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StarRocks Documentation

StarRocks is an open-source, high-performance OLAP database for real-time analytics at scale. It supports Standard SQL, materialized views, data lakes (Iceberg, Delta Lake, Hudi), stream ingestion (Kafka, Flink), and cloud-native deployment. This documentation covers SQL reference, table design, data loading, query acceleration, administration, and release notes.

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For agents: Open-source StarRocks OLAP database docs: SQL reference, table design, data loading, query acceleration, administration and release notes.

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llms.txt: https://docs.starrocks.io/llms.txt
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# StarRocks Documentation

> StarRocks is an open-source, high-performance OLAP database for real-time analytics at scale. It supports Standard SQL, materialized views, data lakes (Iceberg, Delta Lake, Hudi), stream ingestion (Kafka, Flink), and cloud-native deployment. This documentation covers SQL reference, table design, data loading, query acceleration, administration, and release notes.

## Administration

- [Administration](https://docs.starrocks.io/docs/administration/llms.txt): section index of 70 documentation pages.

## Benchmarking

- [SSB Flat-table Benchmarking](https://docs.starrocks.io/docs/benchmarking/SSB_Benchmarking.md): SSB flat-table benchmark on 100 GB dataset: StarRocks is 1.87x faster than ClickHouse and 4.75x faster than Apache Druid across 13 queries.
- [TPC-DS test SQL](https://docs.starrocks.io/docs/benchmarking/tpc_ds_99_sql.md): Complete SQL text for all 99 TPC-DS benchmark queries used in StarRocks performance testing.
- [TPC-DS Benchmarking](https://docs.starrocks.io/docs/benchmarking/TPC_DS_Benchmark.md): TPC-DS benchmark on 1 TB dataset: StarRocks is 8.13x faster than Trino on OLAP tables and 6.93x faster on Iceberg Catalog queries (99 queries).
- [TPC-H Benchmark](https://docs.starrocks.io/docs/benchmarking/TPC-H_Benchmarking.md): TPC-H benchmark on 100 GB dataset: StarRocks native storage is 8.9x faster than Trino; StarRocks Hive external tables are 2x faster than Trino (22 queries).

## Best_practices

- [Best_practices](https://docs.starrocks.io/docs/llms.txt): section index of 18 documentation pages.

## Data_source

- [Data_source](https://docs.starrocks.io/docs/llms.txt): section index of 31 documentation pages.

## Deployment

- [Deployment](https://docs.starrocks.io/docs/llms.txt): section index of 15 documentation pages.

## Developers

- [Developers](https://docs.starrocks.io/docs/developers/llms.txt): section index of 15 documentation pages.

## Faq

- [Faq](https://docs.starrocks.io/docs/faq/llms.txt): section index of 20 documentation pages.

## Flink_connector

- [Releases of StarRocks Connector for Flink](https://docs.starrocks.io/releasenotes/flink_connector.md): Release notes and changelog for the StarRocks Connector for Apache Flink.

## Integrations

- [Integrations](https://docs.starrocks.io/docs/integrations/llms.txt): section index of 43 documentation pages.

## Introduction

- [Architecture](https://docs.starrocks.io/docs/introduction/Architecture.md): StarRocks has a simple architecture.
- [Database Features](https://docs.starrocks.io/docs/introduction/Features.md): StarRocks offers a rich set of features to deliver a blazing-fast, real-time analytics experience on data at scale.
- [Community Chat (via Slack)](https://docs.starrocks.io/docs/introduction/slack.md): How to join the StarRocks community chat on Slack.

## Kafka_connector

- [Releases of StarRocks Connector for Kafka](https://docs.starrocks.io/releasenotes/kafka_connector.md): Release notes and changelog for the StarRocks Conn
…

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