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ClickHouse

High-performance columnar OLAP database system for real-time analytics on big data, with SQL support and linear scalability.

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Repository details:
  • Stars

    35,689
  • Forks

    6,661
  • Last commit

    8 hours ago
  • License

    Apache-2.0
Written in:
C (81%)
C++ (81%)
View Repository
Screenshot of ClickHouse website

ClickHouse is a powerful open-source columnar database management system designed for online analytical processing (OLAP) of big data. It offers unparalleled performance and efficiency, making it an ideal choice for businesses dealing with massive datasets and complex analytical queries.

Key benefits of ClickHouse include:

  • Exceptional Speed: Process billions of rows and terabytes of data in seconds, thanks to its columnar storage format and advanced query optimization techniques.
  • Linear Scalability: Easily scale horizontally across commodity hardware to handle growing data volumes without compromising performance.
  • SQL Support: Familiar SQL syntax with extensions for analytical queries, making it accessible to data analysts and engineers.
  • Real-time Data Ingestion: Insert and query data simultaneously, enabling real-time analytics on fresh data.
  • Compression: Highly efficient data compression reduces storage costs and improves query performance.
  • Fault Tolerance: Built-in replication and sharding capabilities ensure high availability and data reliability.
  • Versatility: Support for a wide range of data types, including arrays and nested structures, accommodating diverse analytical needs.
  • Integration: Seamless integration with popular data processing tools and ecosystems, enhancing its utility in modern data stacks.

ClickHouse empowers organizations to unlock insights from their data at unprecedented speeds, enabling data-driven decision-making and innovative analytical applications across industries.

Repository details:
  • Stars

    35,689
  • Forks

    6,661
  • Last commit

    8 hours ago
  • License

    Apache-2.0
Written in:
C (81%)
C++ (81%)
View Repository
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