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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

Dec 22, 2023 · Databases

What’s New in StarRocks 3.2? Key Features and Usability Enhancements

StarRocks 3.2, released on December 21, 2023, introduces major usability upgrades—including optimized random bucketing, fast schema evolution, PIPE import, HTTP SQL API, runtime profiling, enhanced storage‑compute separation, data lake analysis, and advanced materialized view capabilities—while refining existing features such as indexing, catalog support, and export syntax.

DatabaseRelease NotesStarRocks

0 likes · 15 min read

StarRocks

Dec 19, 2023 · Big Data

How WeChat Achieved Sub‑Second Real‑Time Analytics with StarRocks Lakehouse

WeChat transformed its data platform from Hadoop and ClickHouse to a StarRocks‑based lakehouse, tackling massive data volume, ultra‑low latency, and storage fragmentation by deploying lake‑on‑warehouse and warehouse‑lake fusion architectures, real‑time incremental materialized views, and unified SQL access, resulting in dramatic cost cuts and performance gains.

Big DataLakehouseStarRocks

0 likes · 15 min read

StarRocks

Dec 12, 2023 · Databases

How StarRocks Enables Real-Time Updates in Analytical Databases

The article explains why analytical databases struggle with real‑time data changes due to columnar storage, complex indexes and distributed processing, and then details StarRocks' primary‑key model, adaptive update mode, bitmap indexes, row/column partial updates, and practical SQL upsert techniques to achieve low‑latency updates without sacrificing query performance.

Partial UpdatePrimary KeyReal-Time Update

0 likes · 15 min read

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 SeparationData Lake

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 DataMaterialized ViewsSpill

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.

OLAPStarRocksmigration

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 databasePerformance Optimization

0 likes · 13 min read

How StarRocks Query Cache Supercharges High‑Concurrency Aggregations