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Compute-Storage Separation

31 articles · Page 1 of 1
360 Zhihui Cloud Developer
360 Zhihui Cloud Developer
Sep 15, 2026 · Databases

ZestKV: 360's Cloud-Native Serverless KV Store with Compute-Storage Separation

360 Zhihui Cloud's ZestKV is a Redis-compatible, cloud-native serverless KV store that separates compute from storage using shared object storage and a log service, enabling elastic scaling via region sharding, background task decoupling, and a dual-async write path achieving 700K SET QPS in benchmarks.

Cloud-Native DatabaseCompute-Storage SeparationElastic Scaling
0 likes · 24 min read
ZestKV: 360's Cloud-Native Serverless KV Store with Compute-Storage Separation
YiSu Grain
YiSu Grain
Jul 28, 2026 · Big Data

Day 39: Big Data Architecture – Distributed Storage, Batch vs Stream Processing, and Compute‑Storage Separation

This lesson explains why a single database cannot scale for massive e‑commerce data, introduces the three core pillars of distributed storage—sharding, replication, and horizontal scaling—covers batch and stream processing differences with Spark, Hive, Flink and Storm, compares compute‑storage integration versus separation, and shows how Kafka, HDFS, Spark and Flink fit together in a real‑time data platform.

Batch ProcessingCompute-Storage SeparationFlink
0 likes · 25 min read
Day 39: Big Data Architecture – Distributed Storage, Batch vs Stream Processing, and Compute‑Storage Separation
Architecture & Thinking
Architecture & Thinking
Apr 30, 2026 · Cloud Native

How RocketMQ 5.0’s New Proxy Layer Enables Compute‑Storage Separation and Cloud‑Native Scaling

RocketMQ 5.0 replaces the monolithic Broker with a stateless Proxy layer that decouples compute from storage, solves scalability, multi‑protocol and cloud‑native adaptation challenges, and is demonstrated through detailed architecture comparisons, Java code samples, and two real‑world IoT and finance case studies showing significant performance and cost benefits.

Compute-Storage SeparationMulti-ProtocolProxy
0 likes · 20 min read
How RocketMQ 5.0’s New Proxy Layer Enables Compute‑Storage Separation and Cloud‑Native Scaling
StarRocks
StarRocks
Dec 18, 2025 · Databases

How Fresha Scaled Real‑Time Analytics with StarRocks: A Deep Dive into Their Hybrid Architecture

Facing Postgres overload and costly Snowflake queries, Fresha rebuilt its analytics platform by introducing StarRocks as a unified SQL entry point, combining federated lakehouse queries with high‑performance internal tables, which reduced homepage query latency to around 200 ms and achieved minute‑level data freshness across real‑time, historical, and search workloads.

Compute-Storage SeparationData PipelineHybrid Architecture
0 likes · 20 min read
How Fresha Scaled Real‑Time Analytics with StarRocks: A Deep Dive into Their Hybrid Architecture
Ctrip Technology
Ctrip Technology
Nov 27, 2025 · Big Data

How Ctrip Cut Query Latency by 85% with StarRocks’ Compute‑Storage Separation

Ctrip migrated its massive User Behavior Tracking system from ClickHouse to a compute‑storage separated StarRocks cluster on Kubernetes, achieving millisecond‑level query latency, halving storage usage, reducing node count, and sustaining millions‑of‑rows‑per‑second write throughput while simplifying scaling and operations.

ClickHouseCompute-Storage SeparationKubernetes
0 likes · 15 min read
How Ctrip Cut Query Latency by 85% with StarRocks’ Compute‑Storage Separation
BanTech Think Tank
BanTech Think Tank
Oct 31, 2025 · Databases

Breaking the AI‑Trusted Storage Barrier: Commercial Banks’ AI+Domestic‑Innovation Practices

The article analyzes how Chinese commercial banks are addressing AI data governance and domestic‑technology (信创) challenges by replacing server‑local disk replicas with professional SAN storage integrated into a true compute‑storage‑separated architecture, highlighting survey results, performance benchmarks, and ecosystem collaborations that demonstrate improved stability, latency, and scalability.

AICompute-Storage SeparationPerformance
0 likes · 19 min read
Breaking the AI‑Trusted Storage Barrier: Commercial Banks’ AI+Domestic‑Innovation Practices
Lakehouse Research Base
Lakehouse Research Base
Aug 28, 2025 · Databases

Why Stream Load Beats INSERT 30x in StarRocks Compute-Storage Separation

In StarRocks compute-storage separation clusters, Stream Load achieves 20-30x faster bulk data ingestion than INSERT by leveraging batch-oriented design, direct compute-node access, single-transaction metadata handling, large-file storage writes, and concentrated resource scheduling, avoiding INSERT's per-row overheads.

Compute-Storage SeparationINSERTStarRocks
0 likes · 11 min read
Why Stream Load Beats INSERT 30x in StarRocks Compute-Storage Separation
StarRocks
StarRocks
Jan 2, 2025 · Big Data

StarRocks Compute‑Storage Separation Cuts Costs 40% and Boosts Efficiency 20% at DMALL

DMALL upgraded its big‑data platform by adopting StarRocks 3.x with compute‑storage separation, lakehouse external tables, and Kubernetes deployment, achieving 20% higher compute utilization, 40% lower storage cost, faster cluster provisioning, and notable improvements in development and operations efficiency.

Compute-Storage SeparationKubernetesLakehouse
0 likes · 25 min read
StarRocks Compute‑Storage Separation Cuts Costs 40% and Boosts Efficiency 20% at DMALL
Big Data Technology & Architecture
Big Data Technology & Architecture
Dec 18, 2024 · Big Data

Key Trends of Flink 2.0: Compute‑Storage Separation, Unified Batch‑Stream, and Streaming Warehouse

The article reviews the major directions of Flink 2.0—including compute‑storage separation, a new Materialized Table for unified batch‑stream processing, and deeper integration with Paimon for streaming warehouses—while offering a cautious perspective on their practical impact and migration challenges.

Batch-Stream IntegrationCompute-Storage SeparationFlink
0 likes · 5 min read
Key Trends of Flink 2.0: Compute‑Storage Separation, Unified Batch‑Stream, and Streaming Warehouse
Architects' Tech Alliance
Architects' Tech Alliance
Jun 11, 2024 · Industry Insights

Why Traditional Distributed Storage Struggles and How New Compute‑Storage Separation Can Transform Cloud Data Centers

The article analyzes the limitations of current server‑based distributed storage—such as data‑lifecycle mismatches, performance‑resource trade‑offs, serverless workload demands, and the costly "datacenter tax"—and presents emerging hardware trends and a novel compute‑storage separation architecture that promises higher efficiency, reliability, and scalability for cloud and internet data centers.

CXLCompute-Storage SeparationDPU
0 likes · 13 min read
Why Traditional Distributed Storage Struggles and How New Compute‑Storage Separation Can Transform Cloud Data Centers
DataFunSummit
DataFunSummit
Mar 14, 2024 · Big Data

Tencent Game Data Analysis: Lakehouse Integration Practice

This article presents Tencent Game's comprehensive lakehouse integration practice, detailing the project background, storage‑compute separation, data layering, unified DDL/DML operations, performance optimizations, and future plans, illustrating how StarRocks, Iceberg, and Spark are combined to achieve scalable, cost‑effective analytics for massive game data.

Compute-Storage SeparationLakehousePerformance Optimization
0 likes · 16 min read
Tencent Game Data Analysis: Lakehouse Integration Practice
StarRocks
StarRocks
Nov 23, 2023 · Databases

How StarRocks Redefines Lakehouse Architecture with Compute‑Storage Separation

StarRocks, an open‑source MPP analytical database, consolidates BI, interactive, and real‑time analytics into a single engine by evolving from version 1.0 to 3.x, introducing compute‑storage separation, unified catalog, generated columns, operator spill, and advanced materialized views, while outlining its cloud‑native lakehouse roadmap.

Compute-Storage SeparationLakehouseMPP database
0 likes · 22 min read
How StarRocks Redefines Lakehouse Architecture with Compute‑Storage Separation
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
Sep 19, 2023 · Cloud Native

How REDck Transformed ClickHouse into a Scalable Cloud‑Native Real‑Time Data Warehouse

REDck, a cloud‑native real‑time data warehouse built on open‑source ClickHouse, overcomes the original MPP architecture’s scaling and maintenance limits by separating compute and storage, introducing unified metadata, multi‑level caching, bucket‑based sharding, and distributed transaction support, delivering petabyte‑scale, 99.9% availability and ten‑fold cost and performance gains for Xiaohongshu’s diverse workloads.

ClickHouseCompute-Storage SeparationReal-time OLAP
0 likes · 22 min read
How REDck Transformed ClickHouse into a Scalable Cloud‑Native Real‑Time Data Warehouse
DataFunSummit
DataFunSummit
Sep 16, 2023 · Big Data

Kingsoft Cloud's Big Data Compute‑Storage Separation Practices and KS3‑HDFS Solution

This article presents Kingsoft Cloud's comprehensive practice on big data compute‑storage separation, detailing the challenges of modern data platforms, comparing HDFS with object storage, describing three separation modes, and explaining the architecture, core modules, performance optimizations, and advantages of the KS3‑HDFS solution.

Cloud ComputingCompute-Storage SeparationKS3-HDFS
0 likes · 21 min read
Kingsoft Cloud's Big Data Compute‑Storage Separation Practices and KS3‑HDFS Solution
StarRocks
StarRocks
May 16, 2023 · Databases

How StarRocks’ Compute‑Storage Separation Cuts Costs and Boosts Query Efficiency

This article explains how StarRocks’ new compute‑storage separation architecture reduces storage expenses and improves analytical performance by leveraging hot‑cold data segregation, elastic scaling, caching strategies, multi‑version storage, and optimized compaction, illustrated with real‑world log and e‑commerce workload examples.

Compute-Storage SeparationMPP databasePerformance Optimization
0 likes · 18 min read
How StarRocks’ Compute‑Storage Separation Cuts Costs and Boosts Query Efficiency
ITPUB
ITPUB
Nov 19, 2022 · Databases

Choosing Between OceanBase and TiDB: Architecture, Performance, and Trade‑offs

This article compares the architectures of OceanBase and TiDB, explaining how their sharding and compute‑storage separation designs affect high availability, latency, and workload suitability, and offers guidance on selecting the right distributed database for complex enterprise applications.

Compute-Storage SeparationOceanBaseTiDB
0 likes · 12 min read
Choosing Between OceanBase and TiDB: Architecture, Performance, and Trade‑offs
Baidu Geek Talk
Baidu Geek Talk
Aug 5, 2022 · Big Data

How Baidu Cloud Accelerates Data Lakes with Compute‑Storage Separation

This article analyzes Baidu Intelligent Cloud's data‑lake acceleration strategy, covering the evolution of big‑data architectures, the advantages and challenges of compute‑storage separation, the native hierarchical namespace and RapidFS cache solutions, performance test results, and recommended deployment patterns.

BOSCompute-Storage SeparationData Lake
0 likes · 17 min read
How Baidu Cloud Accelerates Data Lakes with Compute‑Storage Separation
Baidu Intelligent Cloud Tech Hub
Baidu Intelligent Cloud Tech Hub
Jul 28, 2022 · Big Data

How Baidu Cloud Accelerates Data Lakes with Compute‑Storage Separation

This article explains Baidu Intelligent Cloud’s data lake acceleration solution, covering the evolution of big‑data technologies, the benefits and challenges of compute‑storage separation, the architecture of BOS object storage, and the native hierarchical namespace and RapidFS cache mechanisms that boost performance and reduce costs.

BOSCompute-Storage SeparationData Lake
0 likes · 18 min read
How Baidu Cloud Accelerates Data Lakes with Compute‑Storage Separation
Zuoyebang Tech Team
Zuoyebang Tech Team
Apr 7, 2022 · Cloud Native

How Fluid Transforms Large‑Scale Data Retrieval on Kubernetes

This article explains how Zuoyebang redesigned its massive data retrieval platform by separating compute and storage with the Fluid project on Kubernetes, achieving minute‑level hundred‑TB distribution, elastic caching, and improved stability for real‑time educational services.

Compute-Storage SeparationData RetrievalFluid
0 likes · 8 min read
How Fluid Transforms Large‑Scale Data Retrieval on Kubernetes
Architecture Digest
Architecture Digest
Dec 8, 2021 · Cloud Native

Implementing Compute-Storage Separation for Large-Scale Retrieval Systems Using Fluid

This article describes the challenges of operating massive, TB‑scale retrieval clusters at Zuoyebang, and presents a Fluid‑based compute‑storage separation architecture that improves data distribution, update efficiency, scalability, and stability, enabling containerized search services to be managed like regular stateless workloads.

Compute-Storage SeparationFluidKubernetes
0 likes · 13 min read
Implementing Compute-Storage Separation for Large-Scale Retrieval Systems Using Fluid
ITPUB
ITPUB
Jun 30, 2021 · Databases

Why GaussDB for Redis Outperforms Open‑Source Redis: Architecture, Benefits, and Real‑World Performance

This article explains the limitations of open‑source Redis, introduces Huawei Cloud's GaussDB for Redis with its compute‑storage separation architecture, details its design, implementation, and disaster‑recovery mechanisms, and summarizes the competitive advantages such as strong consistency, high availability, elastic scaling, and superior performance.

Compute-Storage SeparationGaussDBNoSQL
0 likes · 14 min read
Why GaussDB for Redis Outperforms Open‑Source Redis: Architecture, Benefits, and Real‑World Performance
Tencent Cloud Developer
Tencent Cloud Developer
Dec 30, 2020 · Big Data

How Alluxio Boosts Tencent Cloud EMR: Cutting Bandwidth by 50% and Accelerating IO‑Intensive Workloads

This article analyzes the challenges of traditional monolithic big‑data architectures, explains how Tencent Cloud EMR integrates Alluxio for compute‑storage separation, presents detailed performance benchmarks showing 20‑50% bandwidth reduction and 5‑40% query speedup, and outlines the specific tuning measures applied.

AlluxioCloud ComputingCompute-Storage Separation
0 likes · 10 min read
How Alluxio Boosts Tencent Cloud EMR: Cutting Bandwidth by 50% and Accelerating IO‑Intensive Workloads
Alibaba Cloud Native
Alibaba Cloud Native
Apr 9, 2019 · Big Data

How Compute‑Storage Separation Cuts Costs and Boosts Performance for Big Data on Kubernetes

This article examines the challenges of big‑data storage in containerized environments, compares compute‑storage‑separated architectures with traditional setups, presents performance and cost benchmarks of Alibaba Cloud ECS instances, and outlines practical storage options such as OSS, NAS, and DFS for Spark workloads on Kubernetes.

Compute-Storage SeparationKubernetesSpark
0 likes · 14 min read
How Compute‑Storage Separation Cuts Costs and Boosts Performance for Big Data on Kubernetes
Tencent Cloud Developer
Tencent Cloud Developer
Mar 27, 2019 · Databases

Technical Overview and Optimizations of Tencent Cloud CynosDB for MySQL

Tencent Cloud’s CynosDB for MySQL separates compute from distributed storage, using a log‑driven, stateless architecture that eliminates local I/O, enables sub‑second failover, 2.5× write performance, lock‑free structures, async group‑commit, compressed logs, fast parallel recovery, and scalable replication, with future plans for external buffer pools and multi‑master support.

Cloud DatabaseCompute-Storage SeparationCynosDB
0 likes · 23 min read
Technical Overview and Optimizations of Tencent Cloud CynosDB for MySQL
Efficient Ops
Efficient Ops
Sep 27, 2018 · Databases

How SequoiaDB’s Multi-Model Architecture Redefines Cloud‑Native Distributed Databases

SequoiaDB, a financial‑grade open‑source distributed database, combines a multi‑model engine with a compute‑storage separation architecture to deliver full MySQL, PostgreSQL and SparkSQL compatibility, elastic scaling, HTAP capabilities, and robust multi‑site disaster recovery for cloud‑native enterprise workloads.

Compute-Storage SeparationHTAPcloud-native
0 likes · 12 min read
How SequoiaDB’s Multi-Model Architecture Redefines Cloud‑Native Distributed Databases
Tencent Cloud Developer
Tencent Cloud Developer
Jun 12, 2018 · Cloud Native

CynosDB: Tencent Cloud's Next-Generation Enterprise Distributed Cloud Database

CynosDB, Tencent Cloud’s next‑generation enterprise distributed database, re‑architects MySQL with compute‑storage separation, distributed high‑availability storage, and RDMA‑accelerated low‑latency replication, delivering extreme performance, scalability, sub‑millisecond response times, and nine‑nine data reliability for cloud‑native applications.

Cloud DatabaseCompute-Storage SeparationCynosDB
0 likes · 9 min read
CynosDB: Tencent Cloud's Next-Generation Enterprise Distributed Cloud Database