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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

Jul 24, 2024 · Big Data

Why Lakehouse Architecture Is Redefining Big Data Infrastructure in the AI Era

The article examines the rapid rise of lakehouse architecture, its market momentum, core components—including storage, metadata, table formats, and compute layers—compares Iceberg, Hudi, and Delta Lake, discusses the shift from HDFS to object storage, and outlines the strategic importance of lakehouses for AI-driven data management and future data infrastructure trends.

AIApache IcebergBig Data

0 likes · 28 min read

Why Lakehouse Architecture Is Redefining Big Data Infrastructure in the AI Era

StarRocks

Jul 17, 2024 · Databases

Unlock 30% Faster Queries: StarRocks on AWS Graviton3 Performance Deep Dive

This article examines how StarRocks, a next‑generation MPP database, leverages AWS Graviton3 instances to achieve over 30% query speed improvement and 15% cost reduction compared with x86 C6i instances, detailing benchmark methodology, hardware specs, SIMD optimizations, and real‑world OLAP results.

AWS Graviton3MPP databaseStarRocks

0 likes · 11 min read

StarRocks

Jul 2, 2024 · Big Data

What’s New in StarRocks 3.3? Deep Dive into Lakehouse‑Optimized Performance and Features

StarRocks 3.3 introduces a comprehensive set of enhancements—including maturity levels, ARM‑optimized performance, advanced caching, materialized‑view rewrites, storage optimizations, and expanded lakehouse ecosystem support—that together boost stability, query speed, and usability for large‑scale analytics workloads.

Big DataLakehouseStarRocks

0 likes · 15 min read

StarRocks

Jun 18, 2024 · Databases

How StarRocks Compaction Boosts Query Performance: Mechanics, Tuning, and Best Practices

This article explains StarRocks' compaction process that merges multiple data versions into larger files to reduce I/O, details the scheduler and executor roles, shows how to monitor and control compaction via SQL commands, and provides tuning parameters and best‑practice recommendations for optimal performance.

Data ManagementSQLStarRocks

0 likes · 21 min read

StarRocks

Jun 6, 2024 · Big Data

Why StarRocks Beats Trino: A Deep Technical Comparison

This article provides a detailed technical comparison between StarRocks and Trino, covering their shared MPP architecture, cost‑based optimizer, pipeline execution, ANSI SQL support, differences in vectorized execution, materialized view capabilities, caching systems, data source connectors, benchmark results, high‑availability designs, join algorithms, and real‑world user case studies.

Big DataCacheMPP

0 likes · 20 min read

StarRocks

May 22, 2024 · Big Data

Unlocking Data Lake Power: Iceberg Architecture & StarRocks Acceleration

Apache Iceberg offers a modern, ACID‑compliant table format for data lakes with features like hidden partitions and schema evolution, while StarRocks provides high‑performance query acceleration, metadata caching, and distributed planning to address Iceberg’s latency challenges, enabling seamless lake‑warehouse integration and real‑time analytics.

Apache IcebergData LakeMetadata Caching

0 likes · 19 min read

StarRocks

May 14, 2024 · Artificial Intelligence

How Tencent Games Boosted AI‑Generated SQL Accuracy to 89% with a Lakehouse Architecture

Tencent Games tackled the low accuracy of AI‑generated SQL in production by combining large language models with a StarRocks lake‑warehouse, introducing a semantic layer, async materialized views, and an agent‑based multi‑intelligence framework, ultimately raising one‑shot SQL correctness to 89% and cutting delivery time from 2 hours to 0.33 hours.

AIData engineeringLLM

0 likes · 13 min read

How Tencent Games Boosted AI‑Generated SQL Accuracy to 89% with a Lakehouse Architecture

StarRocks

Apr 25, 2024 · Big Data

How StarRocks Beats Trino: 4.3× Faster Queries on Apache Paimon Lakehouse

This article explains how to build a high‑performance data‑lake analytics stack by combining StarRocks with Apache Paimon, covering direct queries, Data Cache acceleration, and asynchronous materialized views, and presents benchmark results that show StarRocks achieving up to 4.3× faster query speeds than Trino and significant latency reductions with caching and materialized views.

Apache PaimonData CacheData Lake

0 likes · 12 min read

StarRocks

Apr 25, 2024 · Artificial Intelligence

How AI Boosts SQL Accuracy and Performance: Real‑World Demo & AutoMV Insights

The April 16 online meetup by Tencent Game Data and StarRocks explored AI‑generated SQL, tackled NL2SQL challenges, showcased a demo that lifted one‑shot accuracy to 89%, and introduced StarRocks AutoMV technology that automates materialized‑view recommendation and merging to accelerate data‑warehouse queries.

AIAutoMVNL2SQL

0 likes · 9 min read

How AI Boosts SQL Accuracy and Performance: Real‑World Demo & AutoMV Insights

StarRocks

Apr 18, 2024 · Databases

Master StarRocks Deployment and Optimization: From Capacity Planning to Query Tuning

This comprehensive guide walks you through StarRocks production deployment, covering capacity planning, hardware specs, environment setup, table modeling, partitioning, bucketing, index selection, data import best practices, query optimization, monitoring, and resource‑group configuration, all backed by concrete SQL examples and configuration commands.

StarRocksdeploymentmodeling

0 likes · 20 min read

Master StarRocks Deployment and Optimization: From Capacity Planning to Query Tuning