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Data Lake

388 articles · Page 2 of 4
Volcano Engine Developer Services
Volcano Engine Developer Services
Mar 5, 2025 · Artificial Intelligence

How DeepSeek Smallpond Powers AI Data Processing with Ray and DuckDB

This article introduces DeepSeek Smallpond, a lightweight yet high‑performance AI data‑processing engine built on Ray and DuckDB, explains its dual Dataframe and LogicalPlan APIs, showcases integration with Volcano Engine's AI Data Lake LAS, and provides practical code examples for distributed processing, multimodal storage, and RAG pipelines.

AI data processingData LakeDistributed Computing
0 likes · 18 min read
How DeepSeek Smallpond Powers AI Data Processing with Ray and DuckDB
DataFunSummit
DataFunSummit
Feb 23, 2025 · Big Data

Douyin Group’s ByteLake Data Lake Table Optimization and Management Practices

This article presents Douyin Group’s ByteLake, a heavily customized Apache Hudi‑based data lake table framework, detailing its core concepts, metadata services, write and read optimizations, operational challenges, a fully managed table management service, and its integration with the Amoro open‑source platform.

AmoroApache HudiByteLake
0 likes · 11 min read
Douyin Group’s ByteLake Data Lake Table Optimization and Management Practices
JD Tech
JD Tech
Feb 11, 2025 · Big Data

Cold‑Hot Data Tiering and Performance Optimization in Apache Doris for JD Advertising

This article presents JD Advertising's engineering experience with Apache Doris, describing the evolution from a data‑lake cold‑data solution to a native cold‑hot tiering approach, detailing performance regressions after upgrading to Doris 2.0, and outlining a series of optimizations for query speed, CPU and memory usage, schema‑change efficiency, and automated data migration and restoration.

Apache DorisData Lakebig data
0 likes · 17 min read
Cold‑Hot Data Tiering and Performance Optimization in Apache Doris for JD Advertising
Alibaba Cloud Big Data AI Platform
Alibaba Cloud Big Data AI Platform
Jan 23, 2025 · Big Data

How Alibaba Cloud DataWorks Leverages Flink CDC for Scalable Data Lake Integration

Alibaba Cloud DataWorks’ Data Integration platform, built on Flink CDC, offers a comprehensive, serverless solution for real‑time and batch data lake ingestion, detailing its architecture, elastic scaling, productized use cases, and future roadmap, including AI‑driven diagnostics and expanded source support.

Data IntegrationData LakeElastic Scaling
0 likes · 12 min read
How Alibaba Cloud DataWorks Leverages Flink CDC for Scalable Data Lake Integration
JD Cloud Developers
JD Cloud Developers
Jan 16, 2025 · Artificial Intelligence

JD Retail’s 2024 Tech Innovations: AI, Supply Chain, and Immersive Shopping

In 2024, JD Retail Technology rolled out a series of breakthroughs—including a major JD APP redesign, data‑driven inventory algorithms, an AIGC content platform, a low‑code national‑subsidy system, a high‑performance data lake, cross‑platform Taro on Harmony, AI‑powered merchant assistants, and immersive XR shopping—showcasing how AI and advanced engineering drive faster fulfillment, richer user experiences, and scalable innovation.

AIAIGCCross-platform Development
0 likes · 18 min read
JD Retail’s 2024 Tech Innovations: AI, Supply Chain, and Immersive Shopping
JD Retail Technology
JD Retail Technology
Jan 15, 2025 · Industry Insights

JD Retail’s 2024 Tech Innovations: AI, Supply‑Chain Algorithms, and Development

In 2024 JD Retail Technology delivered a series of breakthroughs—including a major JD APP redesign, a data‑driven inventory selection and allocation algorithm that cut stockouts, an AIGC platform for marketing content, a low‑code national‑subsidy system, a large‑scale Apache Hudi data lake, the Taro‑on‑Harmony cross‑platform framework, immersive XR shopping experiences, and a domestic‑chip AI engine—showcasing how advanced AI, cloud, and operations engineering are reshaping e‑commerce.

AIAIGCCross-platform Development
0 likes · 17 min read
JD Retail’s 2024 Tech Innovations: AI, Supply‑Chain Algorithms, and Development
Alibaba Cloud Big Data AI Platform
Alibaba Cloud Big Data AI Platform
Jan 14, 2025 · Big Data

How Fluss Unifies Lake and Stream for Real‑Time Analytics: Architecture, Benefits, and Future Roadmap

This article summarizes a talk by Alibaba Cloud senior engineer and Flink Committer Luo Yuxia on the challenges of separating lake and stream storage, introduces the Fluss lake‑stream unified architecture, explains its technical benefits such as second‑level data freshness, unified metadata, efficient changelog generation, and outlines future plans for broader ecosystem integration.

Data LakeFlinkFluss
0 likes · 13 min read
How Fluss Unifies Lake and Stream for Real‑Time Analytics: Architecture, Benefits, and Future Roadmap
Alibaba Cloud Developer
Alibaba Cloud Developer
Dec 25, 2024 · Big Data

Build a Low‑Cost, High‑Performance Game Player Profiling Platform with Alibaba Cloud EMR StarRocks

This tutorial walks you through using Alibaba Cloud EMR Serverless StarRocks and Apache Paimon to create a cost‑effective, high‑performance game player profiling and behavior analysis platform, covering data import, materialized view creation, DWD/ADS layer construction, and lakehouse integration.

Alibaba CloudData LakeGame Analytics
0 likes · 12 min read
Build a Low‑Cost, High‑Performance Game Player Profiling Platform with Alibaba Cloud EMR StarRocks
Tencent Advertising Technology
Tencent Advertising Technology
Dec 6, 2024 · Big Data

Building a High‑Performance Advertising Feature Data Lake with Apache Iceberg at Tencent

Tencent's advertising team replaced a traditional HDFS‑Hive warehouse with an Apache Iceberg‑based data lake, adding primary‑key tables, multi‑stream merging, adaptive compaction, and Spark SPJ optimizations to achieve minute‑level feature update latency, 10× back‑fill speed, and up to 60% storage savings.

CDCData LakeStreaming
0 likes · 25 min read
Building a High‑Performance Advertising Feature Data Lake with Apache Iceberg at Tencent
Tongcheng Travel Technology Center
Tongcheng Travel Technology Center
Nov 27, 2024 · Big Data

Highlights of Tongcheng Travel’s 8th Big Data Technology Salon

The 8th Tongcheng Travel Big Data Technology Salon in Suzhou featured four expert talks covering Tencent Cloud’s Meson Spark engine, near‑line computing for travel itineraries, a Flink‑based real‑time risk control system, and Apache Paimon’s latest lake‑warehouse innovations, followed by a data‑driven business perspective session.

Apache PaimonData LakeFlink
0 likes · 7 min read
Highlights of Tongcheng Travel’s 8th Big Data Technology Salon
Bilibili Tech
Bilibili Tech
Nov 26, 2024 · Big Data

Bilibili’s Iceberg‑Based Streaming‑Batch Integration: Architecture, Optimizations, and Practices

Bilibili migrated its massive user‑behavior, commercial AI training, and database synchronization pipelines from Hive and Kafka to an Iceberg‑based streaming‑batch architecture, using Flink and the Magnus optimizer to achieve minute‑level freshness, reduce CPU and memory usage by about 20‑22 %, save roughly 3.55 M CNY annually, and dramatically improve query latency and join performance.

Data IntegrationData LakeFlink
0 likes · 20 min read
Bilibili’s Iceberg‑Based Streaming‑Batch Integration: Architecture, Optimizations, and Practices
DataFunSummit
DataFunSummit
Nov 23, 2024 · Big Data

Bilibili's Iceberg‑Based Streaming‑Batch Integration: Architecture, Optimizations, and Practice

This article presents Bilibili's end‑to‑end exploration of a streaming‑batch unified data pipeline built on Apache Iceberg, detailing the original and iterated architectures for massive user behavior transmission, online AI training, DB synchronization, and dimension‑join, along with performance gains, cost savings, and future plans.

Batch ProcessingData LakeFlink
0 likes · 20 min read
Bilibili's Iceberg‑Based Streaming‑Batch Integration: Architecture, Optimizations, and Practice
iQIYI Technical Product Team
iQIYI Technical Product Team
Nov 21, 2024 · Big Data

Alluxio Integration and Optimization for Multi‑AZ Big Data Analytics at iQIYI

iQIYI integrates Alluxio with its QBFS multi‑AZ unified scheduling system, automatically caching hot tables, applying table‑level policies, page‑level storage and AZ‑aware worker selection, which together cut cross‑zone traffic, halve query latency, achieve up to 20× I/O speedup and a three‑fold overall performance boost.

AlluxioData LakeMulti‑AZ
0 likes · 23 min read
Alluxio Integration and Optimization for Multi‑AZ Big Data Analytics at iQIYI
DataFunSummit
DataFunSummit
Nov 20, 2024 · Artificial Intelligence

How Data Lakes Empower AI: Expert Insights on Feature Management, Columnar Storage, and Vector Formats

In a panel discussion, experts explain how data‑lake‑warehouse integration, columnar formats like Apache Iceberg, and emerging variant types enable efficient feature engineering, support large‑language‑model workloads, and provide flexible vector storage, thereby driving the evolution of AI from traditional ML to the GenAI era.

Apache IcebergArtificial IntelligenceData Lake
0 likes · 6 min read
How Data Lakes Empower AI: Expert Insights on Feature Management, Columnar Storage, and Vector Formats
Baidu Geek Talk
Baidu Geek Talk
Nov 13, 2024 · Industry Insights

Why Cloud‑Native Data Lakes Are the New Standard for Storage Acceleration

This article analyzes the evolution of data‑lake storage acceleration, compares traditional parallel file systems, object‑storage‑based solutions and modern cache‑enabled architectures, and explains how cloud‑native data lakes address scalability, cost, and performance challenges for AI and big‑data workloads.

AIData LakeObject Storage
0 likes · 24 min read
Why Cloud‑Native Data Lakes Are the New Standard for Storage Acceleration
DataFunSummit
DataFunSummit
Nov 8, 2024 · Big Data

Roundtable Discussion on Data Lake Technology Maturity and Governance Practices

Experts from Kuaishou, former Tencent, Ping An Insurance and others discuss data lake maturity, column‑level governance, resource management of unstructured data, and automated optimization techniques such as Iceberg small‑file merging, highlighting how these advances improve data quality and business decision‑making.

Column-level GovernanceData LakeHudi
0 likes · 6 min read
Roundtable Discussion on Data Lake Technology Maturity and Governance Practices
DataFunTalk
DataFunTalk
Nov 6, 2024 · Big Data

How Data Lakes Empower AI: Insights from Industry Experts

In a panel discussion, experts from Kuaishou, Ping An, and Datastrato explain how data lake architectures, columnar storage formats like Apache Iceberg, and vector‑enabled lake formats are enhancing feature management, supporting generative AI workloads, and accelerating machine‑learning pipelines.

AIApache IcebergData Lake
0 likes · 6 min read
How Data Lakes Empower AI: Insights from Industry Experts
Baidu Tech Salon
Baidu Tech Salon
Nov 5, 2024 · Big Data

Accelerating Data Lake Storage for Big Data and AI: Baidu's Solutions

Baidu’s Data Lake Storage Acceleration 2.0 replaces traditional HDFS with a scalable object‑storage foundation, introducing an adaptive hierarchical namespace, high‑throughput streaming engine, RapidFS caching, and fully compatible BOS‑HDFS APIs, thereby delivering up to 70 % higher throughput, lower costs, and seamless migration for big‑data and AI workloads.

AIBOS-HDFSData Lake
0 likes · 11 min read
Accelerating Data Lake Storage for Big Data and AI: Baidu's Solutions
Baidu Geek Talk
Baidu Geek Talk
Nov 4, 2024 · Big Data

Why Object Storage Is Replacing HDFS for Modern Data Lakes: Baidu’s 2.0 Acceleration

Data lakes have evolved from HDFS to object storage, addressing resource inefficiency, scalability limits, and operational burdens; Baidu’s Data Lake Storage Acceleration 2.0 introduces hierarchical Namespace 2.0, a streaming storage engine, RapidFS caching, and a fully HDFS‑compatible BOS‑HDFS layer to boost performance and support massive AI workloads.

AIBaiduData Lake
0 likes · 12 min read
Why Object Storage Is Replacing HDFS for Modern Data Lakes: Baidu’s 2.0 Acceleration
Bilibili Tech
Bilibili Tech
Nov 1, 2024 · Big Data

Magnus: Intelligent Data Optimization Service for Iceberg Tables in Bilibili's Lakehouse Platform

Magnus is Bilibili’s self‑developed intelligent service that continuously optimizes Iceberg tables by scheduling snapshot expiration, orphan‑file cleanup, manifest rewriting, and multi‑dimensional data optimizations—including small‑file merging, sorting, distribution, and index creation—while automatically recommending configurations from real‑time query logs, delivering over 99.9% task success and up to 30% scan‑data reduction.

Data LakeIntelligent RecommendationOptimization
0 likes · 15 min read
Magnus: Intelligent Data Optimization Service for Iceberg Tables in Bilibili's Lakehouse Platform
Baidu Intelligent Cloud Tech Hub
Baidu Intelligent Cloud Tech Hub
Oct 28, 2024 · Cloud Native

How Baidu Smart Cloud Reinvents Cloud‑Native Infrastructure for the AI‑Native Era

The talk outlines Baidu Smart Cloud's comprehensive cloud‑native redesign—including ultra‑elastic compute, AI‑focused storage, high‑performance networking, AI‑driven operations, and edge‑distributed services—illustrated with automotive and fintech case studies that demonstrate how enterprises can accelerate digital transformation in the AI‑native age.

AI infrastructureData LakeMLOps
0 likes · 12 min read
How Baidu Smart Cloud Reinvents Cloud‑Native Infrastructure for the AI‑Native Era
Shopee Tech Team
Shopee Tech Team
Oct 25, 2024 · Big Data

StarRocks at Shopee: Practical Use Cases and Performance Analysis

Shopee’s deployment of StarRocks across DataService, DataGo, and DataStudio demonstrates that its vectorized engine, cost‑based optimizer, and materialized‑view caching can query Hive, Iceberg, Delta Lake and Hudi up to 20,000× faster than Presto, cutting CPU usage and delivering consistently lower latency for complex analytics.

Data LakeHiveMPP
0 likes · 11 min read
StarRocks at Shopee: Practical Use Cases and Performance Analysis
DataFunTalk
DataFunTalk
Oct 3, 2024 · Big Data

Data Lake Technology Maturity Curve: Architecture, Design Principles, Core Functions, and Open‑Source Solutions

Amid growing data demands, this article explains the data lake technology maturity curve, detailing lake‑warehouse architectural patterns, design principles, core functionalities, and the four leading open‑source solutions (Hudi, Iceberg, Delta Lake, Paimon) to guide enterprises in building flexible, scalable, and governed data platforms.

Data LakeDelta LakeHudi
0 likes · 10 min read
Data Lake Technology Maturity Curve: Architecture, Design Principles, Core Functions, and Open‑Source Solutions
Alibaba Cloud Big Data AI Platform
Alibaba Cloud Big Data AI Platform
Sep 27, 2024 · Big Data

How Alibaba Cloud’s New Vectorized Engines Are Revolutionizing Real‑Time Big Data Processing

At the 2024 Cloud Xi Conference, Alibaba Cloud unveiled a suite of vectorized big‑data solutions—including the Flash engine for Flink, EMR Serverless Spark with a 300% speed boost, upgraded lakehouse architecture, and real‑world case studies—showcasing massive performance gains, cost reductions, and broader serverless adoption.

Data LakeFlinkServerless
0 likes · 8 min read
How Alibaba Cloud’s New Vectorized Engines Are Revolutionizing Real‑Time Big Data Processing
DataFunSummit
DataFunSummit
Sep 26, 2024 · Big Data

Apache Hudi Incremental Processing and Change Data Capture (CDC): Overview, Incremental Query, and CDC

This article explains Apache Hudi's incremental processing capabilities, covering an overview of the medallion architecture, detailed configuration for incremental queries, the introduction of Change Data Capture (CDC) with required table properties, and a review of how these features enable richer data insights in modern data lake environments.

Apache HudiData LakeIncremental Processing
0 likes · 9 min read
Apache Hudi Incremental Processing and Change Data Capture (CDC): Overview, Incremental Query, and CDC
DataFunTalk
DataFunTalk
Sep 24, 2024 · Big Data

Data Lake Technology Maturity Curve: Architecture Modes, Design Principles, Core Functions, and Applications

This article explains the rapid growth of data-driven businesses, the challenges of traditional data warehouses, and how modern data lake technologies such as Delta Lake, Hudi, Iceberg, and Paimon form a maturity curve that guides enterprises in architecture choices, design principles, core capabilities, and practical applications.

Data LakeDelta LakeHudi
0 likes · 12 min read
Data Lake Technology Maturity Curve: Architecture Modes, Design Principles, Core Functions, and Applications
DataFunSummit
DataFunSummit
Sep 14, 2024 · Big Data

Apache Hudi Concurrency Control: Overview, MVCC, and OCC

This article provides a comprehensive overview of concurrency control in Apache Hudi, explaining ACID properties, the role of MVCC and OCC, and how Hudi coordinates multiple writers and table services to achieve serializable scheduling while maintaining high performance.

Apache HudiData LakeMVCC
0 likes · 8 min read
Apache Hudi Concurrency Control: Overview, MVCC, and OCC
DataFunTalk
DataFunTalk
Sep 4, 2024 · Artificial Intelligence

Data+AI Data Lake Technologies: Challenges, Apache Iceberg Overview, and Vector Table Implementations with PyIceberg

This article explores the evolution of data lakes for AI, discusses the challenges of AI-era data management, introduces Apache Iceberg and its architecture, demonstrates PyIceberg-based AI training and inference pipelines, and presents vector table designs with LSH indexing and performance optimizations.

AIApache IcebergData Lake
0 likes · 22 min read
Data+AI Data Lake Technologies: Challenges, Apache Iceberg Overview, and Vector Table Implementations with PyIceberg

How Hudi MetaServer Transforms Metadata Management and Performance in Data Lakes

This article examines the challenges of Hudi metadata stored on HDFS, introduces the independently developed Hudi MetaServer for centralized metadata, visual management, unified permission control, TTL, expression payloads, and multi‑active scaling, and outlines future enhancements such as LLS, multi‑table fusion, and JDBC support.

Data LakeHudiMetaServer
0 likes · 11 min read
How Hudi MetaServer Transforms Metadata Management and Performance in Data Lakes
DataFunSummit
DataFunSummit
Aug 4, 2024 · Big Data

Apache Hudi from Zero to One: Comprehensive Guide to Write Indexing (Part 4)

This article explains Apache Hudi’s write‑side indexing, detailing the indexing API, various index types—including simple, Bloom, bucket, HBase, and record‑level indexes—and their mechanisms, helping readers understand how Hudi validates record existence and optimizes updates and deletions.

Apache HudiData LakeIndexing
0 likes · 9 min read
Apache Hudi from Zero to One: Comprehensive Guide to Write Indexing (Part 4)
DataFunSummit
DataFunSummit
Jul 12, 2024 · Big Data

Data Lake Development Trends, Architecture, Integration, Lakehouse Core Capabilities, and Open Design

This article examines the current evolution of data lakes, detailing their overall architecture, batch and real‑time integration methods, Lakehouse core functionalities such as enhanced DML, schema evolution, ACID support, and open‑design principles that enable multi‑cloud deployment and seamless interaction with diverse compute engines.

Batch ProcessingBig Data ArchitectureData Lake
0 likes · 12 min read
Data Lake Development Trends, Architecture, Integration, Lakehouse Core Capabilities, and Open Design
Sohu Tech Products
Sohu Tech Products
Jul 10, 2024 · Industry Insights

How StarRocks and Apache Paimon Transform Data Lake Analytics and Migration

This article provides a practical deep‑dive into StarRocks and Apache Paimon, covering data‑lake fundamentals, the technical advantages of both platforms, performance gains over traditional engines, step‑by‑step migration strategies, deployment options on Alibaba Cloud EMR, and future roadmap plans.

Apache PaimonData LakeQuery Optimization
0 likes · 15 min read
How StarRocks and Apache Paimon Transform Data Lake Analytics and Migration
DataFunTalk
DataFunTalk
Jul 6, 2024 · Big Data

StarRocks and Paimon Data Lake Capabilities, Migration Solutions, and Future Roadmap

This article presents a practical overview of StarRocks and Apache Paimon data‑lake capabilities, explains their performance advantages, details migration strategies from Trino/Presto and other engines, describes cluster‑to‑cluster migration, and outlines future roadmap for integration and optimization.

Cloud ComputingData LakePaimon
0 likes · 13 min read
StarRocks and Paimon Data Lake Capabilities, Migration Solutions, and Future Roadmap
DataFunSummit
DataFunSummit
Jul 6, 2024 · Artificial Intelligence

Highlights of DataFunCon 2024 Beijing: Big Data, AI, and Large‑Model Trends

The two‑day DataFunCon 2024 Beijing conference gathered hundreds of big‑data and AI experts to discuss the evolution from data lakes to lake‑warehouses, large‑model development, practical applications, and future strategies for enterprises, while showcasing partner exhibitions and a vibrant community spirit.

Artificial IntelligenceChinaData Lake
0 likes · 9 min read
Highlights of DataFunCon 2024 Beijing: Big Data, AI, and Large‑Model Trends
DataFunSummit
DataFunSummit
Jun 20, 2024 · Big Data

Data+AI Data Lake Technologies: Apache Iceberg, PyIceberg, and Vector Table Solutions

This article presents a comprehensive overview of modern Data+AI data lake challenges and solutions, covering the evolution of data lakes, an introduction to Apache Iceberg, practical use of PyIceberg for AI training and inference pipelines, and advanced vector table and indexing techniques for efficient similarity search.

Apache IcebergData LakePyIceberg
0 likes · 22 min read
Data+AI Data Lake Technologies: Apache Iceberg, PyIceberg, and Vector Table Solutions
DataFunTalk
DataFunTalk
Jun 18, 2024 · Big Data

Real-time Data Warehouse Evolution with Data Lake: Architecture, Challenges, and Solutions

This article presents a comprehensive overview of the evolution from traditional Lambda‑based real‑time data warehouse solutions to a data‑lake‑integrated architecture, detailing the shortcomings of legacy designs, the iterative improvements made at JD Technology, and the technical and operational challenges encountered during implementation.

Data LakeLambda ArchitectureReal-time Data Warehouse
0 likes · 24 min read
Real-time Data Warehouse Evolution with Data Lake: Architecture, Challenges, and Solutions
21CTO
21CTO
Jun 7, 2024 · Artificial Intelligence

10 Essential Tools for Building a Modern AI Data Lake Architecture

This article outlines ten critical components of a modern data lake reference architecture for AI/ML, detailing each function, the supporting vendor tools and open‑source libraries, and how they enable scalable storage, MLOps, distributed training, model hubs, vector search, and data visualization.

AIData LakeDistributed Training
0 likes · 14 min read
10 Essential Tools for Building a Modern AI Data Lake Architecture
StarRocks
StarRocks
May 22, 2024 · Big Data

Unlocking Data Lake Power: Iceberg Architecture & StarRocks Acceleration

Apache Iceberg offers a modern, ACID‑compliant table format for data lakes with features like hidden partitions and schema evolution, while StarRocks provides high‑performance query acceleration, metadata caching, and distributed planning to address Iceberg’s latency challenges, enabling seamless lake‑warehouse integration and real‑time analytics.

Apache IcebergData LakeMetadata Caching
0 likes · 19 min read
Unlocking Data Lake Power: Iceberg Architecture & StarRocks Acceleration
DataFunSummit
DataFunSummit
May 17, 2024 · Big Data

Comprehensive Hudi Real-Time Data Lake Ingestion Solutions

This article presents a complete guide to Hudi-based real-time data lake ingestion, covering overall data integration architecture, batch and streaming ingestion strategies, advanced table design, and practical recommendations for handling challenges such as deduplication, latency, partitioning, and performance optimization.

Batch ProcessingData LakeHudi
0 likes · 12 min read
Comprehensive Hudi Real-Time Data Lake Ingestion Solutions
DataFunTalk
DataFunTalk
May 16, 2024 · Big Data

Streaming Data Lake Warehouse Solution Based on USDP with Flink and Paimon

This article presents UCloud's USDP‑based streaming data lake warehouse solution that leverages Flink for real‑time processing and Paimon for lake storage, detailing its architecture, advantages, practical scenarios, and providing complete SQL and Flink CDC code snippets for end‑to‑end implementation.

CDCData LakeFlink
0 likes · 27 min read
Streaming Data Lake Warehouse Solution Based on USDP with Flink and Paimon
iQIYI Technical Product Team
iQIYI Technical Product Team
Apr 26, 2024 · Big Data

iQIYI Real-time Lakehouse: Stream‑Batch Unified Architecture

iQIYI replaced its costly Lambda architecture with a unified Iceberg‑based lakehouse that combines Flink streaming and batch processing, cutting data latency from hours to minutes, supporting thousands of tables via a multi‑table sink, guaranteeing completeness, and saving millions of RMB in operational costs.

Data LakeFlinkStream-Batch Integration
0 likes · 18 min read
iQIYI Real-time Lakehouse: Stream‑Batch Unified Architecture
StarRocks
StarRocks
Apr 25, 2024 · Big Data

How StarRocks Beats Trino: 4.3× Faster Queries on Apache Paimon Lakehouse

This article explains how to build a high‑performance data‑lake analytics stack by combining StarRocks with Apache Paimon, covering direct queries, Data Cache acceleration, and asynchronous materialized views, and presents benchmark results that show StarRocks achieving up to 4.3× faster query speeds than Trino and significant latency reductions with caching and materialized views.

Apache PaimonData CacheData Lake
0 likes · 12 min read
How StarRocks Beats Trino: 4.3× Faster Queries on Apache Paimon Lakehouse
DataFunSummit
DataFunSummit
Mar 30, 2024 · Big Data

Alluxio in Data & AI Lakehouse: Architecture, Performance Optimizations, and Cloud Practices at OPPO

OPPO's data architects combined their self‑developed Shuttle service with Alluxio to double performance, halve system pressure, and double throughput, while building a unified Data & AI lakehouse that integrates structured and unstructured data, metadata management, real‑time ingestion, and cloud cost reductions.

AIAlluxioCloud Computing
0 likes · 11 min read
Alluxio in Data & AI Lakehouse: Architecture, Performance Optimizations, and Cloud Practices at OPPO
iQIYI Technical Product Team
iQIYI Technical Product Team
Mar 8, 2024 · Big Data

Smooth Migration from Hive to Iceberg Data Lake at iQIYI: Architecture, Techniques, and Performance Evaluation

iQIYI migrated hundreds of petabytes of Hive tables to Apache Iceberg using dual‑write, in‑place, and CTAS strategies, combined with partition pruning, Bloom filters, and Trino/Alluxio optimizations, achieving up to 40% lower query latency, simplified pipelines, and faster, cost‑effective data lake operations.

Data LakeHivePerformance Optimization
0 likes · 20 min read
Smooth Migration from Hive to Iceberg Data Lake at iQIYI: Architecture, Techniques, and Performance Evaluation
Xiaohongshu Tech REDtech
Xiaohongshu Tech REDtech
Mar 4, 2024 · Big Data

Integrating Data Lake Technologies with Data Warehouse Architecture at Xiaohongshu: Practices and Performance Optimizations

Xiaohongshu’s data‑warehouse team integrated Apache Iceberg‑based data‑lake techniques into its existing warehouse, replacing the legacy Hive/Spark stack with global sorting, Z‑order, and upsert‑enabled tables, which cut query latency by up to 90 %, boosted data freshness by 50 %, slashed storage costs by 83 % and saved tens of thousands of GB‑hours of compute daily.

Apache IcebergData LakeFlink
0 likes · 19 min read
Integrating Data Lake Technologies with Data Warehouse Architecture at Xiaohongshu: Practices and Performance Optimizations
DataFunSummit
DataFunSummit
Feb 26, 2024 · Big Data

Building a New Lakehouse Analytics Paradigm with StarRocks and Paimon

This article introduces a new lakehouse analytics paradigm by combining StarRocks and Paimon, covering the evolution of data lake technologies, key integration scenarios, core technical mechanisms such as JNI connectors, materialized views, and future roadmap for enhanced lakehouse capabilities.

AnalyticsData LakeLakehouse
0 likes · 16 min read
Building a New Lakehouse Analytics Paradigm with StarRocks and Paimon
StarRocks
StarRocks
Jan 10, 2024 · Big Data

How Tencent Built the ABetterChoice SaaS A/B Testing Platform for Global Games

In 2022 Tencent's A/B Test team created the overseas SaaS product ABetterChoice, abstracting internal experiment capabilities, adapting to multi‑cloud compliance, and unifying computation with StarRocks, enabling game titles like Honor of Kings, PUBG Mobile, and Ubisoft to run scalable, compliant A/B experiments worldwide.

A/B testingData LakeMulti-Cloud
0 likes · 14 min read
How Tencent Built the ABetterChoice SaaS A/B Testing Platform for Global Games
Architects Research Society
Architects Research Society
Jan 2, 2024 · Big Data

Understanding Data Lakes: Concepts, Benefits, Challenges, and Comparison with Data Warehouses

This article explains what a data lake is, its origins, key characteristics such as collecting all data, enabling diverse user access, and flexible processing, compares it with traditional data warehouses, discusses cost advantages, potential pitfalls like data swamps, and outlines best‑practice considerations for enterprise adoption.

AnalyticsData LakeHadoop
0 likes · 10 min read
Understanding Data Lakes: Concepts, Benefits, Challenges, and Comparison with Data Warehouses
Big Data Technology & Architecture
Big Data Technology & Architecture
Dec 8, 2023 · Big Data

Comprehensive Guide to Apache Paimon and Advanced Flink Integration

This article provides an in‑depth overview of Apache Paimon as a streaming lakehouse, explains its core features, file layout, consistency guarantees, and offers detailed guidance on integrating and tuning Paimon with Apache Flink for both write and read performance, multi‑writer concurrency, table management, and bucket rescaling.

Apache PaimonData LakeFlink
0 likes · 23 min read
Comprehensive Guide to Apache Paimon and Advanced Flink Integration
DataFunTalk
DataFunTalk
Nov 30, 2023 · Big Data

Big Data Cloud‑Native Trends and Challenges Highlighted at the 2023 Yunqi Conference

The 2023 Yunqi Conference in Hangzhou showcased the latest advances in cloud computing and big‑data technologies, examined the evolution from big‑data 1.0 to 3.0, discussed the key difficulties of making big data cloud‑native, and presented a practical case study of MiHoYo’s cloud‑native transformation.

Alibaba CloudData LakeKubernetes
0 likes · 12 min read
Big Data Cloud‑Native Trends and Challenges Highlighted at the 2023 Yunqi Conference
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
Big Data Technology & Architecture
Big Data Technology & Architecture
Nov 28, 2023 · Big Data

Apache Paimon for CDC: Low‑Cost, Low‑Latency Data Lake Ingestion and Performance Comparison with Hive and Hudi

This article explains how Apache Paimon simplifies CDC data lake ingestion with one‑click, low‑cost, low‑latency pipelines, details its architecture and tag‑based Hive compatibility, provides best‑practice configurations, and presents benchmark results showing Paimon outperforming Hive and Hudi in both write and query performance.

Apache PaimonCDCData Lake
0 likes · 14 min read
Apache Paimon for CDC: Low‑Cost, Low‑Latency Data Lake Ingestion and Performance Comparison with Hive and Hudi
Architects Research Society
Architects Research Society
Nov 26, 2023 · Big Data

Data Lake vs Data Warehouse: Key Differences and How to Choose

Data lakes and data warehouses serve different purposes in big‑data architectures; this article explains their definitions, core attributes, five major distinctions—including data retention, type support, user coverage, adaptability, and insight speed—and offers guidance on selecting or combining the two approaches.

AnalyticsData LakeHadoop
0 likes · 12 min read
Data Lake vs Data Warehouse: Key Differences and How to Choose
StarRocks
StarRocks
Nov 22, 2023 · Big Data

How StarRocks’ Compute‑Storage Separation Cut Costs 46% and Boosted Performance

This article details a Chinese tech company's migration of its internal big‑data analytics platform to StarRocks’ compute‑storage separation architecture, describing the original multi‑component setup, the pain points encountered, the evaluation methodology, performance and cost benchmarks, operational optimizations, migration steps, and future roadmap.

Compute-Storage SeparationData LakeKubernetes
0 likes · 17 min read
How StarRocks’ Compute‑Storage Separation Cut Costs 46% and Boosted Performance
dbaplus Community
dbaplus Community
Nov 8, 2023 · Big Data

Choosing Between Data Warehouse, Data Lake, and Lakehouse: When to Use Each

This article compares traditional data warehouses, modern data lakes, and emerging lakehouse architectures, explaining their design patterns, advantages, disadvantages, and suitable use cases, while detailing implementation considerations such as schema design, ETL/ELT processes, file formats like Delta, Iceberg, and Hudi, and factors influencing platform selection.

Apache SparkData LakeDelta Lake
0 likes · 20 min read
Choosing Between Data Warehouse, Data Lake, and Lakehouse: When to Use Each
DataFunTalk
DataFunTalk
Oct 28, 2023 · Big Data

Data Lake Architecture, Ingestion Options, Real-time Optimization, and Query Practices

This article presents a comprehensive overview of a unified data lake architecture, evaluates three ingestion solutions, details real‑time ingestion optimizations for Flink‑Hudi pipelines, and describes how Kyuubi enables unified query access across multiple engines, offering practical guidance for large‑scale data processing.

Data LakeFlinkHudi
0 likes · 14 min read
Data Lake Architecture, Ingestion Options, Real-time Optimization, and Query Practices
DataFunSummit
DataFunSummit
Oct 18, 2023 · Big Data

Kuaishou Data Lake Construction with Apache Hudi: Architecture, Challenges, and Solutions

This article explains why Kuaishou built a data lake, outlines the shortcomings of its previous Lambda architecture, describes the adoption of Apache Hudi for unified batch‑stream processing, and details the five major technical challenges and the corresponding solutions implemented to improve performance, consistency, and operational reliability.

Apache HudiData LakeFlink
0 likes · 17 min read
Kuaishou Data Lake Construction with Apache Hudi: Architecture, Challenges, and Solutions
Data Thinking Notes
Data Thinking Notes
Oct 11, 2023 · Big Data

How ByteDance Optimized Its E‑Commerce Data Lake to Cut Costs and Boost Real‑Time Accuracy

ByteDance revamped its traditional Lambda architecture for e‑commerce traffic data by introducing a new lake ingestion solution that reduces development and operational costs, ensures timely and stable data, and outlines future plans covering business background, ODS lake design, archiving tags, delayed data handling, and real‑time stability.

Data LakeFlinkHudi
0 likes · 7 min read
How ByteDance Optimized Its E‑Commerce Data Lake to Cut Costs and Boost Real‑Time Accuracy
Sohu Tech Products
Sohu Tech Products
Oct 11, 2023 · Industry Insights

How StarRocks Materialized Views Power Real‑Time Lakehouse Analytics

The article provides a deep technical overview of StarRocks 3.0’s data‑lake analysis capabilities, its unified Lakehouse architecture, Catalog integration, Trino compatibility, extensive I/O optimizations, materialized view features, resource isolation techniques, real‑world use cases, and future development directions.

AnalyticsData LakeLakehouse
0 likes · 22 min read
How StarRocks Materialized Views Power Real‑Time Lakehouse Analytics
DataFunSummit
DataFunSummit
Oct 1, 2023 · Big Data

Iceberg Data Lake: Core Features, Xiaomi Use Cases, and Future Plans

This presentation introduces Iceberg's core capabilities, details Xiaomi's practical applications—including log ingestion, near‑real‑time warehousing, offline challenges, column‑level encryption, and Hive migration—and outlines future development directions such as materialized views and cloud migration, providing a comprehensive view of modern data‑lake engineering.

Data LakeFlinkSpark
0 likes · 22 min read
Iceberg Data Lake: Core Features, Xiaomi Use Cases, and Future Plans
Architects Research Society
Architects Research Society
Sep 26, 2023 · Big Data

From a Single Data Lake to a Decentralized Data Mesh: A Step‑by‑Step Migration Guide

This article explains why traditional centralized data lakes hinder modern software development, introduces the data‑mesh concept as a decentralized alternative, and walks through an e‑commerce microservice example with concrete steps, data‑API designs, and migration tactics to transition from a monolithic lake to a distributed data mesh.

Data LakeData MeshETL
0 likes · 22 min read
From a Single Data Lake to a Decentralized Data Mesh: A Step‑by‑Step Migration Guide
iQIYI Technical Product Team
iQIYI Technical Product Team
Sep 22, 2023 · Big Data

Data Lake: Concepts, Architecture, and Application in iQIYI's Data Platform

iQIYI’s data‑middle‑platform team built a four‑zone data lake—raw, product, work, and sensitive—integrated with unified ODS/DWD/MID layers, a metadata catalog, and self‑service tools, leveraging HDFS, Hive/Iceberg, Spark/Trino, and Flink, migrated to Apache Iceberg for real‑time freshness, and now aims to further streamline modules and adopt new technologies.

Apache IcebergData LakeFlink
0 likes · 13 min read
Data Lake: Concepts, Architecture, and Application in iQIYI's Data Platform
Didi Tech
Didi Tech
Sep 19, 2023 · Cloud Native

OrangeFS: A Cloud‑Native Multi‑Protocol Distributed Data Lake Storage System

OrangeFS is Didi’s cloud‑native, multi‑protocol distributed data‑lake storage system that unifies POSIX, S3 and HDFS access on a single logical hierarchy, integrates with Kubernetes via a CSI plugin, supports on‑premise and public‑cloud backends, provides multi‑tenant isolation, and dramatically improves elasticity, utilization and latency for petabyte‑scale workloads such as ride‑hailing logs, machine‑learning training, finance and analytics.

CSIData LakeFUSE
0 likes · 17 min read
OrangeFS: A Cloud‑Native Multi‑Protocol Distributed Data Lake Storage System
DataFunTalk
DataFunTalk
Sep 16, 2023 · Big Data

StarRocks Data Lake Analysis, Materialized Views, and Lakehouse Architecture

This article explains how StarRocks 3.0 extends real‑time data‑warehouse capabilities to support data‑lake analysis, external catalog integration, Trino compatibility, extensive I/O optimizations, and powerful materialized‑view features that together enable a unified, cloud‑native Lakehouse solution with high performance and flexible resource isolation.

Data LakeLakehousePerformance
0 likes · 20 min read
StarRocks Data Lake Analysis, Materialized Views, and Lakehouse Architecture
iQIYI Technical Product Team
iQIYI Technical Product Team
Sep 15, 2023 · Big Data

Apache Spark at iQIYI: Current Status and Optimization

iQIYI now relies on Apache Spark as its main offline engine, processing over 200 000 daily tasks for ETL, data synchronization and analytics, while recent optimizations—dynamic resource allocation, adaptive query execution, compression, rebalance, Z‑order and resource‑governance—have cut compute usage by ~27 %, storage by up to 76 % and improved query speed, completing a large‑scale migration from Hive and paving the way for Spark 3.4 and Iceberg support.

Apache SparkData LakePerformance Optimization
0 likes · 21 min read
Apache Spark at iQIYI: Current Status and Optimization
DataFunTalk
DataFunTalk
Aug 20, 2023 · Databases

Best Practices for Building Low‑Cost Data Lake Analytics with AnalyticDB MySQL and Serverless Spark

This article presents a comprehensive technical overview of Alibaba Cloud AnalyticDB MySQL and its Serverless Spark integration, detailing architecture, core optimizations, security enhancements, and real‑world case studies that demonstrate how to achieve cost‑effective, high‑performance data lake analytics.

AnalyticDBCloud DatabaseData Lake
0 likes · 19 min read
Best Practices for Building Low‑Cost Data Lake Analytics with AnalyticDB MySQL and Serverless Spark
StarRocks
StarRocks
Aug 9, 2023 · Databases

StarRocks 3.1 Highlights: Faster Lakehouse Analytics and Advanced Materialized Views

StarRocks 3.1 introduces a cloud‑native, lakehouse‑oriented architecture with enhanced storage‑compute separation, up to 3‑6× faster data‑lake queries than Trino/Presto, expanded Iceberg and Paimon support, richer materialized view capabilities, new random bucketing, expression partitioning, generated columns, and spill‑to‑disk stability, all backed by extensive performance optimizations and open‑source contributions.

Data LakeLakehouseMaterialized Views
0 likes · 17 min read
StarRocks 3.1 Highlights: Faster Lakehouse Analytics and Advanced Materialized Views
Baidu Geek Talk
Baidu Geek Talk
Aug 7, 2023 · Artificial Intelligence

Storage Acceleration Solutions for Large AI Model Workflows

To tackle the massive data, high‑throughput and low‑latency demands of large‑model training and inference, the talk proposes a unified data‑lake built on scalable object storage combined with an acceleration layer—either a parallel file system or cloud‑native RapidFS cache—demonstrating multi‑fold training speedups, faster checkpoint uploads, and linear inference scaling.

AI Model StorageAccelerated FilesystemData Lake
0 likes · 18 min read
Storage Acceleration Solutions for Large AI Model Workflows
DataFunSummit
DataFunSummit
Jul 18, 2023 · Databases

Apache Doris Data Lake Federation Features Overview

This article introduces Apache Doris’s data lake federation capabilities, detailing its lake‑warehouse integration design, supported data sources such as Hive, Iceberg, Hudi, and Elasticsearch, performance optimizations for metadata and file access, case studies, community roadmap, and Q&A on replacing Presto.

Apache DorisData LakeFederated Query
0 likes · 21 min read
Apache Doris Data Lake Federation Features Overview
Data Thinking Notes
Data Thinking Notes
Jul 12, 2023 · Fundamentals

Why Metadata Governance Is the Backbone of Modern Data Platforms

This article explains how metadata serves as essential infrastructure for data platforms, detailing Huawei's classification framework, governance challenges, management architecture, integrated modeling, data lake handling, service management, and data map construction to bridge business and IT domains.

Data LakeEnterprise Datadata governance
0 likes · 24 min read
Why Metadata Governance Is the Backbone of Modern Data Platforms
DataFunTalk
DataFunTalk
Jul 10, 2023 · Big Data

Practical Experience of In‑Lake Warehouse Implementation Based on Lakehouse Architecture

This article presents a comprehensive overview of Lakehouse‑based in‑lake warehousing, covering common data‑lake misconceptions, the evolution from databases to data warehouses and lakes, the advantages of Lakehouse over traditional architectures, a reference multi‑layer architecture, typical use cases, challenges, future plans, and a brief Q&A.

Big Data ArchitectureData LakeHudi
0 likes · 20 min read
Practical Experience of In‑Lake Warehouse Implementation Based on Lakehouse Architecture
DataFunTalk
DataFunTalk
Jun 29, 2023 · Big Data

Practical Deployment of Delta Lake in BI and AI Products

This article summarizes a technical presentation on how Delta Lake is integrated into a BI+AI platform, covering the product background, data‑lake architecture, Delta Lake features such as ACID transactions, schema management, multi‑engine support, performance optimizations, and future development directions.

AIBIData Lake
0 likes · 12 min read
Practical Deployment of Delta Lake in BI and AI Products
DataFunTalk
DataFunTalk
Jun 26, 2023 · Big Data

Iceberg Data Lake: Core Features, Xiaomi Use Cases, and Future Plans

This presentation details Iceberg's core capabilities—transactional writes, schema evolution, implicit partitioning, and row‑level updates—while showcasing Xiaomi's real‑world applications such as log ingestion redesign, near‑real‑time warehousing, offline optimizations, column‑level encryption, Hive migration strategies, and outlining upcoming enhancements like materialized views and cloud migration.

Column EncryptionData LakeFlink
0 likes · 20 min read
Iceberg Data Lake: Core Features, Xiaomi Use Cases, and Future Plans
DataFunTalk
DataFunTalk
Jun 24, 2023 · Big Data

Design and Architecture of MaxCompute Lakehouse Near‑Real‑Time Incremental Processing

This article explains the evolution of Alibaba Cloud's MaxCompute platform into a lakehouse architecture that supports near‑real‑time incremental processing, detailing its development history, core design of transactional tables, five‑module technical stack, data ingestion methods, optimization services, transaction management, query capabilities, ecosystem integration, practical applications, future roadmap, and common user questions.

Data LakeIncremental ProcessingLakehouse
0 likes · 24 min read
Design and Architecture of MaxCompute Lakehouse Near‑Real‑Time Incremental Processing
Data Thinking Notes
Data Thinking Notes
Jun 18, 2023 · Big Data

Data Lake vs Data Warehouse: Uncover the Real Differences

This article explores the evolving concept of data lakes, compares them with traditional data warehouses across storage, modeling, tooling, and user roles, and examines the emerging lake‑warehouse integration, highlighting why both remain essential in modern big‑data architectures.

Data Lakebig datadata architecture
0 likes · 12 min read
Data Lake vs Data Warehouse: Uncover the Real Differences
Data Thinking Notes
Data Thinking Notes
Jun 4, 2023 · Big Data

How Distributed Lakehouse Architecture Solves Data Swamp Challenges

This article examines the explosion of heterogeneous data sources, the limitations of traditional data lakes and warehouses, and proposes a distributed lakehouse architecture that integrates advanced management layers to improve data governance, reliability, and support both SQL and advanced analytics workloads.

Data LakeDistributed ArchitectureELT
0 likes · 29 min read
How Distributed Lakehouse Architecture Solves Data Swamp Challenges
DataFunTalk
DataFunTalk
Jun 2, 2023 · Big Data

Iceberg Data Lake Implementation and Optimization at iQIYI

This article details iQIYI's adoption of the Iceberg data lake, covering its OLAP architecture, reasons for a lake, Iceberg table format advantages over Hive, platform construction, extensive performance optimizations, and real‑world business use cases such as ad‑flow unification, log analysis, audit, and CDC pipelines.

Data LakeFlinkPerformance Optimization
0 likes · 18 min read
Iceberg Data Lake Implementation and Optimization at iQIYI