Awesome GitHub RepositoriesTime Series Databases

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

This project is a comprehensive, community-driven knowledge repository designed to support software engineers in mastering distributed systems and architectural design. It functions as a structured compendium of engineering principles, providing a centralized index of patterns, trade-offs, and best practices required for building scalable and reliable software infrastructure. The repository distinguishes itself through a highly organized taxonomy that connects complex technical concepts into a cohesive learning path. It features a categorized collection of system design interview problems, ra

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

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

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

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

Vegeta is an HTTP load testing tool and library designed to measure the performance and stability of web services. It functions as a command-line utility, a programmable package for integration into other applications, and a distributed load generator capable of splitting request rates across multiple machines. The tool is distinguished by its constant-rate request scheduler, which dispatches requests at a fixed frequency regardless of target response times. It employs lazy target streaming to maintain low memory usage during large tests and uses a binary-encoded storage format to minimize di

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

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

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

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

StatsD is a metrics aggregator and UDP collection server that collects system counters and timers. It functions as a time-series data forwarder, receiving high-frequency metric updates via a lightweight line protocol and summarizing them before flushing the data to a backend. The project features a pluggable metrics backend framework, allowing aggregated statistics to be routed to various third-party monitoring services or time-series databases such as Graphite. It supports horizontal scaling and high availability through a proxy ring distribution system that forwards incoming packets across

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

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

VictoriaMetrics is a high-performance, scalable time series database and observability platform designed for long-term storage and analysis of metric, log, and trace data. It functions as a unified backend for monitoring ecosystems, offering full compatibility with industry-standard protocols and query languages. The system is built to handle massive data volumes through a distributed architecture that supports horizontal scaling and efficient data lifecycle management. The platform distinguishes itself through a storage engine that utilizes consistent hashing for data sharding and log-struct

Thanos is a distributed metrics query engine and monitoring scalability suite designed to provide a unified interface for aggregating data from multiple Prometheus servers and clusters. It functions as a high availability monitoring backend that eliminates single points of failure by deduplicating data from replicated instances. The system enables long-term retention by persisting time-series data to cloud-native object storage, allowing for unlimited historical archiving beyond the limits of local disks. It further optimizes this storage through a downsampling and retention manager that comp

Thanos is a CNCF cloud native monitoring tool that provides a highly available and scalable extension to the Prometheus ecosystem. It functions as a global query engine, a long-term storage system, and a metric downsampler. The project enables a unified interface to aggregate and query metrics across multiple distributed clusters from a single view. It maintains historical data beyond local retention limits by persisting time-series metrics in object storage and eliminates data gaps by merging metrics from redundant server pairs. The system includes capabilities for reducing the resolution o

Apache Druid is a real-time OLAP database and distributed analytics engine. It functions as a columnar time-series database designed for high-performance analytical queries and the real-time ingestion of streaming and batch datasets. The system provides a framework for high-concurrency analytics, allowing multiple simultaneous users to execute SQL and native queries across large-scale data. It supports mixed data ingestion, combining real-time streaming and batch loading into a single system for unified analysis. The platform includes capabilities for distributed cluster management, enabling

Nightingale is a Prometheus-compatible monitoring and alerting platform designed to centralize telemetry management across multiple time-series databases. It functions as a multi-source alerting engine and metric data pipeline that ingests telemetry via remote write protocols and triggers alarms based on data from sources such as Prometheus, Elasticsearch, Loki, and ClickHouse. The system is distinguished by its automated alert healing system, which executes predefined scripts and RPC-based corrective actions when monitoring thresholds are breached. It supports distributed alert processing, a

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