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StarRocks avatar

StarRocks/starrocks

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Starrocks

StarRocks is a distributed SQL OLAP database engine designed for real-time analytics and high-performance multi-dimensional analysis. It functions as a data lakehouse query engine that enables SQL execution across large datasets and external open table formats without requiring local data imports.

The system employs a shared-nothing distributed architecture and utilizes the MySQL protocol to integrate with business intelligence tools. It maintains real-time data consistency through a primary key upsert model and accelerates query response times using vectorized execution and cost-based optimization.

Broad capabilities include the use of automated materialized views to reduce scan volumes and multi-tenant resource isolation to manage CPU and memory quotas across concurrent workloads. The engine also supports automatic resource balancing and data recovery during cluster scaling.

Features

  • Real-Time Analytics - Provides a low-latency real-time analytics engine for processing streaming data and updating business dashboards.
  • Cloud Data Lake Integrations - Enables direct SQL access to data stored in open table formats within cloud-native data lakes.
  • Data Upsert Operations - Ensures real-time data consistency using a primary key upsert model to update records during ingestion.
  • Distributed SQL Databases - Implements a distributed SQL database architecture that scales horizontally while maintaining data availability.

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11,789 stars·2,450 forks·Java·Apache-2.0·39 views
Federated Data Query Engines - Functions as a federated query engine that accesses remote lakehouse storage formats without requiring local data imports.
  • Lakehouse Engines - Acts as an analytics engine capable of querying external data lakes and open table formats without local imports.
  • Multi-Dimensional Analysis - Performs complex aggregations and ad-hoc queries across large datasets using vectorized processing.
  • OLAP Database Engines - Provides a distributed database designed for high-performance multi-dimensional analytics and sub-second SQL queries.
  • Cost-Based Optimizers - Implements a cost-based optimizer that determines the most efficient execution plan using table statistics.
  • Real-time Data Synchronization - Synchronizes datasets in real-time using primary key upserts and deletes to keep analytics current.
  • Vectorized Execution Engines - Utilizes a vectorized execution engine with SIMD instructions to process data in batches for high analytical throughput.
  • Lakehouse Querying - Runs high-performance SQL queries directly on open table formats in a data lake without requiring file imports.
  • Shared-Nothing Processing Engines - Employs a shared-nothing distributed processing model where each node manages its own local storage and memory.
  • Business Intelligence Connectors - Bridges the high-speed engine with business intelligence platforms using standard MySQL protocols and ANSI SQL.
  • Materialized Views - Provides automated materialized views that pre-calculate result sets to accelerate query response times.
  • Materialized View Selectors - Implements a cost-based optimizer to automatically route queries to the most efficient pre-calculated materialized views.
  • Multi-Tenant Resource Isolation - Prevents query interference by allocating specific CPU and memory quotas to individual users or workloads within the cluster.
  • MySQL Compatibility - Uses the MySQL protocol to ensure compatibility with standard SQL clients and BI tools.
  • Scalable Database Clusters - Provides a scalable database cluster architecture that automatically balances resources during node scaling.
  • SQL Database Connectivity - Provides connectivity and compatibility with existing business intelligence tools and database clients via standard MySQL protocols.
  • Workload Isolation - Implements multi-tenant resource isolation to manage CPU and memory quotas across concurrent workloads.
  • Cluster Scaling Orchestrators - Automatically balances resources and recovers data replicas when adding or removing nodes from the cluster.

    • Star history

    Star history chart for starrocks/starrocksStar history chart for starrocks/starrocks

    How this analysis was created: This summary and feature list are AI-generated from collected project material and can contain mistakes. Stars, license and language are imported from GitHub. Inclusion does not mean that we have tested or audited this project. Check the source documentation for any feature you depend on. Learn more on our About page.

    Frequently asked questions

    What does starrocks/starrocks do?

    StarRocks is a distributed SQL OLAP database engine designed for real-time analytics and high-performance multi-dimensional analysis. It functions as a data lakehouse query engine that enables SQL execution across large datasets and external open table formats without requiring local data imports.

    What are the main features of starrocks/starrocks?

    The main features of starrocks/starrocks are: Real-Time Analytics, Cloud Data Lake Integrations, Data Upsert Operations, Distributed SQL Databases, Federated Data Query Engines, Lakehouse Engines, Multi-Dimensional Analysis, OLAP Database Engines.

    Which projects share features with starrocks/starrocks?

    Projects with overlapping indexed features include: apache/pinot — Pinot is a distributed, columnar analytical database designed for high-concurrency, low-latency query processing. It… prestodb/presto — Presto is a distributed SQL query engine designed for high-performance analytical processing across heterogeneous data… oceanbase/oceanbase — OceanBase is a distributed SQL database designed for high availability and strong consistency across multiple nodes… ydb-platform/ydb — YDB is a distributed SQL database and analytical engine designed for horizontal scalability and strong consistency. It… apache/doris — Doris is a distributed SQL data warehouse designed for high-performance analytical workloads and real-time data… risingwavelabs/risingwave — RisingWave is a cloud-native streaming database and real-time analytics engine that uses standard SQL to process…

    Projects sharing features with Starrocks

    These projects share indexed features with Starrocks. Shared tags can include platform or build tooling; verify the primary use case before treating a result as a replacement.
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      OceanBase is a distributed SQL database designed for high availability and strong consistency across multiple nodes and regions. It functions as a hybrid transactional and analytical processing engine, allowing real-time analytics and transactions to execute on a single data copy. The system also serves as a vector database engine for indexing and querying vector data to power semantic search and recommendation systems. The platform features native compatibility layers for MySQL and Oracle, enabling the migration of legacy workloads without rewriting SQL code. It utilizes a Paxos-based distri

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      YDB is a distributed SQL database and analytical engine designed for horizontal scalability and strong consistency. It functions as a multi-model system that supports transactional and analytical workloads through a distributed architecture providing serializable ACID transactions. The system is distinguished by its broad protocol compatibility, implementing the PostgreSQL wire protocol for standard SQL drivers and the Kafka protocol for messaging and streaming. It further serves as a vector database, supporting vector indexes and approximate nearest neighbor searches for semantic search and

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