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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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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

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.

Big DataCompute-Storage SeparationKubernetes

0 likes · 17 min read

StarRocks

Nov 3, 2023 · Databases

How StarRocks’ Spill to Disk Boosts Query Stability and Performance

StarRocks introduces a spill-to-disk mechanism that writes intermediate results of heavy operators to disk, freeing memory and enabling stable execution of ETL and ad‑hoc queries, while combined with materialized views it dramatically improves query success rates and delivers up to 4.35× faster performance than Spark.

Big DataDatabase OptimizationMaterialized Views

0 likes · 10 min read

StarRocks

Oct 31, 2023 · Databases

How Ctrip Accelerated Report Queries 10× with StarRocks: A Real‑World Lakehouse Migration

Ctrip migrated its Artnova reporting platform from Hive‑based queries to StarRocks, first loading data into OLAP tables and then using StarRocks as a lakehouse with Hive catalog, Data Cache and materialized views, achieving average query latency reductions from 20 seconds to 1.5 seconds, over 7× speed‑up versus Trino and up to 40× acceleration for complex workloads.

Big DataData CacheLakehouse

0 likes · 15 min read

StarRocks

Sep 6, 2023 · Big Data

How Paimon + StarRocks Revolutionize Lakehouse Analytics

This article reviews traditional Lambda and Kappa data‑warehouse architectures, then details four Paimon‑StarRocks lakehouse solutions—including a data‑lake center, accelerated query with materialized views, hot‑cold data separation, and the JNI connector—while also outlining StarRocks’ future roadmap for lakehouse analytics.

Big DataLakehousePaimon

0 likes · 11 min read

StarRocks

Aug 24, 2023 · Databases

How StarRocks Boosted Query Speed 3‑10× for a Billion‑Scale Reporting Platform

Facing massive daily query loads, Wanwu Newborn’s Watcher reporting platform migrated from MySQL, Greenplum, and Trino to StarRocks, cutting compute nodes by half while achieving 3‑10× faster query performance, higher success rates, and lower cost, as demonstrated by TPC‑DS and real‑world business query benchmarks.

MigrationOLAPStarRocks

0 likes · 14 min read

StarRocks

Aug 22, 2023 · Databases

How StarRocks Query Cache Supercharges High‑Concurrency Aggregations

StarRocks introduces a Query Cache that stores intermediate aggregation results in memory, enabling reuse across semantically equivalent, partition‑overlapping, or append‑only queries, which can boost query performance by 3‑17× in high‑concurrency scenarios while reducing CPU and disk load.

High ConcurrencyMPP databaseQuery Cache

0 likes · 13 min read

StarRocks

Aug 16, 2023 · Databases

How StarRocks Materialized Views Simplify Data Engineering in a Lake‑Warehouse Architecture

StarRocks 3.0 introduces a lake‑warehouse unified architecture where materialized views reduce data processing complexity, boost query performance, and improve timeliness, offering declarative modeling, transparent acceleration, and incremental computation for enterprise‑scale analytics.

Data ModelingIncremental RefreshLake Warehouse

0 likes · 19 min read

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.

LakehouseMaterialized ViewsSQL

0 likes · 17 min read

StarRocks

Jul 27, 2023 · Cloud Native

Deploy StarRocks Quickly with Docker and Kubernetes: Step‑by‑Step Guide

This guide explains how to set up a StarRocks cluster using Docker for rapid testing and the StarRocks Kubernetes Operator for production‑grade deployments, covering architecture basics, required tools, command‑line steps, YAML configuration, and connection methods for both internal and external access.

DockerKubernetesStarRocks

0 likes · 11 min read

Deploy StarRocks Quickly with Docker and Kubernetes: Step‑by‑Step Guide