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TL;DR - ClickHouse
- ClickHouse is a column-oriented database for real-time analytics on massive datasets
- It delivers sub-second query performance on billions of rows for OLAP workloads
- Free and open-source, with ClickHouse Cloud from $0.30/hour
Pricing: Paid only
Best for: Enterprises & pros
Score: 90/100
Pros & Cons
Pros
- Extremely fast analytics
- Good compression
- SQL interface
- Column-oriented
- Open source
Cons
- Not for OLTP
- Updates expensive
- Operations complex
- Learning curve
- Specific use cases
Key Features
Analytics databaseColumnarFast queriesSQLReal-timeOpen source
Pricing Plans
Free TrialBasic
Usage-based pricing
- 1 replica
- 8 GiB RAM
- 2 vCPU
- Pay-as-you-go compute
Most Popular
Scale
Production workloads
- Multiple replicas
- Independent scaling
- Advanced features
Enterprise
High compliance needs
- Custom SLA
- Disaster recovery
- Hardware control
About ClickHouse
By Toolradar Team·
ClickHouse processes analytical queries at speeds that seem impossible. Billions of rows in seconds, columnar storage optimized for aggregations, and SQL syntax that feels familiar even for complex analytics.
The open-source version is production-ready. Compression ratios keep storage costs low. The query optimizer handles analytical workloads brilliantly.
Data teams with big analytical workloads choose ClickHouse when query performance is more important than transaction support.
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ClickHouse FAQ
Is ClickHouse free?
Yes, ClickHouse is open source under Apache 2.0. Self-host for free. ClickHouse Cloud is the managed service with usage-based pricing.
What is ClickHouse?
ClickHouse is a column-oriented database for OLAP. Extremely fast analytical queries. Used by Cloudflare, GitLab, and many others for analytics.
ClickHouse vs PostgreSQL?
ClickHouse is for analytics queries on large datasets. PostgreSQL is general-purpose. ClickHouse 100x+ faster for analytics; PostgreSQL for transactional workloads.
What is ClickHouse used for?
Real-time analytics, log analysis, time-series data, and business intelligence. Queries billions of rows in milliseconds.
Source: clickhouse.com