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DataFunSummit
DataFunSummit
Apr 28, 2026 · Big Data

Dynamic Table: A Next‑Generation Data Processing Architecture Powered by Incremental Computing

The article examines the limitations of traditional batch and stream processing, explains how Hologres Dynamic Table combines declarative freshness settings with stateful incremental computation to bridge the gap between low‑cost batch jobs and low‑latency streaming, and presents benchmark results and real‑world case studies.

BenchmarkDynamic TableHologres
0 likes · 13 min read
Dynamic Table: A Next‑Generation Data Processing Architecture Powered by Incremental Computing
DataFunSummit
DataFunSummit
Apr 23, 2026 · Databases

How Hologres Dynamic Table Redefines Data Processing with Incremental Computing

The article analyzes the limitations of traditional batch and stream processing, introduces Hologres Dynamic Table as a declarative, incremental‑compute framework that bridges the gap between low‑cost batch jobs and low‑latency streaming, and validates its performance with benchmarks and real‑world case studies.

Dynamic TableHologrescloud data warehouse
0 likes · 13 min read
How Hologres Dynamic Table Redefines Data Processing with Incremental Computing
DataFunTalk
DataFunTalk
Apr 22, 2026 · Industry Insights

How Xiaohongshu Cut Data Platform Costs by Two‑Thirds with Incremental Computing

This article details Xiaohongshu's journey from a ClickHouse‑based batch analytics stack to a unified lakehouse architecture powered by generic incremental computing, showing how the company reduced architecture complexity, resource consumption and development effort each to roughly one‑third while supporting trillions of daily events with sub‑10‑second query latency.

Big DataData ArchitectureLakehouse
0 likes · 24 min read
How Xiaohongshu Cut Data Platform Costs by Two‑Thirds with Incremental Computing
DataFunTalk
DataFunTalk
Apr 16, 2026 · Big Data

How Xiaohongshu Cut Data Architecture Costs by Two‑Thirds with Incremental Computing

This article details Xiaohongshu's data platform evolution from a simple ClickHouse‑based ad‑hoc system to a Lambda‑style architecture and finally a lakehouse solution, highlighting how the adoption of a new incremental computing model reduced architectural complexity, resource consumption and development effort each to roughly one‑third while delivering sub‑second query performance on petabyte‑scale data.

Big DataData ArchitectureLakehouse
0 likes · 21 min read
How Xiaohongshu Cut Data Architecture Costs by Two‑Thirds with Incremental Computing
DataFunTalk
DataFunTalk
Apr 10, 2026 · Big Data

How Xiaohongshu Cut Data Architecture Costs by Two‑Thirds with Incremental Computing

This article analyzes Xiaohongshu's data platform evolution—from a simple ClickHouse‑based analytics layer to a Lambda architecture and finally a lakehouse design—highlighting how adopting a new incremental computing model reduced architecture complexity, resource consumption, and development effort each to roughly one‑third while delivering sub‑second query performance on petabyte‑scale data.

Big DataData ArchitectureLakehouse
0 likes · 22 min read
How Xiaohongshu Cut Data Architecture Costs by Two‑Thirds with Incremental Computing
DataFunTalk
DataFunTalk
Nov 22, 2025 · Big Data

How Modern Data Lakes and AI Governance Transform Enterprise Analytics

This article collection examines Tencent Cloud’s Iceberg batch‑stream integration, AI‑driven game data governance, Apache Gravitino unified metadata and lineage, Xiaohongshu’s multimodal data‑lake evolution, and Volcano Engine’s Data+AI multimodal lake, highlighting architectures, techniques, performance gains, and practical implementations.

AI GovernanceData LakeGravitino
0 likes · 7 min read
How Modern Data Lakes and AI Governance Transform Enterprise Analytics
DataFunSummit
DataFunSummit
Nov 10, 2025 · Big Data

How Xiaohongshu Cut Data Architecture Costs by One‑Third with Incremental Computing

This article explains how Xiaohongshu, a lifestyle community with over 350 million monthly users, transformed its data platform from a traditional Lambda architecture to a next‑generation incremental computing model, reducing architectural complexity, resource consumption and development effort each by roughly two‑thirds while supporting massive real‑time and offline data demands.

AIBig DataData Architecture
0 likes · 6 min read
How Xiaohongshu Cut Data Architecture Costs by One‑Third with Incremental Computing
DataFunSummit
DataFunSummit
Oct 4, 2025 · Big Data

How Xiaohongshu Cut Data Architecture Costs by Two‑Thirds with Incremental Computing

This article details how Xiaohongshu's massive user‑generated data platform evolved from a simple ClickHouse‑based architecture to a multi‑stage lakehouse design, adopting a new incremental computing model that reduced architecture complexity, resource and development costs by one‑third while boosting query performance for petabyte‑scale data.

Lakehouseincremental computing
0 likes · 19 min read
How Xiaohongshu Cut Data Architecture Costs by Two‑Thirds with Incremental Computing
DataFunSummit
DataFunSummit
Jul 20, 2025 · Big Data

Why Incremental Computing Is Replacing Lambda Architecture in Modern Big Data Platforms

This interview with Yunqi Technology CTO Guan Tao explains how the traditional Lambda architecture’s triple‑system complexity drives costs and operational pain, and why the company’s General Incremental Computing (GIC) approach offers a unified, cost‑effective Kappa‑style solution for real‑time, batch, and interactive analytics.

Kappa architectureLambda architecturedata engineering
0 likes · 13 min read
Why Incremental Computing Is Replacing Lambda Architecture in Modern Big Data Platforms
Xiaohongshu Tech REDtech
Xiaohongshu Tech REDtech
May 19, 2025 · Industry Insights

How Xiaohongshu Built a Minute‑Level Near‑Real‑Time Data Warehouse with Incremental Computing

Facing billions of daily logs and the need for minute‑level experiment metrics, Xiaohongshu partnered with Yunqi Tech to design a generic incremental‑compute solution that delivers near‑real‑time data warehousing with lower cost, higher accuracy, simplified pipelines, and improved query performance.

Big DataData LakeFlink
0 likes · 24 min read
How Xiaohongshu Built a Minute‑Level Near‑Real‑Time Data Warehouse with Incremental Computing
Tencent Cloud Developer
Tencent Cloud Developer
May 8, 2025 · Big Data

How Setats Unifies Stream, Batch, and Incremental Processing for Real‑Time Data Lakes

At the 2025 DA Data+AI Conference in Shanghai, Tencent Cloud unveiled Setats—a unified stream‑batch‑incremental engine that cuts system costs, delivers second‑level data visibility and real‑time changelog generation, and demonstrates measurable performance gains in automotive IoT analytics while integrating tightly with the WeData platform.

Batch ProcessingBig Data ArchitectureData Lake
0 likes · 5 min read
How Setats Unifies Stream, Batch, and Incremental Processing for Real‑Time Data Lakes
DataFunSummit
DataFunSummit
Jan 9, 2024 · Big Data

Introducing Yunqi Lakehouse: An Integrated Cloud‑Native Data Platform with Incremental Computing and Auto Materialized Views

This article introduces Yunqi's self‑developed Lakehouse product, explaining its cloud‑native, one‑stop data platform architecture, incremental computing that balances freshness, performance and cost, and the autoMV feature that automatically creates materialized views to boost query speed up to nine times.

Auto Materialized ViewBig DataData Platform
0 likes · 14 min read
Introducing Yunqi Lakehouse: An Integrated Cloud‑Native Data Platform with Incremental Computing and Auto Materialized Views
DataFunTalk
DataFunTalk
Dec 18, 2023 · Big Data

Unified Data Architecture: Balancing Freshness, Cost, and Performance with Incremental Computing

The article explains why unified data architecture is essential to avoid duplication and inefficiency, discusses differing performance trade‑offs among batch, streaming, and interactive analytics, introduces an incremental computation model that unifies these modes, and invites readers to a Dec 19, 2023 technical sharing event.

Batch ProcessingBig DataData Architecture
0 likes · 3 min read
Unified Data Architecture: Balancing Freshness, Cost, and Performance with Incremental Computing
ITPUB
ITPUB
Apr 8, 2023 · Big Data

How Bilibili Cut Data Pipeline Costs by 20% with Flink Real‑Time Incremental Computing

Facing daily terabyte‑scale data ingestion and costly duplicate reads in its ODS‑to‑DWD pipeline, Bilibili introduced a Flink‑based real‑time incremental computation and multi‑level partition shuffling, dramatically reducing read amplification, cutting resource usage by ~20%, improving latency to minutes, and enhancing scalability.

Big DataFlinkReal-time Processing
0 likes · 19 min read
How Bilibili Cut Data Pipeline Costs by 20% with Flink Real‑Time Incremental Computing