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VictoriaMetrics is a fast, cost-effective, and scalable monitoring solution and time series database designed for high-ingestion, long-term storage, and efficient querying of time series data. It is fully compatible with Prometheus metrics.
VictoriaMetrics is a high-performance open-source time series database and monitoring solution optimized for resource efficiency, speed, and scalability. It aims to provide a superior alternative to traditional monitoring systems, especially for large-scale environments.
Traditional time series databases and monitoring systems often struggle with high data ingestion rates, require significant storage resources, become prohibitively expensive at scale, and offer slow query performance. VictoriaMetrics addresses these issues by providing a highly optimized solution for storing and querying time series data efficiently and affordably.
Offers high data ingestion throughput and low storage requirements through advanced data compression techniques.
Designed to scale vertically and horizontally to handle millions of time series and terabytes of data.
Supports Prometheus querying APIs (PromQL), data ingestion protocols, and integration with Grafana.
Significant reduction in operational costs due to lower resource consumption (CPU, RAM, disk I/O).
VictoriaMetrics is ideal for any scenario involving collection, storage, and analysis of large volumes of time series data, particularly where performance, cost, and scalability are critical factors.
用于收集、存储和分析来自数千台服务器、容器和网络设备的指标数据,实现全面的系统健康监控和性能分析。
提供高性能的数据摄入和查询能力,有效应对大规模监控场景下的数据洪流,同时降低基础设施成本。
收集和存储来自大量IoT设备的传感器数据,用于实时监控、历史数据分析和异常检测。
其高写入吞吐量和低存储成本使其成为处理海量IoT时间序列数据的理想选择。
整合应用生成的性能指标、日志和追踪数据,用于深入分析应用行为、瓶颈和用户体验。
提供快速查询和聚合能力,帮助SREs和开发者迅速定位和解决应用性能问题。
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