Open Source High-Performance Data Warehouse delivering Sub-Second Analytics for End Users and Agents at Scale.
StarRocks is a high-performance analytical database designed for real-time analytics, supporting both real-time and lakehouse querying. Its architecture enables sub-second latency for complex, multi-table queries at scale without requiring data denormalization or copying. Built on open formats and standards, StarRocks allows direct analytics on data residing in data lakes. It excels in serving AI agents with low latency and high concurrency, even with unoptimized SQL. Key use cases include real-time risk engineering (as demonstrated by DiDi), faster analytics at Pinterest, and query performance optimization at Shopee. The system provides a unified OLAP solution covering various data analytics scenarios and can handle second-level data updates and deletes without impacting query performance.
StarRocks is a high-performance analytical database designed for real-time analytics, supporting both real-time and lakehouse querying.
Explore all tools that specialize in real-time analytics. This domain focus ensures StarRocks delivers optimized results for this specific requirement.
Enables continuous data ingestion from sources like Apache Kafka, allowing for up-to-the-second analytics.
Leverages a massively parallel processing (MPP) architecture to distribute queries across multiple nodes.
Automatically optimizes query execution plans based on data statistics and system resources.
Pre-computes and stores the results of complex queries, reducing the need for repeated calculations.
Directly queries data stored in data lakes (e.g., AWS S3, Apache HDFS) without data movement or transformation.
Download the StarRocks distribution.
Configure the cluster with the necessary resources.
Define schemas for your data sources.
Load data from your data lake or real-time streams.
Optimize query performance with indexing and partitioning.
Integrate with BI tools like Tableau or Superset.
All Set
Ready to go
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