Amazon Redshift
Fully managed, petabyte-scale cloud data warehouse for analytics and reporting
StarRocks
Sub-second ad-hoc analytics across data lakes and warehouses
StarRocks delivers sub‑second, ad‑hoc analytics on‑premise or directly on data lakehouse formats like Hive, Iceberg, Delta Lake and Hudi, with a vectorized SQL engine that’s 3× faster than alternatives.
Overview
Overview
StarRocks is a high‑performance, vectorized SQL engine designed for sub‑second, ad‑hoc analytics on both traditional data warehouses and modern lakehouse storage. It supports full ANSI‑SQL, the MySQL protocol, and a cost‑based optimizer that automatically generates efficient execution plans for complex multi‑dimensional queries. Real‑time upserts and intelligent materialized views keep data fresh while delivering fast query responses.
Deployment & Scalability
The system consists of Frontend and Backend nodes that scale horizontally without single points of failure. Starting with version 3.0, a shared‑data architecture further reduces cost and improves scalability. Deployment is straightforward on Linux environments using Docker or native binaries, and the engine can directly query external tables in Hive, Iceberg, Delta Lake, or Hudi without data movement. Resource management features enable tenant isolation and quota enforcement, making StarRocks suitable for cloud‑native, multi‑tenant analytics platforms.
Highlights
Native vectorized SQL engine for sub‑second query latency
Real‑time upsert/delete support with primary‑key tables
Direct querying of Hive, Iceberg, Delta Lake, and Hudi
Intelligent materialized views that auto‑refresh on data load
Pros
- Sub‑second query performance for multi‑dimensional analytics
- Full ANSI‑SQL compatibility and MySQL protocol support
- Horizontal scalability with no single point of failure
- Simple architecture that eases deployment and maintenance
Considerations
- Optimally runs on Linux/Unix environments only
- Advanced tuning may require deep expertise
- Limited native graphical UI compared to commercial tools
- Community support varies relative to large commercial vendors
Managed products teams compare with
When teams consider StarRocks, these hosted platforms usually appear on the same shortlist.
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Fit guide
Great for
- Interactive BI teams needing instant ad‑hoc query results
- Enterprises storing data in lakehouse formats seeking zero‑ETL analytics
- Real‑time dashboards that require frequent data updates
- Organizations looking for an open‑source, cost‑effective OLAP engine
Not ideal when
- Very small, low‑traffic workloads where heavyweight engine overhead is unnecessary
- Environments that require Windows‑only deployment
- Use cases demanding built‑in machine‑learning model serving inside the database
- Scenarios needing extensive native ETL pipelines beyond query capabilities
How teams use it
Business intelligence dashboards with sub‑second refresh
Analysts receive instant query results across multi‑dimensional data, enabling real‑time decision making.
Lakehouse analytics without data movement
Teams query Hive/Iceberg tables directly, eliminating ETL latency and storage duplication.
Real‑time inventory tracking
Upserts on primary‑key tables keep stock levels current while supporting concurrent analytical queries.
Automated reporting via materialized views
Materialized views refresh on data load, delivering pre‑aggregated results with no manual maintenance.
Tech snapshot
Java55%
C++42%
Python1%
C1%
Thrift1%
Shell1%
Frequently asked questions
Does StarRocks require data to be loaded into its own storage?
No. It can query data directly from external lakehouse formats such as Hive, Iceberg, Delta Lake, and Hudi.
What SQL dialect does StarRocks support?
StarRocks implements ANSI‑SQL and is compatible with the MySQL protocol, so most standard queries work out of the box.
How does StarRocks achieve sub‑second performance?
It uses a native vectorized execution engine and a cost‑based optimizer that fully exploits CPU parallelism.
Is StarRocks suitable for multi‑tenant environments?
Yes. Built‑in resource management lets you isolate workloads and enforce quotas per tenant.
What licensing governs StarRocks?
StarRocks is released under the Apache License 2.0.
Project at a glance
Active- Stars
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- Watchers
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- 2,269
LicenseApache-2.0
Repo age4 years old
Last commit13 hours ago
Primary languageJava
Last synced 12 hours ago