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time_series_database

65 articles · Page 1 of 1
Raymond Ops
Raymond Ops
Jun 15, 2026 · Databases

How to Deploy VictoriaMetrics for High‑Performance Prometheus Remote Storage

This article walks through the challenges of scaling Prometheus storage, compares Thanos, Cortex, and VictoriaMetrics, and provides a complete step‑by‑step guide—including hardware requirements, configuration, deployment, tuning, multi‑tenant setup, and troubleshooting—to replace Prometheus local TSDB with VictoriaMetrics for long‑term, high‑performance monitoring.

MonitoringPerformance TuningVictoriaMetrics
0 likes · 43 min read
How to Deploy VictoriaMetrics for High‑Performance Prometheus Remote Storage
Wukong Talks Architecture
Wukong Talks Architecture
Mar 5, 2026 · Databases

Unifying Card and Coin Payments: KaiwuDB’s Dual‑Mode Solution for Amusement Parks

This article presents a detailed technical case study of using KaiwuDB’s multi‑model database to unify card‑based and coin‑based payment processing in amusement parks, covering architecture, schema design, SQL implementations, offline handling, cross‑model analytics, hot‑cold data tiering, visualization, monitoring, security, and high‑availability strategies.

Amusement ParkData IntegrationDual-Mode Payments
0 likes · 42 min read
Unifying Card and Coin Payments: KaiwuDB’s Dual‑Mode Solution for Amusement Parks
Data Party THU
Data Party THU
Sep 2, 2025 · Industry Insights

How a Tsinghua CTO Is Driving IoTDB Toward Global Leadership

The article profiles Tianmou Technology’s co‑founder and CTO Qiao Jialin, detailing his personal journey, the company’s mission to build the world’s best time‑series database, its technical advantages, adoption by aerospace and other industries, and the cultural values that sustain rapid innovation.

AerospaceData ManagementIoTDB
0 likes · 21 min read
How a Tsinghua CTO Is Driving IoTDB Toward Global Leadership
Data Party THU
Data Party THU
Aug 23, 2025 · Industry Insights

How Apache IoTDB Dominated Benchmarks and Powered Industry 2023‑2025

The article summarizes the 2025 Time Series Database Innovation Conference where Apache IoTDB’s evolution, technical breakthroughs, benchmark leadership, open‑source community growth, and real‑world industrial deployments from aerospace to oil‑gas are detailed, highlighting the upcoming IoTDB 2.0 vision.

Apache IoTDBDB+AIbenchmarks
0 likes · 11 min read
How Apache IoTDB Dominated Benchmarks and Powered Industry 2023‑2025
360 Zhihui Cloud Developer
360 Zhihui Cloud Developer
Apr 2, 2025 · Databases

How VictoriaMetrics' Distributed Architecture Scales Massive Time‑Series Data

VictoriaMetrics employs a modular, horizontally scalable architecture composed of vmagent, vminsert, vmstorage, vmselect, and vmalert, each handling data collection, ingestion, storage, querying, and alerting, while leveraging consistent hashing, LSM‑tree storage, TSID indexing, and multi‑tenant isolation to efficiently manage large‑scale time‑series workloads.

Query OptimizationVictoriaMetricsscalable storage
0 likes · 11 min read
How VictoriaMetrics' Distributed Architecture Scales Massive Time‑Series Data
DataFunTalk
DataFunTalk
Jan 9, 2025 · Databases

Innovative IoT Point Management with DolphinDB IOTDB Engine

This article explains the challenges of managing heterogeneous IoT sensor data, compares wide‑table and narrow‑table modeling approaches, and introduces DolphinDB's IOTDB engine—featuring a unified IOTANY column, a TSDB engine, a latest‑value cache, and a static info table—to efficiently store and query diverse point data in a single table.

DolphinDBIOTDB engineIoT
0 likes · 8 min read
Innovative IoT Point Management with DolphinDB IOTDB Engine
AntData
AntData
Sep 26, 2024 · Databases

Apache HoraeDB (CeresDB): An Open‑Source Distributed Time‑Series Database

Apache HoraeDB (CeresDB) is an open‑source, distributed, high‑availability time‑series database developed by Ant Group, supporting multi‑dimensional queries, compatible with Prometheus and OpenTSDB, and offering SQL and OLAP capabilities for use cases such as APM, IoT monitoring, financial analytics, and AI‑infra observability.

ObservabilitySQLdistributed systems
0 likes · 5 min read
Apache HoraeDB (CeresDB): An Open‑Source Distributed Time‑Series Database
Xiaolei Talks DB
Xiaolei Talks DB
Aug 28, 2024 · Databases

What 15 Years of China’s DTCC Conferences Reveal About Database Evolution

The author reflects on a decade‑plus journey through China’s DTCC database conferences, describing personal growth from novice to speaker and organizer, sharing insights on Redis Cluster, distributed database selection, openGauss, time‑series databases, and the evolving themes that chart the industry's progress.

DatabasesRediscareer development
0 likes · 6 min read
What 15 Years of China’s DTCC Conferences Reveal About Database Evolution
dbaplus Community
dbaplus Community
Jun 24, 2024 · Operations

How Qunar Achieved Sub‑Second Monitoring to Slash Fault Detection Time to Under 1 Minute

Qunar’s Watcher monitoring platform was upgraded from minute‑level to second‑level precision, redesigning storage, data collection, and alerting pipelines, adopting VictoriaMetrics, enhancing client SDKs, and adding fine‑grained alarm rules, which reduced fault detection from four minutes to under one minute while improving reliability and scalability.

MonitoringObservabilitydevops
0 likes · 20 min read
How Qunar Achieved Sub‑Second Monitoring to Slash Fault Detection Time to Under 1 Minute
Huawei Cloud Developer Alliance
Huawei Cloud Developer Alliance
Jun 3, 2024 · Databases

Master OpenGemini: From Schema Design to Performance Tuning Best Practices

This article summarizes a live session where Shawn explains how understanding business scenarios drives effective OpenGemini database design, and provides comprehensive best‑practice guidance on library and table design, data ingestion, query optimization, and performance tuning for time‑series workloads.

Performance TuningQuery OptimizationSharding
0 likes · 7 min read
Master OpenGemini: From Schema Design to Performance Tuning Best Practices
NetEase Cloud Music Tech Team
NetEase Cloud Music Tech Team
Jan 10, 2024 · Operations

Building Cloud Music's APM Metric Monitoring System Based on VictoriaMetrics

Cloud Music’s middleware team built the Pylon APM monitoring system on VictoriaMetrics, combining exporters, vmagent, Nacos, Flink‑based pre‑aggregation recording rules and vminsert for collection with Grafana, a custom Proxy and vmselect for querying, achieving millisecond‑level latency, metric‑trace correlation, stability improvements, and cost‑effective storage for nearly 700 million active time series.

APM monitoringFlinkMetric Pre-aggregation
0 likes · 12 min read
Building Cloud Music's APM Metric Monitoring System Based on VictoriaMetrics
Aikesheng Open Source Community
Aikesheng Open Source Community
Jan 2, 2024 · Databases

HoraeDB (formerly CeresDB) Joins Apache Incubator: Design Goals, Architecture, and Core Features

HoraeDB, the open‑source time‑series database formerly known as CeresDB, has been accepted into the Apache Incubator, and the announcement details its design objectives, cloud‑native architecture, distributed solution, key features such as high performance, low cost, compute‑storage separation, and how developers can contribute to the project.

Apache Incubatortime_series_database
0 likes · 6 min read
HoraeDB (formerly CeresDB) Joins Apache Incubator: Design Goals, Architecture, and Core Features
Didi Tech
Didi Tech
Sep 26, 2023 · Databases

Didi's Time Series Storage Evolution: From InfluxDB to VictoriaMetrics

Facing exponential growth of time‑series data from 2017 to 2023, Didi migrated from InfluxDB to RRDtool, then to an in‑memory cache layer, and finally adopted VictoriaMetrics because its low‑cost commodity‑hardware operation, high write throughput, strong compression, and easy horizontal scaling solved the earlier storage, OOM, and scalability problems.

ObservabilityTSDBVictoriaMetrics
0 likes · 13 min read
Didi's Time Series Storage Evolution: From InfluxDB to VictoriaMetrics
Efficient Ops
Efficient Ops
May 24, 2023 · Operations

How Ant Group Solves Client Observability Challenges with CeresDB and AI

This article explains Ant Group's client observability system, the technical difficulties of tracing, logging, and metrics on mobile clients, and presents their open‑source solutions—including a custom time‑series database, dimension‑join services, and intelligent alerting—to handle massive data and multi‑dimensional analysis.

AICeresDBTracing
0 likes · 15 min read
How Ant Group Solves Client Observability Challenges with CeresDB and AI
ITPUB
ITPUB
May 17, 2023 · Databases

InfluxDB vs Kdb+ vs Prometheus: Which Time‑Series Database Wins?

This article compares three leading time‑series databases—InfluxDB, Kdb+, and Prometheus—detailing their origins, core features, strengths, and drawbacks, and helps readers decide which solution best fits specific monitoring, IoT, or financial data workloads.

InfluxDBKdb+performance
0 likes · 13 min read
InfluxDB vs Kdb+ vs Prometheus: Which Time‑Series Database Wins?
Efficient Ops
Efficient Ops
Apr 4, 2023 · Databases

Master InfluxDB: From Basics to Advanced Queries and Retention Policies

This guide explains InfluxDB's architecture, data model, CRUD commands, measurement handling, retention policies, query syntax, time‑zone considerations, and service management, providing a comprehensive tutorial for developers working with time‑series databases.

Data InsertionInfluxDBRetention Policies
0 likes · 10 min read
Master InfluxDB: From Basics to Advanced Queries and Retention Policies
Open Source Linux
Open Source Linux
Mar 9, 2023 · Operations

Prometheus vs Zabbix: Which Monitoring Tool Wins for Modern Ops?

An in‑depth comparison of Prometheus and Zabbix examines their histories, architectures, data storage, scalability, and container support, highlighting Prometheus’s cloud‑native pull model and Go‑based performance versus Zabbix’s mature, relational‑database approach, to help teams choose the right monitoring solution.

MonitoringZabbixcloud-native
0 likes · 8 min read
Prometheus vs Zabbix: Which Monitoring Tool Wins for Modern Ops?
ITPUB
ITPUB
Dec 4, 2022 · Cloud Native

How Qunar Scaled Container Monitoring with VictoriaMetrics: A Cloud‑Native Case Study

This article details Qunar's migration from a Prometheus‑based monitoring stack to VictoriaMetrics, describing the limitations they faced, the architectural redesign using vmagent, vmcluster, and vmalert, and the resulting performance improvements and operational benefits for large‑scale Kubernetes environments.

Cloud NativeMonitoringVictoriaMetrics
0 likes · 14 min read
How Qunar Scaled Container Monitoring with VictoriaMetrics: A Cloud‑Native Case Study
Qunar Tech Salon
Qunar Tech Salon
Nov 29, 2022 · Cloud Native

Qunar’s Experience Replacing Prometheus with VictoriaMetrics for Cloud‑Native Container Monitoring

This article details Qunar’s migration from a traditional Prometheus‑based monitoring stack to VictoriaMetrics, describing the challenges of large‑scale container metrics collection, the architectural redesign using VM‑Cluster, vmagent, and vmalert, and the performance improvements achieved after full replacement.

VictoriaMetricskubernetesprometheus
0 likes · 14 min read
Qunar’s Experience Replacing Prometheus with VictoriaMetrics for Cloud‑Native Container Monitoring
21CTO
21CTO
Nov 9, 2022 · Operations

How Ctrip Handles Billions of Logs Daily: Real‑Time Monitoring, Clog, CAT & TSDB

This article details Ctrip’s large‑scale log monitoring architecture, covering the overall Overview, the Clog log system, the CAT tracing platform, and the internal TSDB solution, explaining how billions of logs are processed in real time with low latency, high reliability, and efficient querying.

Big DataLog MonitoringReal-time Processing
0 likes · 12 min read
How Ctrip Handles Billions of Logs Daily: Real‑Time Monitoring, Clog, CAT & TSDB
DataFunSummit
DataFunSummit
Oct 24, 2022 · Databases

Intelligent Operations: Challenges and Solutions with the IoTDB Time‑Series Database

This article examines the data challenges faced by intelligent operations (AIOps), evaluates IoTDB against other time‑series databases through performance benchmarks, outlines Cloudwise's architecture and open‑source contributions, and presents real‑world case studies demonstrating anomaly detection and root‑cause analysis in industrial settings.

AIOpsBig DataIoTDB
0 likes · 15 min read
Intelligent Operations: Challenges and Solutions with the IoTDB Time‑Series Database
dbaplus Community
dbaplus Community
Sep 5, 2022 · Operations

How EyesTSDB Evolved into a Cloud‑Native, Second‑Level Monitoring Platform

This article details the evolution of NetEase's self‑built time‑series database EyesTSDB into a cloud‑native, second‑level monitoring solution, covering its architecture, core features, integration with VictoriaMetrics, custom plugin workflow, CMDB linkage, real‑world use cases, and future challenges.

CMDB integrationMetricsMonitoring
0 likes · 21 min read
How EyesTSDB Evolved into a Cloud‑Native, Second‑Level Monitoring Platform
Efficient Ops
Efficient Ops
Aug 14, 2022 · Databases

How TDengine 3.0 Redefines Cloud‑Native Time‑Series Databases

The TDengine Developer Conference in Beijing unveiled the open‑source, cloud‑native TDengine 3.0, detailing its revolutionary architecture that tackles high‑cardinality challenges, introduces RAFT‑based distribution, and showcases real‑world IoT and IT‑operations case studies where enterprises dramatically improved performance and reduced costs.

Data ArchitectureIoTTDengine
0 likes · 11 min read
How TDengine 3.0 Redefines Cloud‑Native Time‑Series Databases
AntTech
AntTech
Aug 2, 2022 · Databases

Introducing CeresDB: An Open‑Source Distributed High‑Performance Time Series Database

CeresDB, a distributed high‑availability time‑series database originally built at Ant Group, is now open‑sourced with version 0.2.0, offering high‑throughput writes, multi‑dimensional queries, SQL support, compatibility with Prometheus and OpenTSDB, and a range of features targeting both monitoring and analytical workloads.

CeresDBSQLopen source
0 likes · 11 min read
Introducing CeresDB: An Open‑Source Distributed High‑Performance Time Series Database
DataFunTalk
DataFunTalk
Jul 6, 2022 · Databases

Apache IoTDB Overview: Open‑File Time Series Database, TsFile Format, Architecture and Community

This article introduces Apache IoTDB, an open‑file based time‑series database designed for industrial IoT, explains its TsFile storage format, data modeling options, layered architecture (embedded, edge, cloud), performance advantages over traditional formats, and highlights the active open‑source community and real‑world deployments.

Apache IoTDBBig DataIoT
0 likes · 18 min read
Apache IoTDB Overview: Open‑File Time Series Database, TsFile Format, Architecture and Community
ITPUB
ITPUB
Jul 1, 2022 · Databases

What’s New in Apache IoTDB? Exploring the Latest Features for Industrial IoT

This article introduces Apache IoTDB, an open‑source time‑series database for industrial IoT, outlines its recent feature releases, explains its data‑modeling and compression strategies, and discusses UDF, trigger, and quality‑control capabilities that guide technical selection and architecture design.

Apache IoTDBBig DataIndustrial IoT
0 likes · 12 min read
What’s New in Apache IoTDB? Exploring the Latest Features for Industrial IoT
vivo Internet Technology
vivo Internet Technology
Feb 16, 2022 · Operations

Vivo Server Monitoring System Architecture and Evolution: A Comprehensive Technical Guide

Vivo’s vmonitor system replaces its legacy RabbitMQ‑based pipeline with an HTTP‑driven collector and gateway, stores minute‑level JVM, system, and business metrics in a customized OpenTSDB on HBase, adds precise floating‑point handling and null‑aware aggregation, buffers data in Redis, and provides multi‑dimensional alerts comparable to Zabbix, Open‑Falcon, and Prometheus.

AlertingDistributed MonitoringJVM Monitoring
0 likes · 18 min read
Vivo Server Monitoring System Architecture and Evolution: A Comprehensive Technical Guide
DataFunTalk
DataFunTalk
Jan 16, 2022 · Big Data

Time Series Database Capabilities and Application Scenarios in IoT, Smart Cities, and Edge Computing

This article explains the fundamentals of time‑series data, outlines the architecture and core technical advantages of Baidu Cloud's TSDB, and demonstrates how the database powers IoT, smart‑city, industrial, power‑grid, and autonomous‑driving use cases through multi‑level storage, distributed query optimization, and edge‑cloud integration.

Big DataCloud ComputingDistributed storage
0 likes · 11 min read
Time Series Database Capabilities and Application Scenarios in IoT, Smart Cities, and Edge Computing
Efficient Ops
Efficient Ops
Sep 5, 2021 · Operations

Why Prometheus’s TSDB Makes Monitoring Scalable: A Deep Dive

This article explains how Prometheus’s time‑series database handles massive monitoring data, illustrates practical query examples, and shows why its storage engine and pre‑computation features enable efficient, high‑performance observability for large‑scale services.

MonitoringObservabilityTSDB
0 likes · 8 min read
Why Prometheus’s TSDB Makes Monitoring Scalable: A Deep Dive
Open Source Linux
Open Source Linux
Aug 24, 2021 · Operations

Why Prometheus Became the Leading Cloud‑Native Monitoring Solution

This article explains how Prometheus evolved from a Google internal project to a CNCF‑graduated, top‑ranked time‑series database and full‑stack monitoring ecosystem, detailing its history, core features, architecture, and the roles of its components such as Exporters, Pushgateway, Service Discovery, and Alertmanager.

Monitoringcloud-nativeprometheus
0 likes · 19 min read
Why Prometheus Became the Leading Cloud‑Native Monitoring Solution
360 Quality & Efficiency
360 Quality & Efficiency
Aug 6, 2021 · Databases

Introduction to Time Series Databases and InfluxDB 2.0: Architecture, Features, Installation, and Practical Applications

This article explains what time series databases are, introduces InfluxDB as the leading TSDB, describes its TICK architecture and storage engine, provides step‑by‑step installation and configuration of InfluxDB and Telegraf, demonstrates visualization, JMeter integration, and Flux queries in Python, and highlights the rapid market growth of TSDBs.

FluxInfluxDBPython
0 likes · 11 min read
Introduction to Time Series Databases and InfluxDB 2.0: Architecture, Features, Installation, and Practical Applications
DataFunTalk
DataFunTalk
Jul 20, 2021 · Databases

Time‑Series Database Series: Trends, Design Principles, and Comparative Analysis of OpenTSDB, InfluxDB, and Apache IoTDB

This article explores the evolution and current landscape of time‑series databases, detailing design principles, storage structures such as B‑Tree, B+Tree, and LSM‑Tree, and providing an in‑depth comparison of OpenTSDB, InfluxDB, and the emerging Apache IoTDB, while also discussing practical deployment considerations and industry use cases.

Apache IoTDBB+TreeInfluxDB
0 likes · 38 min read
Time‑Series Database Series: Trends, Design Principles, and Comparative Analysis of OpenTSDB, InfluxDB, and Apache IoTDB
DataFunTalk
DataFunTalk
Apr 19, 2021 · Databases

Current Trends, Core Technologies, and Challenges of Time Series Databases

This article reviews the rapid growth of global data, examines the evolving landscape and classification of time‑series databases, analyzes storage engine designs such as B‑Tree versus LSM‑Tree, discusses query optimization and real‑time analytics, and outlines practical application scenarios in IoT and industrial settings.

IoTLSM‑Treetime_series_database
0 likes · 19 min read
Current Trends, Core Technologies, and Challenges of Time Series Databases
DeWu Technology
DeWu Technology
Mar 19, 2021 · Databases

TDengine Deployment for Sentinel Flow Control Data at DeWu

DeWu chose the open‑source time‑series database TDengine to store billions of daily Sentinel flow‑control metrics, using a super‑table design with per‑resource tables, a three‑node cluster, Druid/MyBatis pooling, and raw‑SQL writes, achieving 10 ms batch write latency, sub‑millisecond queries, and 90 % compression.

JDBCJavaSentinel
0 likes · 11 min read
TDengine Deployment for Sentinel Flow Control Data at DeWu
JD Cloud Developers
JD Cloud Developers
Sep 15, 2020 · Databases

How JD’s HoraeDB Tackles Massive Time‑Series Data at Scale

This article introduces JD Cloud’s self‑built time‑series database HoraeDB, explaining its core concepts, typical use cases, architectural layers, high‑performance features, down‑sampling strategies, compression techniques, and stability measures for handling massive, 24‑hour monitoring data at scale.

Distributed storageDownsamplingMonitoring
0 likes · 18 min read
How JD’s HoraeDB Tackles Massive Time‑Series Data at Scale
vivo Internet Technology
vivo Internet Technology
Apr 29, 2020 · Cloud Native

Prometheus Architecture and Design Principles: A Deep Dive into Cloud-Native Monitoring

Prometheus, a CNCF‑graduated, cloud‑native monitoring system, combines pull‑based target discovery, a label‑rich time‑series data model, and four core metric types—gauge, counter, histogram, and summary—to provide near‑real‑time visibility, short‑term retention, alerting via AlertManager, and integration with Grafana and remote storage for scalable observability.

AlertmanagerCNCFMonitoring
0 likes · 11 min read
Prometheus Architecture and Design Principles: A Deep Dive into Cloud-Native Monitoring
360 Quality & Efficiency
360 Quality & Efficiency
Feb 28, 2020 · Operations

External Network Quality Monitoring System at 360: Architecture, Features, and Alert Strategies

The article details 360's external network quality monitoring system, explaining its background, real‑time detection features, CDN‑based source host selection, three‑layer architecture, data collection and storage pipelines, fault‑diagnosis strategies, and visualization approaches for rapid network fault localization.

AlertingCDNfault detection
0 likes · 10 min read
External Network Quality Monitoring System at 360: Architecture, Features, and Alert Strategies
360 Tech Engineering
360 Tech Engineering
Feb 6, 2020 · Operations

External Network Quality Monitoring System at 360: Architecture, Features, and Alert Strategies

The article describes how 360 implements an external network quality monitoring system that uses CDN nodes as source hosts to perform minute‑level, end‑to‑end ping measurements, stores results in time‑series and other databases, analyzes them to detect VIP, data‑center or ISP faults, and generates visualized alerts and reports for operations teams.

AlertingCDNnetwork monitoring
0 likes · 8 min read
External Network Quality Monitoring System at 360: Architecture, Features, and Alert Strategies
Efficient Ops
Efficient Ops
Dec 24, 2019 · Operations

Scaling Real‑Time Monitoring for Billion‑Call Billing with Prometheus

Jiangsu Mobile’s IT operations team partnered with Newland to build a high‑availability, real‑time performance management platform using Prometheus, achieving billion‑level call‑record monitoring, low‑latency queries, data compression, and advanced forecasting, dramatically improving system health visibility and operational efficiency.

performance managementprometheustime_series_database
0 likes · 10 min read
Scaling Real‑Time Monitoring for Billion‑Call Billing with Prometheus
System Architect Go
System Architect Go
Nov 17, 2019 · Databases

Handling Single Point Failures and Disaster Recovery in InfluxDB

To mitigate the inherent single‑point‑failure risk of the open‑source InfluxDB community edition, the article proposes deploying multiple InfluxDB instances with concurrent client writes, tracking failed writes, temporarily storing them, and using custom workers to replay data, while addressing timeout, data consistency, and storage considerations.

Data ConsistencyDisaster RecoveryHigh Availability
0 likes · 3 min read
Handling Single Point Failures and Disaster Recovery in InfluxDB
System Architect Go
System Architect Go
Oct 28, 2019 · Databases

InfluxDB Storage Engine Architecture and Hardware Recommendations

This article explains InfluxDB's storage engine workflow—including WAL, Cache, TSM files, compression components, and file management—then provides hardware sizing guidance based on write/query load, series cardinality, and recommends SSD storage with sample configuration settings.

HardwareInfluxDBStorage Engine
0 likes · 5 min read
InfluxDB Storage Engine Architecture and Hardware Recommendations
System Architect Go
System Architect Go
Oct 25, 2019 · Databases

Understanding InfluxDB: Core Concepts, Architecture, and Design Trade‑offs of a Time‑Series Database

This article explains the fundamentals of time‑series databases, introduces InfluxDB’s key components such as databases, measurements, retention policies, tags, fields, series, and points, describes the line protocol syntax, compares it with traditional databases, and outlines the design trade‑offs that shape its performance and limitations.

Database DesignInfluxDBLine Protocol
0 likes · 10 min read
Understanding InfluxDB: Core Concepts, Architecture, and Design Trade‑offs of a Time‑Series Database
58 Tech
58 Tech
Mar 27, 2019 · Databases

OpenTSDB Architecture, Data Model, Storage Optimizations, and Practical Use Cases

This article introduces OpenTSDB as a distributed, scalable time‑series database built on HBase, explains its architecture, data model, and storage optimizations, presents real‑world monitoring use cases, analyzes performance issues caused by high‑cardinality tags, and details the solution steps taken to restore query speed.

HBaseOpenTSDBStorage Optimization
0 likes · 9 min read
OpenTSDB Architecture, Data Model, Storage Optimizations, and Practical Use Cases
HomeTech
HomeTech
Mar 7, 2019 · Operations

Design and Implementation of a Sonar Monitoring System for Spring Boot Applications

This article presents the design, architecture, and technology choices of a Sonar monitoring system for Spring Boot microservices, covering time‑series database selection, deployment topology, client collection strategies, and future plans for advanced analytics and AI‑driven alerting.

InfluxDBMicroservicesSpring Boot
0 likes · 15 min read
Design and Implementation of a Sonar Monitoring System for Spring Boot Applications
dbaplus Community
dbaplus Community
Apr 24, 2018 · Databases

Scaling Baidu’s TSDB to Trillions of Points: Elastic, High‑Performance Architecture

Baidu’s TSDB processes over 20 million data points per second per node and tens of thousands of queries per second cluster‑wide by employing a stateless read/write‑separated elastic architecture, multi‑layer storage across Redis, HBase and Hadoop, minute‑level geo‑redundant self‑healing, and a modified Gorilla compression that cuts storage by 80% with minimal CPU overhead.

Big DataHigh AvailabilityScalable Architecture
0 likes · 8 min read
Scaling Baidu’s TSDB to Trillions of Points: Elastic, High‑Performance Architecture
Alibaba Cloud Developer
Alibaba Cloud Developer
Apr 19, 2018 · Databases

How HiTSDB’s New Streaming Aggregation Engine Boosts Query Speed 10×

This article examines the architectural redesign of Alibaba's High‑Performance Time Series Database (HiTSDB), covering storage model changes, inverted‑index enhancements, a pipelined streaming aggregation engine, data‑migration strategies, and performance benchmarks that together deliver over tenfold query speed improvements.

Data MigrationHiTSDBPerformance Optimization
0 likes · 24 min read
How HiTSDB’s New Streaming Aggregation Engine Boosts Query Speed 10×
Tencent Architect
Tencent Architect
Dec 30, 2017 · Databases

An Overview of Time Series Databases and Tencent CTSDB

This article introduces the concept, characteristics, and use cases of time series databases, explains the data model and challenges of traditional solutions, and provides a detailed overview of Tencent's Cloud Time Series Database (CTSDB) along with performance comparisons against InfluxDB.

Big DataCTSDBDistributed storage
0 likes · 12 min read
An Overview of Time Series Databases and Tencent CTSDB
Qudian (formerly Qufenqi) Technology Team
Qudian (formerly Qufenqi) Technology Team
Jan 18, 2017 · Operations

Building a Scalable Business Monitoring System: Architecture, Modules & Lessons

This article presents a comprehensive case study of a business monitoring system, covering its background, architectural analysis, module design, time‑series database selection, visualization with Grafana, alerting strategies, decision‑making logic, and intelligent monitoring experiments, followed by key takeaways and lessons learned.

InfluxDBMonitoringOperations
0 likes · 12 min read
Building a Scalable Business Monitoring System: Architecture, Modules & Lessons