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StarRocks

StarRocks is an open‑source project under the Linux Foundation, focused on building a high‑performance, scalable analytical database that enables enterprises to create an efficient, unified lake‑house paradigm. It is widely used across many industries worldwide, helping numerous companies enhance their data analytics capabilities.

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Latest from StarRocks

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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

StarRocks

Nov 4, 2022 · Big Data

Building a High‑Performance, Cost‑Effective Cloud Lakehouse with StarRocks and EMR

This article explains how to design and implement a cloud‑native Lakehouse using StarRocks and Tencent Cloud EMR, covering core technical requirements, a five‑layer architecture, data ingestion with Iceberg/Hudi, performance tricks like Z‑order clustering, cost‑control through elastic scaling, and the key product features of EMR StarRocks.

EMRHudiIceberg

0 likes · 24 min read

StarRocks

Nov 2, 2022 · Databases

Mastering Join Optimization in StarRocks: Techniques, Algorithms, and Distributed Planning

This article provides a comprehensive, step‑by‑step guide to StarRocks join optimization, covering join types, logical rewrite rules, predicate push‑down, join reorder algorithms, cost modeling, distributed join strategies, and runtime filters, while offering practical tips for achieving high‑performance query execution.

Cost ModelDistributed SQLJOIN optimization

0 likes · 26 min read

StarRocks

Oct 20, 2022 · Databases

Inside StarRocks Pipeline Engine: How BE Splits and Schedules Queries

This article explains the core concepts, architecture, and source‑code details of StarRocks’ Pipeline execution framework, covering BE initialization, query lifecycle management, operator splitting, PipelineBuilder processing, and the scheduling logic of PipelineDriver, with concrete code examples and diagrams to illustrate each step.

Database EnginePipelineQuery Execution

0 likes · 21 min read

StarRocks

Oct 13, 2022 · Databases

Inside StarRocks: How the Pipeline Execution Engine Boosts Query Performance

This article explains the core concepts, architecture, and code logic of StarRocks' Pipeline execution framework, covering ExecPlan, PlanFragment, Fragment Instance, ExecNode, SourceOperator, SinkOperator, PipelineDriver scheduling, asynchronous handling of blocking operations, and the roles of FE and BE in MPP scheduling.

Execution EngineMPPPipeline

0 likes · 13 min read

StarRocks

Oct 11, 2022 · Databases

Why StarRocks Outperforms Traditional OLAP: Architecture, Storage Model, and Real‑World Use Cases

This article explains the advantages of StarRocks as a next‑generation MPP database, detailing its simplified architecture, vectorized engine, storage layout, partitioning and bucketing strategies, and showcases two production case studies with performance comparisons, configuration tips, and future roadmap considerations.

Flink IntegrationMPP databaseStarRocks

0 likes · 17 min read

StarRocks

Aug 17, 2022 · Databases

Why Vectorization Supercharges Database Performance: Deep Dive into StarRocks

This article explains how CPU‑centric vectorization, especially SIMD, reduces instruction count and CPI, addresses the four major CPU bottlenecks, and how StarRocks systematically applies automatic and manual SIMD techniques, verification methods, and a suite of engineering optimizations to achieve multi‑fold query speedups.

CPU optimizationSIMDStarRocks

0 likes · 16 min read

StarRocks

Aug 10, 2022 · Databases

How 58 Group Scaled AP Analytics with StarRocks: Benchmarks, Ops Tools, and Cloud Deployment

Facing massive AP‑heavy analytics workloads, 58 Group evaluated TiFlash, ClickHouse and StarRocks, chose StarRocks for its superior write/read performance and ease of operation, built internal tools for topology, cluster, Kafka import and slow‑SQL management, and migrated to cloud‑native Docker deployments, achieving up to 90% query speedup and massive data‑volume reductions.

Performancedatabase

0 likes · 17 min read

StarRocks

Aug 6, 2022 · Databases

How StarRocks Accelerates Low‑Cardinality String Queries with Global Dictionary Optimization

This article explains how StarRocks uses a global dictionary to transform low‑cardinality string columns into integer codes, dramatically improving query performance across scan, filter, aggregation, join, shuffle, and sort phases, and details the construction, maintenance, and practical impact of this optimization.

StarRocksglobal dictionarylow cardinality

0 likes · 17 min read

StarRocks

Jul 22, 2022 · Big Data

How 37 Mobile Games Boosted Analytics with StarRocks: A Real‑World Performance Case Study

37 Mobile Games, a leading mobile game publisher, migrated its user‑profile analytics from a Hadoop‑Hudi‑Kafka‑Hive‑Flink stack to StarRocks, achieving sub‑second query latency on billion‑row tables, simplifying operations, reducing storage costs, and enabling real‑time data sync, as detailed in this technical case study.

OLAPPerformance optimizationStarRocks

0 likes · 12 min read

How 37 Mobile Games Boosted Analytics with StarRocks: A Real‑World Performance Case Study