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Real-time Analytics

306 articles · Page 2 of 4
DataFunSummit
DataFunSummit
Dec 7, 2023 · Databases

Apache Doris: A High‑Performance Real‑Time Analytical Database for Online High‑Concurrency Reporting

This article introduces Apache Doris, a real‑time analytical database built on an MPP architecture, explains its suitability for massive data workloads and online high‑concurrency reporting scenarios, and details the core technologies—storage models, vectorized query engine, materialized views, partitioning, indexing, row‑store and prepared statements—that enable sub‑second query latency and high QPS, while also showing a real‑world case study and how to join the Doris community.

Apache DorisHigh ConcurrencyMaterialized Views
0 likes · 13 min read
Apache Doris: A High‑Performance Real‑Time Analytical Database for Online High‑Concurrency Reporting
Big Data Technology Architecture
Big Data Technology Architecture
Nov 29, 2023 · Big Data

Building Real-Time Wide Tables with Partial-Update Using Apache Paimon for NetEase News Recommendation

The article describes how NetEase News' recommendation team replaced a slow, batch‑oriented data‑warehouse pipeline with a Flink‑based, Apache Paimon real‑time wide‑table solution that supports partial updates, reduces latency from hours to minutes, and lowers processing costs while handling both deduplication and non‑deduplication recommendation scenarios.

Apache PaimonData LakeFlink
0 likes · 8 min read
Building Real-Time Wide Tables with Partial-Update Using Apache Paimon for NetEase News Recommendation
DataFunSummit
DataFunSummit
Oct 31, 2023 · Big Data

Customer Data Platform (CDP) at Qunar Travel: Business Background, Construction Practice, Applications, and Future Outlook

This article details Qunar Travel's multi‑year development of a Customer Data Platform (CDP), covering its business motivations, architectural design, tag‑based data processing, real‑time and offline pipelines, user segmentation, marketing automation, performance optimizations, and future directions for model‑driven personalization.

Customer Data PlatformReal-time AnalyticsUser Segmentation
0 likes · 18 min read
Customer Data Platform (CDP) at Qunar Travel: Business Background, Construction Practice, Applications, and Future Outlook
DataFunTalk
DataFunTalk
Oct 25, 2023 · Databases

Apache Doris Summit Asia 2023: Highlights, Innovations, and Industry Use Cases

The Apache Doris Summit Asia 2023 showcased the milestone 2.0 release, impressive performance gains, rapid community growth, and diverse industry deployments, while outlining future cloud‑native and unified analytics directions that position Doris as a leading real‑time data warehouse solution.

Apache DorisReal-time AnalyticsSelectDB
0 likes · 13 min read
Apache Doris Summit Asia 2023: Highlights, Innovations, and Industry Use Cases
DataFunTalk
DataFunTalk
Oct 13, 2023 · Big Data

Design Principles, Architecture, and Applications of the Open‑Source LakeSoul Lakehouse Framework

This article provides a comprehensive technical overview of LakeSoul, an open‑source, cloud‑native lakehouse framework, covering its design philosophy, core features, architecture, performance benchmarks, real‑time ingestion, incremental computation, multi‑stream joining, security, community progress, and future roadmap.

FlinkLakeSoulReal-time Analytics
0 likes · 16 min read
Design Principles, Architecture, and Applications of the Open‑Source LakeSoul Lakehouse Framework
DeWu Technology
DeWu Technology
Sep 6, 2023 · Industry Insights

From Simple Split Tests to Real‑Time Multi‑Layer Experiments: The Evolution of an AB Testing Platform

This article traces the step‑by‑step evolution of an AB testing platform—from its initial 1.0 version with basic traffic splitting, through the 2.0 era that introduced multi‑layer orthogonal traffic models and real‑time metric pipelines, to the 3.0 era focused on usability, stability, and advanced analysis—while sharing concrete design decisions, implementation details, and lessons learned.

A/B testingReal-time Analyticsexperiment platform
0 likes · 25 min read
From Simple Split Tests to Real‑Time Multi‑Layer Experiments: The Evolution of an AB Testing Platform
JD Retail Technology
JD Retail Technology
Sep 4, 2023 · Big Data

JD Mini Program Data Center: Architecture, Milestones, and Real‑time Analytics Solutions

The article details the JD Mini Program platform, its data‑center development milestones, comprehensive business panorama, technical architecture, data collection, storage, and analysis pipelines—including Flink‑based real‑time monitoring, ClickHouse custom analytics, and Elasticsearch user‑behavior insights—while outlining current challenges and future AI‑driven enhancements.

ClickHouseElasticsearchFlink
0 likes · 16 min read
JD Mini Program Data Center: Architecture, Milestones, and Real‑time Analytics Solutions
DataFunTalk
DataFunTalk
Sep 4, 2023 · Big Data

Unified Batch‑Stream Storage with Hudi and LAS: Architecture, Design, and Deployment

This article presents a comprehensive overview of a batch‑stream unified storage solution built on Hudi and the Lakehouse Analysis Service (LAS), covering background challenges, architectural design, data organization, read/write mechanisms, BTS architecture, real‑world deployment scenarios, and future development plans.

Batch-StreamHudiLAS
0 likes · 22 min read
Unified Batch‑Stream Storage with Hudi and LAS: Architecture, Design, and Deployment
DataFunTalk
DataFunTalk
Sep 3, 2023 · Big Data

Evolution of OLAP at Xingyun Retail Credit Using Apache Doris

This article details how Xingyun Retail Credit transitioned from traditional data warehouses to an Apache Doris‑based OLAP solution, covering data demand generation, OLAP engine selection challenges, multi‑stage implementation, performance optimizations, data‑warehouse construction, real‑world use cases, and future roadmap.

Apache DorisETLOLAP
0 likes · 16 min read
Evolution of OLAP at Xingyun Retail Credit Using Apache Doris
AsiaInfo Technology: New Tech Exploration
AsiaInfo Technology: New Tech Exploration
Aug 18, 2023 · Big Data

How Lakehouse Architecture is Transforming Hadoop: A Deep Dive into Hudi, Iceberg, and Delta Lake

This article analyzes the rise of lake‑house architecture in the Hadoop ecosystem, compares the technical capabilities of Hudi, Iceberg and Delta Lake, details implementation enhancements such as MOR and multi‑writer support, showcases Flink integration, presents a real‑time marketing use case, and outlines future development directions.

Delta LakeHadoopHudi
0 likes · 14 min read
How Lakehouse Architecture is Transforming Hadoop: A Deep Dive into Hudi, Iceberg, and Delta Lake
JD Cloud Developers
JD Cloud Developers
Jul 19, 2023 · Databases

Why ClickHouse Is the Ideal Choice for Massive Data Storage and Real‑Time Analytics

This article examines the massive‑scale data requirements of an activity‑tracking platform, compares MySQL, Elasticsearch and HBase, and explains why ClickHouse—with its columnar storage, MergeTree engine, vectorized execution, and distributed architecture—offers the best combination of storage capacity, write performance, real‑time analysis, and query speed for billions of records.

ClickHouseColumnar DatabaseMergeTree
0 likes · 31 min read
Why ClickHouse Is the Ideal Choice for Massive Data Storage and Real‑Time Analytics
Architect
Architect
Jul 10, 2023 · Big Data

Understanding Lambda Architecture for Real‑Time Billion‑Scale Data Analysis

This article explains the Lambda Architecture—a three‑layer big‑data processing model combining batch and speed layers to deliver accurate, low‑latency analytics, and illustrates its use with Twitter hashtag tracking and a smart‑parking recommendation system.

Batch ProcessingLambda ArchitectureReal-time Analytics
0 likes · 10 min read
Understanding Lambda Architecture for Real‑Time Billion‑Scale Data Analysis
DataFunTalk
DataFunTalk
Jul 7, 2023 · Databases

Apache Doris 2.0-beta Release: New Query Optimizer, Pipeline Execution Engine, Workload Management and Major Performance Improvements

Apache Doris 2.0-beta, released on July 3, 2023, introduces a new Cascades‑based query optimizer, adaptive pipeline execution engine, workload‑aware resource isolation, enhanced memory management, partial column updates, multi‑catalog support, and numerous performance gains across real‑time analytics, ETL, and high‑concurrency point queries.

Apache DorisPipeline ExecutionReal-time Analytics
0 likes · 25 min read
Apache Doris 2.0-beta Release: New Query Optimizer, Pipeline Execution Engine, Workload Management and Major Performance Improvements
iQIYI Technical Product Team
iQIYI Technical Product Team
Jun 30, 2023 · Big Data

Advertising Data Lake Architecture and Real-time Optimizations

By replacing the costly Lambda architecture with a unified data‑lake built on Iceberg and Flink CDC, the advertising team achieved minute‑level latency, strong consistency, and lower storage expenses, cutting end‑to‑end processing times from hours to a few minutes across budgeting, warehousing, OLAP and ETL workloads.

AdvertisingFlinkReal-time Analytics
0 likes · 13 min read
Advertising Data Lake Architecture and Real-time Optimizations
Alibaba Cloud Big Data AI Platform
Alibaba Cloud Big Data AI Platform
Jun 27, 2023 · Big Data

How MaxCompute’s Lakehouse Architecture Enables Near‑Real‑Time Incremental Processing

This article details Alibaba Cloud MaxCompute’s lakehouse evolution, describing its unified storage‑metadata‑compute design, the Transactional Table 2.0 format, near‑real‑time incremental ingestion, clustering and compaction services, transaction handling, TimeTravel and incremental queries, and future roadmap for big‑data workloads.

Incremental ProcessingLakehouseMaxCompute
0 likes · 23 min read
How MaxCompute’s Lakehouse Architecture Enables Near‑Real‑Time Incremental Processing
DataFunTalk
DataFunTalk
May 19, 2023 · Big Data

Log Analysis and Schema‑On‑Read: Design and Implementation of the Honghu Real‑Time Heterogeneous Data Platform

This article examines the challenges and value of log analysis, introduces the concepts of schema‑on‑read versus schema‑on‑write, and details how the Honghu platform implements real‑time, one‑stop heterogeneous data analytics with flexible storage, indexing, and SQL‑based query engines.

Real-time Analyticslog-analysisschema-on-read
0 likes · 24 min read
Log Analysis and Schema‑On‑Read: Design and Implementation of the Honghu Real‑Time Heterogeneous Data Platform
Tongcheng Travel Technology Center
Tongcheng Travel Technology Center
May 17, 2023 · Databases

StarRocks Production Practice at Tongcheng Travel: Architecture, Use Cases, and Technical Evaluation

This article details Tongcheng Travel’s production deployment of the StarRocks OLAP database, covering background, business scenarios, technical evaluation against ClickHouse and Greenplum, implementation with Flink SQL, real‑time analytics, offline reporting, CDP use cases, performance optimizations, and future cloud‑native plans.

FlinkOLAPReal-time Analytics
0 likes · 12 min read
StarRocks Production Practice at Tongcheng Travel: Architecture, Use Cases, and Technical Evaluation
ITPUB
ITPUB
Mar 28, 2023 · Big Data

How We Turned a Hive Data Warehouse into a Real‑Time Lakehouse with Apache Hudi

This article details the migration from a traditional Hive‑based data warehouse to a lakehouse architecture using Apache Hudi, covering the original Lambda setup, its pain points, lake‑vs‑warehouse differences, Hudi features, integration challenges, practical solutions, and future roadmap.

Apache HudiFlinkHive
0 likes · 11 min read
How We Turned a Hive Data Warehouse into a Real‑Time Lakehouse with Apache Hudi
ITPUB
ITPUB
Mar 13, 2023 · Databases

10 Years of Amazon Redshift: From MPP to Serverless and Real‑Time Data Warehousing

This article traces a decade of Amazon Redshift’s evolution, detailing its shift from a traditional MPP warehouse to a fully cloud‑native Serverless architecture, exploring its underlying innovations, key features such as Concurrency Scaling, built‑in ML, Data Sharing, and offering practical best‑practice guidance for real‑time analytics across diverse industry scenarios.

Amazon RedshiftCloud ComputingConcurrency Scaling
0 likes · 17 min read
10 Years of Amazon Redshift: From MPP to Serverless and Real‑Time Data Warehousing
DataFunSummit
DataFunSummit
Mar 9, 2023 · Big Data

Designing Efficient and Agile Real-Time Big Data Analytics Platforms for Enterprises

The article explains how enterprises can build a comprehensive big data analytics platform—covering data collection, storage, computation, and decision layers—by clarifying business scenarios, choosing appropriate on‑premise or cloud deployment, selecting suitable architectures such as Lambda/Kappa, and addressing component choices and emerging technical trends.

Real-time Analyticsanalytics platformbig data
0 likes · 9 min read
Designing Efficient and Agile Real-Time Big Data Analytics Platforms for Enterprises
StarRocks
StarRocks
Feb 21, 2023 · Databases

How Yidian Tianxia Built a Unified Real‑Time & Offline Data Warehouse with StarRocks

Yidian Tianxia tackled massive daily data volumes and complex analytics by defining a five‑layer data‑warehouse standard, comparing ClickHouse and StarRocks performance, and implementing a unified real‑time/offline architecture with StarRocks, DataPlus, and EasyJob, achieving multi‑fold query speedups and lower operational costs.

ClickHouseReal-time AnalyticsStarRocks
0 likes · 14 min read
How Yidian Tianxia Built a Unified Real‑Time & Offline Data Warehouse with StarRocks
ITPUB
ITPUB
Feb 13, 2023 · Databases

How Apache Doris Enables Cloud‑Native Real‑Time Data Warehousing for Log Analytics

Based on a DTCC2022 presentation, this article explains Apache Doris's high‑performance MPP architecture, its cloud‑native extensions in SelectDB, and how they solve large‑scale log storage and analysis with superior write throughput, storage efficiency, and interactive query speed.

Apache DorisMPPReal-time Analytics
0 likes · 11 min read
How Apache Doris Enables Cloud‑Native Real‑Time Data Warehousing for Log Analytics
Past Memory Big Data
Past Memory Big Data
Feb 1, 2023 · Databases

From ClickHouse to ByteHouse: Real‑Time Data Analytics Optimization Practices

This article details ByteDance's large‑scale ClickHouse deployment, presents two real‑time analytics use cases—recommendation metrics and ad delivery—and explains the performance bottlenecks encountered and the concrete engineering solutions such as asynchronous indexing, multi‑threaded Kafka Engine, and enhanced Buffer Engine that boosted throughput and ensured data integrity.

Buffer EngineByteHouseClickHouse
0 likes · 11 min read
From ClickHouse to ByteHouse: Real‑Time Data Analytics Optimization Practices
Data Thinking Notes
Data Thinking Notes
Jan 16, 2023 · Big Data

How Kuaishou Scaled Its Big Data Platform to Handle EB‑Level Data and Millions of Daily Tasks

This article details Kuaishou's one‑stop big data development platform, covering its massive scale, low‑code and real‑time capabilities, multi‑layer architecture, SLA guarantees, diagnostic tools, and future plans to further lower development barriers and democratize data engineering.

Low-Code DevelopmentReal-time AnalyticsSLA management
0 likes · 21 min read
How Kuaishou Scaled Its Big Data Platform to Handle EB‑Level Data and Millions of Daily Tasks
Alibaba Cloud Big Data AI Platform
Alibaba Cloud Big Data AI Platform
Jan 10, 2023 · Big Data

How Alibaba’s Dolphin Engine Uses Flink + Hologres for Real‑Time Big Data

The Dolphin engine, built by Alibaba’s Data Engine team, combines Flink and Hologres to deliver ultra‑large‑scale OLAP, streaming, batch, and AI capabilities for real‑time advertising analytics, offering smart materialization, intelligent indexing, and vector recall while supporting millions of advertisers and petabyte‑level data.

AIFlinkHologres
0 likes · 13 min read
How Alibaba’s Dolphin Engine Uses Flink + Hologres for Real‑Time Big Data
DataFunSummit
DataFunSummit
Jan 8, 2023 · Big Data

Streaming‑Batch Integrated Real‑time Multi‑dimensional Analysis

This article presents a comprehensive overview of evolving big‑data architectures—from classic offline warehouses to Lambda and Kappa models—and details a streaming‑batch integrated solution that addresses latency, data freshness, and multi‑table join challenges to achieve minute‑level real‑time multi‑dimensional analytics.

Batch ProcessingKappa ArchitectureLambda Architecture
0 likes · 18 min read
Streaming‑Batch Integrated Real‑time Multi‑dimensional Analysis
DataFunTalk
DataFunTalk
Dec 31, 2022 · Big Data

Glacier: An Intelligent Data Lake Architecture for Real‑Time Analytics and Machine Learning

This article presents Glacier, OPPO's intelligent data lake solution that builds on Iceberg Table Format to provide real‑time data ingestion, low‑latency queries, advanced indexing, and robust multi‑version management for both structured and unstructured data, tightly integrating with machine‑learning workflows.

Data LakeGlacierReal-time Analytics
0 likes · 20 min read
Glacier: An Intelligent Data Lake Architecture for Real‑Time Analytics and Machine Learning
ITPUB
ITPUB
Dec 21, 2022 · Databases

How OpenMLDB Guarantees Real‑Time, Consistent Features for Machine Learning at Scale

This article explains the data and feature engineering challenges of deploying machine learning, introduces OpenMLDB’s open‑source architecture—including offline Spark‑based processing, a high‑availability online engine with dual‑layer memory indexes, snapshot/binlog persistence, and pre‑aggregation techniques—then showcases real‑world case studies and the project’s roadmap.

Feature StoreOpenMLDBReal-time Analytics
0 likes · 15 min read
How OpenMLDB Guarantees Real‑Time, Consistent Features for Machine Learning at Scale
Alipay Experience Technology
Alipay Experience Technology
Nov 29, 2022 · Mobile Development

How Ant's Mobile Edge Computing Container Powers Real‑Time AI on Devices

This article explains the challenges of deploying intelligent features on mobile clients and describes Ant Group's edge computing container, its three‑layer architecture, real‑time compute, feature, and decision engines, and the low‑code platform that enables fast, stable, and scalable AI solutions on devices.

Real-time Analyticsdecision enginefeature engineering
0 likes · 15 min read
How Ant's Mobile Edge Computing Container Powers Real‑Time AI on Devices
Alibaba Cloud Big Data AI Platform
Alibaba Cloud Big Data AI Platform
Nov 29, 2022 · Big Data

How Flink’s Stream‑Batch Fusion Is Transforming Real‑Time Big Data

The article explores Apache Flink’s eight‑year journey to becoming a top‑level Apache project, Alibaba’s extensive contributions, the rise of stream‑batch unified computing, its impact on real‑time data integration, cloud‑native deployment, and the emerging Flink‑based data‑warehouse and serverless solutions.

Apache FlinkData IntegrationReal-time Analytics
0 likes · 15 min read
How Flink’s Stream‑Batch Fusion Is Transforming Real‑Time Big Data
TAL Education Technology
TAL Education Technology
Nov 17, 2022 · Big Data

Real-Time Data Warehouse: Background, Value Assessment, and Half-Year Progress

This article outlines the background and terminology of data warehousing, presents a formula for evaluating warehouse value, and details the team's half‑year efforts—including architecture selection, quality assurance, stability governance, and data‑value externalization—to improve efficiency, quality, stability, and cost in real‑time data services.

Data OperationsReal-time Analyticsdata governance
0 likes · 10 min read
Real-Time Data Warehouse: Background, Value Assessment, and Half-Year Progress
StarRocks
StarRocks
Nov 8, 2022 · Databases

How StarRocks’ Real‑Time Storage Engine Evolves to Meet Modern Analytics Demands

This article outlines the evolution of StarRocks’ storage engine—from its real‑time update capabilities and primary‑key model challenges to recent optimizations like persistent indexes, partial column updates, conditional updates, high‑frequency import improvements, DML support, and future plans for separating primary and sort keys, introducing row‑store, and enhancing materialized view support.

DMLReal-time AnalyticsRow Store
0 likes · 18 min read
How StarRocks’ Real‑Time Storage Engine Evolves to Meet Modern Analytics Demands
Alibaba Cloud Big Data AI Platform
Alibaba Cloud Big Data AI Platform
Nov 3, 2022 · Big Data

How Alibaba Cloud’s ODPS Upgrade Redefines Big Data Processing and AI Integration

Alibaba Cloud announced that its ODPS platform has been upgraded into an integrated big‑data solution that supports massive batch jobs, real‑time analytics, and AI workloads, delivering record‑breaking performance and enabling use cases from smart city traffic optimization to accelerated autonomous‑driving model training.

AIReal-time Analyticsbig data
0 likes · 5 min read
How Alibaba Cloud’s ODPS Upgrade Redefines Big Data Processing and AI Integration
DataFunSummit
DataFunSummit
Oct 15, 2022 · Cloud Computing

Design and Evolution of Tencent Cloud Product Metering and Billing System

The article presents a comprehensive overview of Tencent Cloud's metering and billing system, detailing the billing models, multi‑dimensional data analysis, real‑time data‑warehouse construction, operator orchestration, hot‑key handling, smooth upgrade strategies, and future evolution directions for large‑scale cloud services.

Cloud ComputingMulti-dimensional AnalysisReal-time Analytics
0 likes · 16 min read
Design and Evolution of Tencent Cloud Product Metering and Billing System
Past Memory Big Data
Past Memory Big Data
Sep 26, 2022 · Databases

How ClickHouse Gains Full Upsert and Delete Support with UniqueMergeTree

This article examines ClickHouse’s lack of native upsert and delete operations, explains how ByteHouse’s UniqueMergeTree engine introduces a Mark‑Delete + Insert approach to provide real‑time upsert/delete capabilities, and presents benchmark results showing dramatically faster queries with only modest write overhead.

ByteHouseClickHouseColumnar Database
0 likes · 10 min read
How ClickHouse Gains Full Upsert and Delete Support with UniqueMergeTree
dbaplus Community
dbaplus Community
Sep 14, 2022 · Databases

How Apache Doris Enables Real‑Time Analysis of Hudi Data Lakes

This article explains the architecture of Apache Doris, introduces Apache Hudi as a data‑lake format, compares Lambda and Kappa approaches, and details the design, implementation steps, and future roadmap for querying Hudi tables directly from Doris.

Apache DorisApache HudiData Lake
0 likes · 10 min read
How Apache Doris Enables Real‑Time Analysis of Hudi Data Lakes
DeWu Technology
DeWu Technology
Sep 14, 2022 · Databases

Introduction to StarRocks: Architecture, Storage, Use Cases, and Troubleshooting

StarRocks is a high‑performance MPP database whose simplified FE/BE architecture, fully vectorized engine, and CBO optimizer enable fast multi‑table joins, while its partition‑bucket‑tablet storage model supports real‑time metric services and dashboard migrations, accompanied by practical troubleshooting guidance and upcoming enhancements.

MPP databasePerformanceReal-time Analytics
0 likes · 15 min read
Introduction to StarRocks: Architecture, Storage, Use Cases, and Troubleshooting
Shopee Tech Team
Shopee Tech Team
Sep 2, 2022 · Big Data

Shopee Data System Challenges and Apache Hudi Practices

Shopee tackled its data‑system bottlenecks by customizing Apache Hudi to provide unified stream‑batch integration, efficient state‑detail snapshots, and low‑latency wide‑table generation, using CDC‑based bootstrapping, COW/MOR tables, savepoints and partial updates, which cut latency to ten minutes, lowered resource use, and yielded several community‑backed enhancements.

Apache HudiData IntegrationIncremental Processing
0 likes · 18 min read
Shopee Data System Challenges and Apache Hudi Practices
DataFunTalk
DataFunTalk
Jul 30, 2022 · Databases

StarRocks-Based Unified Data Service and Analytics Platform at JD Logistics

JD Logistics leverages StarRocks to create the Udata unified query engine, addressing data silos, low performance, and high maintenance costs by integrating data services and analytics, enabling low‑code data service generation, high‑speed federated queries, real‑time updates, and future data‑lake and resource isolation capabilities.

Data IntegrationReal-time AnalyticsStarRocks
0 likes · 14 min read
StarRocks-Based Unified Data Service and Analytics Platform at JD Logistics
DataFunSummit
DataFunSummit
Jul 28, 2022 · Databases

TiDB HTAP for Financial Intelligent Risk Control: Architecture, Challenges, and Solutions

This article presents a comprehensive overview of how TiDB's HTAP capabilities enable real‑time multi‑source data processing for financial intelligent risk control, detailing the overall risk‑control architecture, digital transformation challenges, TiDB‑based solutions, practical implementations, and future outlooks.

HTAPIntelligent Risk ControlReal-time Analytics
0 likes · 12 min read
TiDB HTAP for Financial Intelligent Risk Control: Architecture, Challenges, and Solutions
Efficient Ops
Efficient Ops
Jul 19, 2022 · Databases

How CDC Powers Real-Time Analytics Without Overloading Your Database

This article introduces the practice of Change Data Capture (CDC), explaining how capturing only data changes can feed downstream systems and data warehouses in near real‑time, reducing load on the source database, improving reporting latency, and supporting scalable, reliable analytics pipelines.

CDCReal-time Analyticschange data capture
0 likes · 9 min read
How CDC Powers Real-Time Analytics Without Overloading Your Database
DataFunTalk
DataFunTalk
Jul 18, 2022 · Big Data

Integrating Apache Doris with Hudi: Design, Implementation, and Future Plans

This article introduces Apache Doris, an MPP analytical database, and explains how it integrates with the Hudi data lake format, covering architectural features, design choices, implementation steps including external table creation and query processing, and outlines future enhancements for supporting MOR snapshots and incremental queries.

Apache DorisData LakeHudi
0 likes · 12 min read
Integrating Apache Doris with Hudi: Design, Implementation, and Future Plans
DataFunSummit
DataFunSummit
Jul 17, 2022 · Big Data

Elasticsearch and Big Data: Architecture, Use Cases, and Advantages

This article explains what Elasticsearch is, how it solves database acceleration, log observability, and data analysis problems, details its core components and underlying engine features, compares its strengths and weaknesses, and presents classic application scenarios and a real‑world case study integrating Elasticsearch with Flink for large‑scale log analytics.

ElasticsearchFlinkLog Management
0 likes · 13 min read
Elasticsearch and Big Data: Architecture, Use Cases, and Advantages
Shepherd Advanced Notes
Shepherd Advanced Notes
Jul 6, 2022 · Databases

Understanding Apache Doris: Real‑Time Analytical Database Architecture and Data Modeling

This article introduces Apache Doris, a high‑performance, real‑time analytical database built on an MPP architecture, covering its simple FE/BE design, three data‑model types (Aggregate, Unique, Duplicate), partitioning and bucketing strategies, rollup tables, and the limitations and best practices of row‑level updates.

Apache DorisData ModelingMPP
0 likes · 28 min read
Understanding Apache Doris: Real‑Time Analytical Database Architecture and Data Modeling
Xingsheng Youxuan Technology Community
Xingsheng Youxuan Technology Community
Jul 5, 2022 · Databases

Mastering Apache Druid: Architecture, Real-Time Ingestion, and Query Optimization

Apache Druid is a distributed, column‑store OLAP engine designed for massive real‑time data ingestion and sub‑second queries; this article explains its LSM‑tree‑inspired architecture, DataSource and Segment structures, memory‑based querying, practical deployment steps, common pitfalls, and optimization techniques for high‑throughput analytics.

Apache DruidData IngestionOLAP
0 likes · 20 min read
Mastering Apache Druid: Architecture, Real-Time Ingestion, and Query Optimization
dbaplus Community
dbaplus Community
Jun 14, 2022 · Big Data

How Qunar Built a Scalable BI Platform for Real‑Time Analytics and Self‑Service Reporting

This article details Qunar's multi‑year journey of designing and evolving a full‑stack BI platform—covering data ingestion, storage, query engines, self‑service analytics, and real‑time OLAP—by iterating through three development phases, selecting technologies such as Impala, Kudu, ClickHouse and Apache Druid, and addressing performance, usability and governance challenges to empower business users with fast, reliable data insights.

Apache DruidBIClickHouse
0 likes · 24 min read
How Qunar Built a Scalable BI Platform for Real‑Time Analytics and Self‑Service Reporting
Alibaba Cloud Developer
Alibaba Cloud Developer
Jun 14, 2022 · Big Data

Can a Streaming Data Warehouse Balance Freshness, Latency, and Cost?

This article examines the core trade‑offs of data warehouses—freshness, query latency, and cost—compares offline and real‑time architectures, introduces the concept of a streaming data warehouse, and details how Apache Flink Table Store aims to provide a unified, low‑cost solution.

FlinkReal-time AnalyticsStreaming
0 likes · 19 min read
Can a Streaming Data Warehouse Balance Freshness, Latency, and Cost?
IT Architects Alliance
IT Architects Alliance
Jun 7, 2022 · Databases

Introduction to Change Data Capture (CDC) Practices

This article introduces the concept and practice of Change Data Capture (CDC), explaining how it captures database changes to provide real‑time incremental data for analytics and reporting without impacting source performance, and outlines modern CDC methods, challenges, and production‑ready system requirements.

CDCData IntegrationDatabase Replication
0 likes · 8 min read
Introduction to Change Data Capture (CDC) Practices
Top Architect
Top Architect
Jun 7, 2022 · Databases

An Introduction to Change Data Capture (CDC) Practices and Modern Approaches

This article introduces the concept of Change Data Capture (CDC), explains why traditional batch reporting strains resources, describes how CDC captures only data changes to keep source databases performant, and outlines modern CDC architectures, production‑ready considerations, and best‑practice guidelines for building reliable data pipelines.

CDCData IntegrationReal-time Analytics
0 likes · 16 min read
An Introduction to Change Data Capture (CDC) Practices and Modern Approaches
StarRocks
StarRocks
Jun 2, 2022 · Big Data

Simplify Real‑Time Data Warehousing with Flink CDC and StarRocks

This article explores how combining Flink CDC with StarRocks can streamline real‑time data pipelines, reduce component complexity, support both full and incremental synchronization, and enable efficient OLAP queries and updates for fast, scalable analytics across diverse business scenarios.

Flink CDCOLAPReal-time Analytics
0 likes · 18 min read
Simplify Real‑Time Data Warehousing with Flink CDC and StarRocks
IT Architects Alliance
IT Architects Alliance
May 11, 2022 · Databases

How Change Data Capture Enables Real‑Time Analytics Without Overloading Your Database

The article explains the fundamentals of Change Data Capture (CDC), describing how capturing DML changes from relational databases like MySQL or PostgreSQL can provide incremental, near‑real‑time data for analytics and reporting while preserving source performance, and outlines modern CDC architectures, transaction‑log based extraction, and production‑ready design considerations.

CDCDatabase ReplicationReal-time Analytics
0 likes · 9 min read
How Change Data Capture Enables Real‑Time Analytics Without Overloading Your Database
DataFunTalk
DataFunTalk
May 3, 2022 · Big Data

Lianyou Technology Car IoT Platform: Architecture, Data Ingestion, Storage, and Application Overview

The article presents a comprehensive overview of Lianyou Technology's car IoT platform, detailing its four‑layer architecture, configurable data ingestion, hybrid cloud storage solutions, real‑time and offline data warehouses, and downstream data applications such as user operation, intelligent recommendation, and data security practices.

Real-time Analyticscar IoTcloud
0 likes · 12 min read
Lianyou Technology Car IoT Platform: Architecture, Data Ingestion, Storage, and Application Overview
DataFunSummit
DataFunSummit
Apr 9, 2022 · Big Data

Impala Deployment and Optimization: Practical Experience with Sensor Data Multi‑dimensional Analysis Platform

This article presents a comprehensive technical walkthrough of Sensor Data's multi‑dimensional analysis platform, covering product architecture, an Impala‑based real‑time query engine, query performance tuning, resource‑estimation strategies, and future plans, with concrete diagrams, test results, and community contributions.

ImpalaQuery OptimizationReal-time Analytics
0 likes · 19 min read
Impala Deployment and Optimization: Practical Experience with Sensor Data Multi‑dimensional Analysis Platform
StarRocks
StarRocks
Mar 29, 2022 · Big Data

How StarRocks Handles PB‑Scale Real‑Time Analytics with High Availability

This article explains how StarRocks manages petabyte‑level user behavior logs, ads and orders through a shared‑nothing architecture, tablet‑based data distribution, MPP compute, high‑availability metadata, real‑time mini‑batch ingestion, and online schema changes, enabling 24/7 analytical services for diverse internet companies.

MPPReal-time AnalyticsStarRocks
0 likes · 11 min read
How StarRocks Handles PB‑Scale Real‑Time Analytics with High Availability
Hacker Afternoon Tea
Hacker Afternoon Tea
Mar 22, 2022 · Databases

Quick Start Guide: Building a Multi‑Tenant Ad Analytics Database with Distributed PostgreSQL (Citus)

This tutorial walks through setting up Citus, creating and distributing PostgreSQL tables for a multi‑tenant ad‑analytics application, loading sample data, executing CRUD and analytical queries, and extending the approach to real‑time GitHub event analysis, demonstrating end‑to‑end database operations in a distributed environment.

CitusPostgreSQLReal-time Analytics
0 likes · 14 min read
Quick Start Guide: Building a Multi‑Tenant Ad Analytics Database with Distributed PostgreSQL (Citus)
Hacker Afternoon Tea
Hacker Afternoon Tea
Mar 21, 2022 · Databases

Choosing the Right Distribution Column in Citus: Best Practices for Efficient Queries

This article explains how to select an optimal distribution column for Citus tables by first identifying whether your workload is multitenant SaaS or real‑time analytics, then applying concrete guidelines such as using high‑cardinality tenant or entity IDs, avoiding timestamps, ensuring uniform distribution, and leveraging co‑location for better query performance.

CitusPostgreSQLReal-time Analytics
0 likes · 17 min read
Choosing the Right Distribution Column in Citus: Best Practices for Efficient Queries
Hacker Afternoon Tea
Hacker Afternoon Tea
Mar 16, 2022 · Databases

Building a Real-Time Dashboard with Distributed PostgreSQL (Citus) – Official Example

This tutorial shows how to use Citus, a distributed PostgreSQL extension, to ingest immutable HTTP event logs, shard them by site_id, create real‑time and pre‑aggregated tables, schedule roll‑up jobs, handle data expiration, estimate distinct counts with HyperLogLog, and store unstructured JSONB counters for a low‑latency analytics dashboard.

CitusHyperLogLogJSONB
0 likes · 16 min read
Building a Real-Time Dashboard with Distributed PostgreSQL (Citus) – Official Example
Hacker Afternoon Tea
Hacker Afternoon Tea
Feb 25, 2022 · Databases

How Citus Turns PostgreSQL into a Distributed Database

Citus is an open‑source PostgreSQL extension that adds sharding, distributed tables and parallel query execution, enabling horizontal and vertical scaling for multi‑tenant SaaS, real‑time analytics, and massive workloads, while outlining acquisition options, practical use cases, and scenarios where it is unsuitable.

AzureCitusPostgreSQL
0 likes · 7 min read
How Citus Turns PostgreSQL into a Distributed Database
21CTO
21CTO
Feb 24, 2022 · Big Data

5 Data Trends for 2022: Analytics Engineers, Lakehouse Wars, Real‑Time

In 2022 the modern data stack will be driven by the rise of analytics engineers, intensified competition between lakehouse and warehouse solutions, growing demand for real‑time analytics, the explosive growth of cloud marketplaces, and the emergence of unified data‑quality terminology, all reshaping data infrastructure and operational practices.

Data QualityLakehouseReal-time Analytics
0 likes · 17 min read
5 Data Trends for 2022: Analytics Engineers, Lakehouse Wars, Real‑Time
DataFunTalk
DataFunTalk
Feb 22, 2022 · Artificial Intelligence

Real‑Time Graph Neural Network for Payment Fraud Detection at eBay

This article describes how eBay applies graph neural networks to real‑time payment fraud detection, covering the anti‑fraud scenario, limitations of traditional GBDT pipelines, challenges of constructing and serving dynamic heterogeneous graphs, the end‑to‑end solution with directed slice graphs and a Lambda‑style architecture, and experimental results comparing GNN with LightGBM.

Real-time Analyticsfraud detectionmachine learning
0 likes · 15 min read
Real‑Time Graph Neural Network for Payment Fraud Detection at eBay
DataFunSummit
DataFunSummit
Feb 20, 2022 · Databases

Understanding TiDB Architecture and Real‑Time Application Scenarios

This article explains TiDB's HTAP architecture, covering industry challenges, the row‑store TiKV and column‑store TiFlash design, MPP integration in TiDB 5.0, and a range of real‑time use cases such as dashboards, reporting, and data‑warehouse pipelines.

HTAPMPPReal-time Analytics
0 likes · 16 min read
Understanding TiDB Architecture and Real‑Time Application Scenarios
ByteDance Data Platform
ByteDance Data Platform
Jan 17, 2022 · Big Data

How ByteHouse Scales Real‑Time Analytics on ClickHouse: Challenges & Solutions

This article details ByteHouse’s evolution from ClickHouse, presenting two real‑time analytics use cases, the technical selection process, performance bottlenecks such as write throughput and Kafka consumption, and the engineered solutions—including asynchronous indexing, multi‑threaded Kafka engines, and enhanced Buffer engines—that enable reliable, high‑throughput data processing at massive scale.

ByteHouseClickHouseKafka
0 likes · 11 min read
How ByteHouse Scales Real‑Time Analytics on ClickHouse: Challenges & Solutions
Shopee Tech Team
Shopee Tech Team
Jan 13, 2022 · Big Data

Engineering Practices and Performance Optimizations of Apache Druid for Real‑Time OLAP at Shopee

Shopee’s engineering team scaled a 100‑node Apache Druid cluster for real‑time OLAP by redesigning the Coordinator load‑balancing algorithm, adding incremental metadata pulls, introducing a segment‑merged result cache, and building exact‑count and flexible sliding‑window operators, while planning cloud‑native deployment.

Apache DruidBitmap IndexOLAP
0 likes · 17 min read
Engineering Practices and Performance Optimizations of Apache Druid for Real‑Time OLAP at Shopee
Programmer DD
Programmer DD
Jan 8, 2022 · Big Data

How Flink’s Streaming Warehouse Is Redefining Real‑Time Data Lakes

This interview explores Apache Flink’s evolution toward a Streaming Warehouse, detailing its stream‑batch integration, new CDC‑based data integration, the Dynamic Table storage architecture, and how these innovations aim to simplify and accelerate real‑time big‑data analytics.

Apache FlinkDynamic TableFlink CDC
0 likes · 17 min read
How Flink’s Streaming Warehouse Is Redefining Real‑Time Data Lakes
Volcano Engine Developer Services
Volcano Engine Developer Services
Jan 4, 2022 · Big Data

How ByteDance Scales EB-Level Data: Architecture, BP Model & Real-Time Insights

ByteDance’s data platform, built over seven years, now handles exabyte-scale data and over 100 million TPS, using a hybrid “middle‑platform + Business Partner” model, custom engines like ClickHouse/ByteHouse, agile governance, and a suite of products to support internal and external businesses, illustrating large-scale big-data engineering practices.

ByteDanceClickHouseReal-time Analytics
0 likes · 22 min read
How ByteDance Scales EB-Level Data: Architecture, BP Model & Real-Time Insights
Qunar Tech Salon
Qunar Tech Salon
Nov 29, 2021 · Big Data

Construction and Practice of Qunar's Business Intelligence Platform

This article details the evolution, architecture, and technical choices of Qunar's BI platform—from early one‑stop reporting to a modular, self‑service system supporting real‑time analytics, multi‑metric calculations, and unified data governance—highlighting challenges, solutions, and performance benchmarks across big‑data technologies.

BIClickHouseReal-time Analytics
0 likes · 23 min read
Construction and Practice of Qunar's Business Intelligence Platform
Tencent Cloud Developer
Tencent Cloud Developer
Nov 26, 2021 · Big Data

WeChat's ClickHouse Real‑Time Data Warehouse: Challenges, Co‑Construction, and Performance Gains

Facing Hadoop’s minute‑to‑hour query latency on petabyte‑scale data, WeChat partnered with Tencent Cloud to build a ClickHouse‑based real‑time warehouse, adding custom ingestion, query‑optimisation and management tools that deliver billion‑row throughput, sub‑5‑second queries and over ten‑fold performance gains across millions of daily queries.

ClickHouseReal-time AnalyticsWeChat
0 likes · 9 min read
WeChat's ClickHouse Real‑Time Data Warehouse: Challenges, Co‑Construction, and Performance Gains
HomeTech
HomeTech
Nov 24, 2021 · Databases

Real‑Time Data Analysis at AutoHome: Evaluation and Adoption of StarRocks

This article describes AutoHome's real‑time data analysis architecture, the challenges of existing OLAP solutions, the reasons for choosing StarRocks, detailed performance comparisons with Kylin, ClickHouse, Doris, Presto and Spark, and the practical integration of StarRocks with Flink, broker‑load scripts, and monitoring tools.

FlinkOLAPReal-time Analytics
0 likes · 9 min read
Real‑Time Data Analysis at AutoHome: Evaluation and Adoption of StarRocks
DataFunTalk
DataFunTalk
Nov 24, 2021 · Big Data

Tencent Game Big Data Analysis Engine: Architecture, Practices, and Future Plans

This article presents Tencent's game big‑data analysis platform, detailing its background, the architecture of the iData engine—including offline multi‑dimensional analysis (TGMars), online portrait analysis (TGFace), and real‑time multi‑dimensional analysis (TGDruid)—application scenarios, performance insights, and future ecosystem and open‑source plans.

Game AnalyticsOLAPReal-time Analytics
0 likes · 15 min read
Tencent Game Big Data Analysis Engine: Architecture, Practices, and Future Plans
DataFunTalk
DataFunTalk
Nov 23, 2021 · Big Data

ClickHouse Practice at Youzan: Architecture, Deployment, and Future Plans

This article details Youzan's adoption of ClickHouse for real-time analytics, covering its evolution from Presto, Druid, and Kylin, the system's architecture, deployment strategies, use cases, performance characteristics, limitations, and future roadmap, including integration with Apache Doris and emerging big‑data trends.

ClickHouseOLAPReal-time Analytics
0 likes · 23 min read
ClickHouse Practice at Youzan: Architecture, Deployment, and Future Plans
DataFunSummit
DataFunSummit
Nov 8, 2021 · Big Data

Building JD's OLAP System: From Data Ingestion to Management and Future Plans

This article explains how JD.com designs and evolves its OLAP platform, covering data sources, ingestion, storage, real‑time and offline processing, key challenges such as timeliness, high throughput, consistency, and the solutions implemented to support massive e‑commerce analytics.

JD.comOLAPReal-time Analytics
0 likes · 13 min read
Building JD's OLAP System: From Data Ingestion to Management and Future Plans
Big Data Technology & Architecture
Big Data Technology & Architecture
Nov 8, 2021 · Big Data

Why Choose Apache Iceberg? Tencent’s Optimizations and Real‑World Practices

This article examines the strengths and weaknesses of Apache Iceberg, explains why Tencent selected it over alternatives, details Tencent’s own enhancements and integration with Flink, Spark, and other engines, and shares multiple real‑world implementations for building enterprise‑grade real‑time data lakes.

Apache IcebergData LakeFlink
0 likes · 17 min read
Why Choose Apache Iceberg? Tencent’s Optimizations and Real‑World Practices
dbaplus Community
dbaplus Community
Oct 26, 2021 · Databases

Scaling JD.com Customer Service with Doris OLAP: Architecture & Caching

JD.com’s customer service team leverages the open‑source MPP database Doris to power real‑time and offline OLAP dashboards, detailing data ingestion pipelines, full‑link monitoring, dual‑stream high‑availability design, dynamic partition management, multi‑layer caching strategies, and performance optimizations applied during the 2020 11.11 shopping festival.

Data IngestionDorisOLAP
0 likes · 15 min read
Scaling JD.com Customer Service with Doris OLAP: Architecture & Caching
Big Data Technology & Architecture
Big Data Technology & Architecture
Oct 26, 2021 · Big Data

Practical Experience Building a Real‑Time Clickstream Data Warehouse with Flink and ClickHouse

This article shares practical insights on designing and operating a real‑time clickstream data warehouse using Flink for streaming processing and ClickHouse for near‑real‑time OLAP, covering dimensional modeling, layered architecture, Flink‑ClickHouse sink implementation, and data rebalancing strategies.

ClickHouseFlinkReal-time Analytics
0 likes · 10 min read
Practical Experience Building a Real‑Time Clickstream Data Warehouse with Flink and ClickHouse
NetEase Smart Enterprise Tech+
NetEase Smart Enterprise Tech+
Sep 26, 2021 · Databases

How ClickHouse Powers a Billion‑User Profiling Platform at Sub‑5‑Second Latency

This article shares NetEase’s experience building a user‑profile platform with ClickHouse, detailing the business background, challenges of massive data and complex queries, core table designs, data ingestion, bitmap techniques, performance gains, and future plans for scaling and optimization.

Bitmap IndexClickHouseReal-time Analytics
0 likes · 13 min read
How ClickHouse Powers a Billion‑User Profiling Platform at Sub‑5‑Second Latency
NetEase Game Operations Platform
NetEase Game Operations Platform
Sep 18, 2021 · Big Data

StreamflySQL: NetEase Games’ Journey from Template JAR to SQL Gateway for Flink SQL Platformization

This article details NetEase Games’ evolution of its Flink SQL platform, from the early StreamflySQL v1 template‑JAR approach to the v2 SQL‑Gateway architecture, discussing design decisions, challenges such as metadata persistence, multi‑tenant security, horizontal scaling, and job state management.

FlinkReal-time AnalyticsSQL
0 likes · 17 min read
StreamflySQL: NetEase Games’ Journey from Template JAR to SQL Gateway for Flink SQL Platformization
Volcano Engine Developer Services
Volcano Engine Developer Services
Sep 6, 2021 · Databases

How ByteDance Optimized ClickHouse for Real‑Time Recommendation and Ad Analytics

ByteDance’s ByteHouse, an enterprise‑grade ClickHouse, powers real‑time recommendation and ad‑delivery analytics at massive scale, detailing two case studies, technical selections, architectural designs, and performance optimizations such as asynchronous indexing, multi‑threaded Kafka consumption, and enhanced buffer engines to ensure data integrity.

ByteHouseClickHouseKafka
0 likes · 10 min read
How ByteDance Optimized ClickHouse for Real‑Time Recommendation and Ad Analytics
dbaplus Community
dbaplus Community
Aug 17, 2021 · Big Data

How JD Transformed Its Data Warehouse with Delta Lake for Real‑Time Analytics

This article examines JD's shift from a traditional Lambda‑based data warehouse to a Delta Lake‑powered real‑time data lake, detailing the challenges of legacy architectures, the evaluation of open‑source table formats, Delta Lake's core mechanisms, and the resulting simplified batch‑stream development workflow.

Batch-StreamData LakeDelta Lake
0 likes · 11 min read
How JD Transformed Its Data Warehouse with Delta Lake for Real‑Time Analytics
Big Data Technology & Architecture
Big Data Technology & Architecture
Aug 10, 2021 · Databases

Kudu Overview: Architecture, Features, and Use Cases

Kudu is an open‑source columnar storage engine from Cloudera that combines high‑throughput batch processing with low‑latency random reads, offering features such as C++/Java APIs, Raft‑based replication, flexible consistency, partitioning, and integration with Hadoop, Spark, Impala, and other ecosystem components.

HadoopKuduReal-time Analytics
0 likes · 64 min read
Kudu Overview: Architecture, Features, and Use Cases
DataFunTalk
DataFunTalk
Jul 27, 2021 · Big Data

Building a Real‑Time Data Warehouse with Apache Doris at Shuhai Supply Chain

This article describes how Shuhai Supply Chain upgraded its data warehouse from a complex, high‑cost 1.0 architecture to a streamlined, real‑time solution built around Apache Doris, detailing the motivations, design choices, zero‑code ingestion, metadata management, Flink connector, and the resulting performance gains.

Apache DorisFlinkReal-time Analytics
0 likes · 13 min read
Building a Real‑Time Data Warehouse with Apache Doris at Shuhai Supply Chain
dbaplus Community
dbaplus Community
Jul 11, 2021 · Big Data

Scaling Real‑Time & Offline Analytics with Druid: Architecture, Optimizations, and Lessons

This article explains how Beike adopted the Druid OLAP engine to handle massive real‑time and offline query workloads, detailing its four‑component architecture, key technologies such as deep storage and metadata storage, practical optimizations for data ingestion, query caching, dynamic throttling, timeout control, and a roadmap for future enhancements.

DruidOLAPPerformance Optimization
0 likes · 19 min read
Scaling Real‑Time & Offline Analytics with Druid: Architecture, Optimizations, and Lessons
Xianyu Technology
Xianyu Technology
Jun 8, 2021 · Big Data

Longgong Data Analysis Platform: Architecture and Solutions for Large‑Scale Structured Data

The Longgong Data Analysis Platform enables Idle Fish to capture, store, and analyze billions of structured product attributes in real time across more than 8,000 categories, using TableStore, MySQL, ODPS, and a distributed scheduler to achieve over 50% query speedup, 80% category coverage, and rapid support for search and recommendation teams.

AlibabaData PipelineDistributed Processing
0 likes · 9 min read
Longgong Data Analysis Platform: Architecture and Solutions for Large‑Scale Structured Data
IT Architects Alliance
IT Architects Alliance
May 25, 2021 · Big Data

How Modern Data Middle Platforms Power Real‑Time and Offline Analytics

This article provides a comprehensive technical overview of data middle platforms, covering data aggregation, offline and real‑time development, smart operations, data asset management, governance, service layers, platform implementations, warehouse layering, and key differences between offline and real‑time data warehouses.

ETLReal-time Analyticsbig data
0 likes · 26 min read
How Modern Data Middle Platforms Power Real‑Time and Offline Analytics
Architects Research Society
Architects Research Society
May 24, 2021 · Big Data

Understanding the Differences Between Event Stream Processing (ESP) and Complex Event Processing (CEP)

This article explains the origins, concepts, and use‑cases of Event Stream Processing (ESP) and Complex Event Processing (CEP), contrasting their handling of ordered event streams versus unordered event clouds, and discusses how both technologies have evolved and are applied in modern real‑time analytics.

CEPData StreamsESP
0 likes · 17 min read
Understanding the Differences Between Event Stream Processing (ESP) and Complex Event Processing (CEP)