ClickHouse

Unternehmensdaten

Offizieller Name

ClickHouse, Inc.

Einheitentyp

COMPANY

Gegründet

2021

Hauptsitz

United States

Unternehmensgröße

201–500

Marktrolle

B2B SaaS Provider

Offizielle Website

clickhouse.com

Was ClickHouse macht

ClickHouse uses an open-core B2B SaaS model. It creates value by offering an open-source OLAP database for developer adoption and then monetising that adoption through managed cloud infrastructure, customer-managed cloud deployments, data ingestion services, managed Postgres and observability products. The company reduces deployment complexity, improves performance for real-time analytics and expands wallet share by adding adjacent data infrastructure capabilities.

Strategische Einordnung

KI-gestützte Einordnung aus der bestehenden Unternehmensrecherche; Interpretation und belegte Fakten sind zu unterscheiden.

ClickHouse is a private US-based B2B software company that commercialises a high-performance open-source analytical database and a managed cloud service for real-time analytics. Its core business is selling managed data infrastructure to engineering, data and platform teams that need sub-second analytical querying, high concurrency and lower operational overhead than self-managed deployments. The company also offers related products for ingestion, managed Postgres, embedded analytics and observability. Its revenue model is centred on ClickHouse Cloud and related managed services, with usage-based and subscription-style commercial mechanics tied to compute, storage and managed operations. The open-source database acts as the adoption engine, helping the company acquire developers and technical teams before converting them into paid cloud, enterprise and managed observability customers.

Geschäftsmodell und Monetarisierung

ClickHouse primarily monetises via usage-based SaaS and managed infrastructure fees. Customers pay for ClickHouse Cloud based on compute, storage and related cloud consumption, supported by free trials and credits for conversion. Additional revenue comes from managed deployments in customer-owned cloud accounts, managed observability services, and managed database offerings such as Postgres. The open-source core supports product-led adoption and lowers customer acquisition costs for paid commercial tiers.

ClickHouse Cloud

Usage-based managed cloud data warehouse pricing across compute and storage

Bring Your Own Cloud

Managed service subscription for deployments in customer cloud accounts

Managed ClickStack observability

Managed observability SaaS

Managed Postgres

Subscription or managed database service fees

Open-source engine

Indirect conversion funnel into paid managed offerings

Produkte und Fähigkeiten

Für diese Ansicht liegen keine Produkte mit zugeordneten Quellen vor.

Produkte und Marktkategorien

Wettbewerber und Alternativen

• Supabase

  Open-source Postgres backend platform for application developers.

Tochtergesellschaften und Akquisitionen

• Langfuse

  Open-source platform for production LLM observability and evaluation.

Zuletzt erfasste Signale

Datumsangaben beziehen sich auf die Quellenveröffentlichung. Ältere Einträge sind historischer Kontext, kein Beleg für ein neues Ereignis.

• Introducing ClickHouse's new TimeSeries Engine: Your drop-In Prometheus replacement

  2026-09-15clickhouse.com

  Erfasster Impact-Score: 4/5

  ClickHouse PromQL support lets you store Prometheus metrics in ClickHouse Cloud, query them using familiar PromQL, and bring metrics together with your logs and traces without rewriting queries in SQL.

• High-Performance ETL for Apple Health XML Exports

  2026-08-31dev.to

  Infrastructure · Erfasster Impact-Score: 2/5

  This technical tutorial describes building a high-concurrency ETL engine to process very large Apple Health XML exports. The author outlines a performance-first architecture: a streaming Rust XML parser (quick-xml) to extract <Record> tags, export data as Apache Arrow record batches via PyO3 for zero-copy consumption in Python/Polars, and bulk-ingest cleaned data into ClickHouse using clickhouse-connect. The post includes code snippets for the Rust parser, Arrow-to-Polars bridge, ClickHouse table schema and bulk insert, and discusses production considerations such as parallelization, schema evolution, malformed XML handling, Grafana visualization, and feeding Arrow buffers into ML frameworks like PyTorch.

  • Apple Health exports a single massive XML file containing millions of <Record> tags.
  • The pipeline uses a streaming Rust parser (quick-xml) to avoid loading the entire XML into memory.

• NeverBlink Adds ClickHouse Support

  2026-08-26martechseries.com

  Infrastructure · Erfasster Impact-Score: 3/5

  NeverBlink, an AI-driven database administrator, announced support for ClickHouse, extending its database resilience and optimization platform to ClickHouse clusters. The integration offers continuous health checks, automated root-cause analysis, query analytics, prioritized remediation guidance, and optional unlimited expert consulting via BigData Boutique. NeverBlink already supports Elasticsearch and OpenSearch and is used in production by companies including Akamai, Perforce, and Palo Alto Networks. The article notes ClickHouse has surpassed 4,000 customers and a reported $15 billion valuation. Leadership quotes emphasize reducing downtime, lowering costs, and accelerating database optimization in the AI era.

  • NeverBlink announced support for ClickHouse, extending its AI-native database resilience and optimization platform to ClickHouse clusters.
  • NeverBlink is described as the world’s first AI database administrator (DBA) and already supports Elasticsearch and OpenSearch.

• Deploying SigNoz with ClickHouse v25 and OTel Gotchas

  2026-08-19dev.to

  Application Performance Monitoring · Erfasster Impact-Score: 1/5

  A developer describes troubleshooting and deployment patterns for self-hosting SigNoz in 2026, focusing on ClickHouse v25 configuration changes, OpenTelemetry Collector incompatibilities, and Docker network isolation. Key recommendations include using config.d/users.d for ClickHouse overrides (instead of replacing the main config), enforcing a deterministic docker-compose boot sequence with one-shot migrator containers (signoz_init_clickhouse and signoz_telemetrystore_migrator), updating exporter names and image tags for the OTel collector (use signozclickhousemetrics and include the 'v' prefix), and relying on internal Docker network isolation rather than per-component passwords to simplify connectivity. The post emphasizes that maintaining self-hosted observability infrastructure requires ongoing engineering effort.

  • Author self-hosted SigNoz for Verne Software to control telemetry data.
  • ClickHouse v25+ changes require using config.d/ and users.d/ for overrides instead of replacing the main config file.

• Picnic builds AI control room for automated fulfilment

  2026-08-12retail-news.de

  Logistics & Retail Systems · Erfasster Impact-Score: 3/5

  Picnic, the online grocery retailer, is developing an "Intelligent Control Room" to manage its highly automated fulfilment centres using AI, real-time data and automated action recommendations. The system aggregates data from microservices and warehouse systems and evaluates operational events using SQL queries, dbt models and ClickHouse. Controllers will receive prioritized, clickable recommendations and Picnic will collect accept/reject feedback to improve and potentially automate frequent routines. Longer-term plans include predictive models, digital twins for virtual simulations and the eventual use of reinforcement learning to optimise warehouse control strategies. Picnic emphasises a human-in-the-loop approach: employees remain the final decision-makers while AI reduces routine cognitive load.

  • Picnic is developing an "Intelligent Control Room" for its automated fulfilment centres.
  • The system uses AI and real-time data to generate prioritized, actionable recommendations that controllers can accept or reject.

Unternehmensbeziehungen vertiefen

• Wettbewerber und Alternativen
• Partner und Integrationen
• Tochtergesellschaften und Akquisitionen
• Akquisitionshistorie
• Eigentumsverhältnisse
• Ähnliche Unternehmen

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