大规模时序数据平台

超高并发写入 · 专有时序优化 · 冷热分级存储

案例咨询

问题概述

随着技术的发展和各行各业对数据处理需求的增加,时序数据平台的建设变得尤为重要。时序数据平台主要用于处理和分析具有时间属性的数据,在物联网、工业自动化、金融科技和智慧城市等多个领域都有广泛的应用。目前,企业建设一个高效的时序数据平台,就需要一个可以满足企业数据量高效写入、实时性能高、存储成本低等需求的数据库产品。

PA平台官方网 具备高效的数据并发写入能力,可实现每秒 10 亿点数据的接入;多模数据处理能力应对多种数据的处理;Domino 流计算引擎支持对数据的实时分析计算;同时,自适应数据压缩、冷热分级存储可以为企业实现更高存储性价比。

实时性要求高
时序数据需要实时生成、写入存储,并支持快速查询,以实现可视化的数据展示。
写入吞吐并发高
在大规模应用性能监控、物联网场景中,海量设备持续产生时序数据,需要解决大规模集群的横向扩展和高性能平稳写入的需求。
数据灵活性高
在物联网场景中,设备元数据、运行时指标等字段总量多,业务变动多,要求数据库具备适应 Schema 灵活变化的能力。
存储成本增长快
由于时序数据增长速度快,每日新增可达数亿条数据,存储的开销随之飙升,亟需数据库具备在存储方面更强的降本能力。

PA平台官方网 核心优势

多模融合、灵活 JSON
支持结构化、半结构化等多种数据类型,可通过 JSON 灵活拓展字段数量和类型,在满足字段数量、灵活性要求的同时降低数据处理复杂度。
专有时序场景优化
内核级时序场景优化,充分提升性能表现,同时原生支持各类时序场景专有函数,降低使用复杂度。
超高并发写入能力
提供专属数据写入组件 MatrixGate ,可实现数据每秒 10 亿数据点的接入。
高性价存储方案
数据自适应压缩提高数据压缩比,冷热分级存储可以将历史数据降级存储至 S3 等低成本的存储介质,防止数据扩张带来的存储成本的高速增长。
强大分析能力
全栈向量化计算引擎,数据处理性能可提升 10 倍。支持丰富的高性能统计、分析、窗口函数,持续聚集功能,可实现产线设备的预测性维护。
库内计算能力
支持 Python/C++/R ,提供库内计算能力,实现高效算法开发与验证,降低机器学习使用难度。

方案架构

PA平台官方网 简化方案架构,无需使用 HBase、OpenTSDB、Redis 等组合的方案架构,一库实现数据高性能写入和数据高效率查询。此外,MARS3 存储引擎支持行列混存的存储模式,提供自适应的数据压缩算法,同时支持冷热数据分级存储能力,大幅节约硬件存储成本。

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"/>|||
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