positions and the execution of orders across various brokerage accounts.

The platform c
- [apple/foundationdb](https://awesome-repositories.com/repository/apple-foundationdb.md) (16,446 ⭐) — FoundationDB is an ACID-compliant distributed transactional key-value store. It functions as a scalable database engine that ensures strict serializability and data consistency across a cluster of servers using a shared-nothing architecture.

The system is distinguished by its multi-region replication capabilities, allowing data to be synchronized across different datacenters for high availability and disaster recovery. It utilizes optimistic concurrency control to manage distributed transactions and employs a majority-based coordination system to maintain cluster state.

The platform provides
- [mongodb/mongo](https://awesome-repositories.com/repository/mongodb-mongo.md) (28,158 ⭐) — This project is a distributed, document-oriented database system designed to store information in flexible, hierarchical structures. It supports horizontal scaling through automated sharding and maintains high availability across global clusters using a multi-node replication protocol. By executing multi-document operations as atomic units, the system ensures data integrity and consistency across distributed environments.

The platform distinguishes itself by integrating advanced vector-based indexing, which enables semantic similarity searches alongside traditional geospatial and lexical quer
- [crowdcurio/time-series-annotator](https://awesome-repositories.com/repository/crowdcurio-time-series-annotator.md) (59 ⭐) — Time series annotation library.
- [dubinc/dub](https://awesome-repositories.com/repository/dubinc-dub.md) (23,722 ⭐) — This project is a comprehensive link management and marketing attribution platform designed for creating, tracking, and analyzing shortened URLs. It functions as a centralized hub for marketing analytics, providing tools to monitor link performance, visualize conversion funnels, and manage affiliate programs through a unified dashboard.

The platform distinguishes itself by integrating advanced attribution modeling and partner management directly into the link infrastructure. It supports complex marketing workflows, including automated commission calculations, fraud detection, and payout distr
- [ustc-time-series/tokencast](https://awesome-repositories.com/repository/ustc-time-series-tokencast.md) (25 ⭐) — TokenCast: An LLM-Driven Framework for Context-Aware Time Series Forecasting via Symbolic Discretization
- [graphite-project/graphite-web](https://awesome-repositories.com/repository/graphite-project-graphite-web.md) (6,068 ⭐) — Graphite-web is a time-series monitoring platform that stores numeric metric data in fixed-size Whisper database files, ingests metrics over a plaintext TCP protocol, and renders on-demand graphs from stored data. It provides a tag-based metric query engine for flexible data organization and retrieval, and includes a custom dashboard builder that assembles multiple time-series graphs into a single web view for consolidated monitoring.

The platform distinguishes itself through its URL-driven metric retrieval system, which allows fetching rendered graph images or raw data by constructing HTTP r
- [nationalsecurityagency/timely](https://awesome-repositories.com/repository/nationalsecurityagency-timely.md) (392 ⭐) — Accumulo backed time series database
- [pathwaycom/llm-app](https://awesome-repositories.com/repository/pathwaycom-llm-app.md) (59,341 ⭐) — This project is a data processing engine and AI application platform designed for building production-grade machine learning workflows. It provides a unified programming model that handles both historical batch data and live stream ingestion, enabling the development of real-time ETL pipelines and scalable data transformation workflows.

The framework distinguishes itself through differential dataflow execution, which propagates only changes through a pipeline rather than recomputing entire datasets. It supports distributed state management across worker nodes and utilizes incremental stream p
- [yunaiv/ruoyi-vue-pro](https://awesome-repositories.com/repository/yunaiv-ruoyi-vue-pro.md) (37,833 ⭐) — This project is an enterprise application framework designed to accelerate the construction of complex business software. It functions as a full-stack code generator that automatically produces backend logic, database operations, and frontend interface components from defined data schemas. By providing a standardized foundation for security, authentication, and administrative management, it enables developers to rapidly deploy functional, production-ready software environments.

The platform distinguishes itself through its native support for multi-tenant architectures, allowing for secure dat
- [qingsongedu/time-series-transformers-review](https://awesome-repositories.com/repository/qingsongedu-time-series-transformers-review.md) (2,990 ⭐) — A professionally curated list of awesome resources (paper, code, data, etc.) on Transformers in Time Series, which is first work to comprehensively and systematically summarize the recent advances of Transformers for modeling time series data to the best of our knowledge.
- [greptimeteam/greptimedb](https://awesome-repositories.com/repository/greptimeteam-greptimedb.md) (5,968 ⭐) — 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
- [firehol/netdata](https://awesome-repositories.com/repository/firehol-netdata.md) (79,416 ⭐) — Netdata is a real-time infrastructure monitoring tool and multi-node observability platform. It functions as a high-resolution monitoring agent, log and metric aggregator, and time-series database designed to provide full-stack visibility into server health.

The system is distinguished by its per-second metric sampling and zero-configuration auto-discovery, which allows for immediate infrastructure tracking upon installation. It utilizes edge-based machine learning and unsupervised models to detect system anomalies and abnormal metric patterns locally on each node. For distributed environment
- [qingsongedu/awesome-ai-for-time-series-papers](https://awesome-repositories.com/repository/qingsongedu-awesome-ai-for-time-series-papers.md) (1,618 ⭐) — A professional list of Papers, Tutorials, and Surveys on AI for Time Series in top AI conferences and journals.
- [jakevdp/pythondatasciencehandbook](https://awesome-repositories.com/repository/jakevdp-pythondatasciencehandbook.md) (48,561 ⭐) — This project is an interactive data science environment that combines code execution, rich media visualization, and narrative documentation into a persistent, browser-based platform. It serves as a comprehensive educational resource for scientific computing, providing a framework for iterative data analysis and machine learning prototyping.

The environment is distinguished by its focus on high-performance numerical computing, utilizing vectorized array operations and memory-mapped data structures to handle large-scale computations efficiently. It features a unified estimator interface that st
- [taosdata/tdengine](https://awesome-repositories.com/repository/taosdata-tdengine.md) (24,734 ⭐) — TDengine is a distributed time-series database designed for the high-speed ingestion, compression, and retrieval of timestamped metrics and sensor data. It functions as a SQL-compatible analytics engine, allowing users to perform complex operations on massive volumes of time-ordered information using standard relational syntax. The platform is built to serve as a backend foundation for industrial IoT environments, managing real-time data streams and device metadata through a cluster-based architecture.

The system distinguishes itself through a distributed sharding architecture that uses consi
- [git-time-metric/gtm](https://awesome-repositories.com/repository/git-time-metric-gtm.md) (1,001 ⭐) — Simple, seamless, lightweight time tracking for Git
- [cube-js/cube](https://awesome-repositories.com/repository/cube-js-cube.md) (20,251 ⭐) — Cube is a semantic data layer that provides a unified framework for defining business metrics, dimensions, and relationships across diverse data sources. By acting as a headless business intelligence engine, it transforms raw data into a governed model that can be queried via SQL, REST, and GraphQL interfaces. This architecture ensures consistent data definitions and logic across all downstream analytical applications and reporting tools.

The platform distinguishes itself through its integrated conversational AI capabilities, which allow users to explore data using natural language. It orches
- [ermshaua/time-series-segmentation-benchmark](https://awesome-repositories.com/repository/ermshaua-time-series-segmentation-benchmark.md) (84 ⭐) — The problem of time series segmentation (TSS) is to find a meaningful segmentation of a time series (TS) that captures a data-generating process with distinct states and transitions. We consider a segmentation meaningful, if the change points (CPs) between two consecutive segments correspond to…
- [letianzj/quantresearch](https://awesome-repositories.com/repository/letianzj-quantresearch.md) (2,808 ⭐) — QuantResearch is a quantitative research framework and specialized toolkit for algorithmic simulation, financial time-series analysis, and systematic trading. It provides an event-driven backtesting environment for validating strategies against historical tick and bar data, alongside a dedicated portfolio optimization engine for calculating asset weights and risk metrics.

The project distinguishes itself through a machine learning finance toolkit that implements recurrent neural networks for price prediction and reinforcement learning for derivative pricing. It also features advanced statisti
- [clickhouse/clickhouse](https://awesome-repositories.com/repository/clickhouse-clickhouse.md) (48,229 ⭐) — ClickHouse is a high-performance, columnar analytical database designed for real-time query execution and large-scale data aggregation. It functions as a distributed data warehouse capable of processing petabytes of information, while also providing an embedded engine that integrates directly into applications for native query capabilities without external dependencies. The system is built to handle high-throughput ingestion and complex analytical workloads, delivering millisecond-level latency for interactive dashboards and operational monitoring.

The platform distinguishes itself through ad
- [docker-library/docs](https://awesome-repositories.com/repository/docker-library-docs.md) (5,281 ⭐) — This project serves as a documentation hub and specification repository for official Docker images. It functions as a metadata-driven documentation generator that transforms structured content files into markdown files and readmes for public distribution.

The repository provides technical guides and configuration standards for deploying containerized software across multiple CPU architectures. It includes detailed manuals for configuring environment variables, volume mounts, and network settings to ensure consistent image deployments.

The documentation covers a broad range of containerized e
- [thuml/time-series-library](https://awesome-repositories.com/repository/thuml-time-series-library.md) (12,494 ⭐) — 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
- [clj-time/clj-time](https://awesome-repositories.com/repository/clj-time-clj-time.md) (737 ⭐) — A date and time library for Clojure, wrapping the Joda Time library.
- [influxdata/influxdb](https://awesome-repositories.com/repository/influxdata-influxdb.md) (31,556 ⭐) — InfluxDB is a specialized time series database platform engineered for the high-speed ingestion, compression, and retrieval of timestamped data at scale. It functions as a distributed metrics platform, providing the infrastructure necessary to organize and analyze massive volumes of time-stamped information to identify trends, patterns, and anomalies within complex data streams.

The platform distinguishes itself through a functional dataflow engine that utilizes a specialized programming language for complex analytical transformations and automated tasks. This architecture is supported by a p
- [dask/dask](https://awesome-repositories.com/repository/dask-dask.md) (13,746 ⭐) — Dask is a parallel computing framework and distributed task scheduler designed to scale Python data science workflows from single machines to large clusters. It functions as a cluster resource manager that orchestrates computational logic by representing tasks and their dependencies as directed acyclic graphs. This architecture allows the system to automate the distribution of workloads across available hardware while managing complex execution requirements.

The project distinguishes itself through a lazy evaluation engine that defers data operations until they are explicitly requested, enabl
- [pola-rs/polars](https://awesome-repositories.com/repository/pola-rs-polars.md) (38,855 ⭐) — Polars is a high-performance columnar data processing library designed for efficient analytical workflows. It functions as a structured data library that organizes information into typed columns, utilizing the Apache Arrow memory format to enable zero-copy data sharing and cache-friendly, vectorized operations. The engine is built to handle large-scale tabular datasets, providing both local and distributed analytical runtimes that scale from single-machine environments to multi-node clusters.

The project distinguishes itself through a sophisticated lazy query engine that constructs abstract e
- [qianlima-lab/time-series-ptms](https://awesome-repositories.com/repository/qianlima-lab-time-series-ptms.md) (226 ⭐) — This is an official implementation code for paper "A Survey on Time-Series Pre-Trained Models" (TKDE-24).
- [myhhub/stock](https://awesome-repositories.com/repository/myhhub-stock.md) (12,987 ⭐) — Stock is an algorithmic trading framework designed for the development, backtesting, and execution of automated investment strategies. It provides a comprehensive environment for quantitative market analysis, enabling users to build systems that connect to brokerage interfaces for order placement based on predefined technical rules.

The platform distinguishes itself through integrated data acquisition and analysis capabilities, including a financial data collection engine that utilizes proxy rotation and session persistence to maintain stable connectivity and bypass rate limits. It supports h
- [nscala-time/nscala-time](https://awesome-repositories.com/repository/nscala-time-nscala-time.md) (866 ⭐) — A new Scala wrapper for Joda Time based on scala-time
- [mrdbourke/tensorflow-deep-learning](https://awesome-repositories.com/repository/mrdbourke-tensorflow-deep-learning.md) (5,914 ⭐) — This is a comprehensive deep learning course delivered entirely through Jupyter Notebooks, designed to teach neural network construction using TensorFlow 2.x. The curriculum follows a sequential-model-first pedagogy, introducing the Sequential API before moving to functional and subclassing approaches, and covers the full spectrum of model building from regression and classification through convolutional neural networks, natural language processing, and time series forecasting.

The course is structured around a checkpoint-based training workflow that saves the best model weights during traini
- [zabbix/zabbix](https://awesome-repositories.com/repository/zabbix-zabbix.md) (5,666 ⭐) — Zabbix is an enterprise-grade open-source platform for monitoring IT infrastructure, networks, and applications. It provides real-time metrics, alerts, and dashboards, enabling organizations to track performance and availability across their entire technology stack.

The platform collects metrics from virtually any source, including agents, agentless protocols, APIs, containers, databases, and cloud platforms, without requiring custom scripting. It automatically discovers IT resources by scanning network ranges and cloud environments, then applies pre-built templates for immediate monitoring.
- [transformeroptimus/superagi](https://awesome-repositories.com/repository/transformeroptimus-superagi.md) (17,572 ⭐) — SuperAGI is a comprehensive marketing automation platform and customer data system designed to orchestrate multi-channel engagement workflows. It functions as a no-code workflow orchestrator, allowing users to build complex, automated task sequences triggered by real-time user behavior, transactional data, or scheduled events. By centralizing customer profiles and interaction history, the platform enables businesses to manage end-to-end marketing operations from a single interface.

The platform distinguishes itself through its deep integration with e-commerce storefronts and its ability to ex
- [davedelong/time](https://awesome-repositories.com/repository/davedelong-time.md) (2,344 ⭐) — Robust and type-safe date and time calculations for Swift
- [googlechrome/lighthouse](https://awesome-repositories.com/repository/googlechrome-lighthouse.md) (30,355 ⭐) — Lighthouse is an automated diagnostic tool that evaluates web pages against industry standards for performance, accessibility, and search engine optimization. It functions as a programmatic analysis engine and a command-line utility, allowing developers to integrate comprehensive web quality checks directly into continuous integration pipelines and local development workflows.

The project distinguishes itself through a modular architecture that utilizes artifact-based data collection to ensure consistent analysis across different environments. It supports a headless execution mode for automat
- [yunruizhang/revisit-time-series-classification-benchmark](https://awesome-repositories.com/repository/yunruizhang-revisit-time-series-classification-benchmark.md) (5 ⭐) — This repository contains the official implementation of "Revisiting Time Series Classification Benchmarks: The Impact of Temporal Information for Classification", accepted at PAKDD 2025.
- [avelino/awesome-go](https://awesome-repositories.com/repository/avelino-awesome-go.md) (175,576 ⭐) — This project serves as a comprehensive language ecosystem index, functioning as a centralized, community-curated directory for the Go programming language. It organizes a vast landscape of software components, libraries, and development tools into a structured, navigable hierarchy, enabling developers to efficiently discover resources tailored to specific functional domains.

The repository distinguishes itself through a decentralized contribution model, where community-driven updates ensure the index remains current with the rapidly evolving software landscape. Beyond simple resource listing,
- [apache/hertzbeat](https://awesome-repositories.com/repository/apache-hertzbeat.md) (7,097 ⭐) — HertzBeat is an agentless monitoring platform designed to collect performance metrics from network devices, databases, and servers without requiring client software. It functions as an infrastructure monitoring dashboard, an alert management system, and a centralized log aggregator using the OpenTelemetry Protocol.

The system utilizes a cloud-edge collection hierarchy to scale data gathering across clusters and isolated networks. It distinguishes itself with a flexible extensibility model, allowing users to define new monitoring workflows through configuration-based metric templates and custo
- [influxdb/influxdb](https://awesome-repositories.com/repository/influxdb-influxdb.md) (31,557 ⭐) — InfluxDB is a high-performance time-series database designed for collecting, storing, and querying time-stamped metrics and event data. It functions as a columnar time-series store and a real-time analytics engine, providing a network-accessible interface for retrieving and analyzing temporal records.

The system utilizes a specialized columnar storage format to support high ingestion rates and efficient data retrieval. It incorporates a programmable runtime for executing custom plugins and triggers, including integration for processing and transforming incoming data streams.

The platform cov