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ClickHouse

PublishedLast updated

ClickHouse is a fast, open-source columnar database that runs analytical queries on billions of scraped records in milliseconds.

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Reviewed profile

Quick verdict

ClickHouse fits teams analyzing large scraped datasets with fast SQL analytics. It is not a crawler, browser automation tool, extraction API, or proxy layer.

Best for
  • Large scraped data analytics
  • Real-time crawl dashboards
  • Open-source SQL infrastructure
  • Columnar storage at scale
Not ideal for
  • Turnkey scraping APIs
  • Small page archives
  • Browser automation workflows
Last verified
Jun 26, 2026

Key facts

  • RepoC++ project, Apache-2.0 licenseGitHub
  • Popularity45,405 GitHub stars, 8,004 forksGitHub
  • Python package10,454,274 monthly PyPI downloads for clickhouse-connectPyPI
  • JS package4,490,864 monthly npm downloads for @clickhouse/clientnpm
  • SDKsPython, JavaScript, Go, Java, Rust, and C# clientsProject docs

Compiled from public repository, docs, and package registry data; check ClickHouse for current details.

Sources

github.com

Verified against the ClickHouse/ClickHouse repository and the PyPI package.

ClickHouse is a fast, open-source columnar database built for real-time analytics at petabyte scale.

Key Features:

  • Millisecond Queries - Analyze billions of rows with sub-second response times using vectorized execution.
  • Column-Oriented Storage - Compress and query only the columns you need for maximum efficiency.
  • SQL Interface - Use standard SQL to explore scraped datasets without learning new query languages.
  • Real-Time Ingestion - Stream scraped data directly into tables and query it immediately.
  • Horizontal Scaling - Distribute data across nodes for linear performance scaling.

Whether you're analyzing crawl metrics, building real-time dashboards, or aggregating scraped e-commerce data, ClickHouse delivers the speed and scale your analytics demand.

Features:
Real-Time StreamingOpen SourceMulti-Language SDKsColumnar StorageSQL InterfaceHorizontal Scaling

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