ClickHouse vs CockroachDB
- ✦ Column-oriented storage
- ✦ Vectorized query execution
- ✦ Real-time ingestion
- ✦ Distributed SQL
- ✦ PostgreSQL Wire Protocol
- ✦ Multi-Region Replication
Real-World Scenarios: When to Choose Which
The question that matters: “In what situation will I regret choosing A over B after 3 months?”
Ingest clickstream events via Kafka, query 100B rows in under 1 second for live dashboards
Store and query server logs at petabyte scale with 10x better compression than Elasticsearch
Count unique users and calculate click-through rates across billions of ad impressions in milliseconds
Replace InfluxDB with ClickHouse for metrics storage, gaining SQL query support and better compression
CockroachDB's geo-partitioning pins rows to specific cloud regions by key prefix, ensuring GDPR-regulated customer data never leaves EU nodes without sacrificing SQL query capability.
CockroachDB's multi-zone deployment survives the loss of an entire availability zone automatically, with zero data loss and sub-30-second recovery versus minutes of manual failover for traditional primary/replica setups.
CockroachDB's online schema changes apply column additions and index builds while the database serves traffic, avoiding the maintenance windows that single-node SQL databases require for schema changes.
Pricing Intelligence
ClickHouse Plans
Free tier available
- • Self-hosted
- • Full features
- • Community support
- • $0.20/hr compute from
- • Free trial credits
- • Managed service
- • Dedicated resources
- • SLA
- • Enterprise support
CockroachDB Plans
Free tier available
- • 10 GiB storage
- • Shared cluster
- • PostgreSQL compatible
- • $0.20/hr
- • Dedicated cluster
- • Multi-region support
- • Custom deployment
- • SLA
- • HIPAA/FedRAMP
Feature Matrix
10 differences found across 18 standardized features
- •Column-oriented storage
- •Vectorized query execution
- •Real-time ingestion
- •Kafka integration
- •SQL support
- •Distributed tables
- •Compression (LZ4/ZSTD)
- •Approximate query functions
- •Materialized views
- •Replicated tables
- •JSON support
- •Geospatial functions
- •Time-series optimizations
- •REST and native protocols
- •Distributed SQL
- •PostgreSQL Wire Protocol
- •Multi-Region Replication
- •Serializable Isolation
- •Automatic Sharding
- •Geo-Partitioning
- •Follower Reads
- •Online Schema Changes
- •ACID Transactions
- •Backup to Cloud Storage
- •Change Data Capture
- •LDAP/SAML Auth
- •Row-Level TTL
- •Import/Export
- •Prometheus Monitoring
- •Kubernetes Operator
Pros & Cons Face-Off
Evaluative strengths and weaknesses: not feature lists
- +Fastest OLAP query performance for analytical queries at scale
- +Aggressive compression cuts storage costs 5-10x vs row-oriented DBs
- +Open source with full feature parity on self-hosted
- −Not designed for OLTP workloads or frequent row updates
- −Complex cluster configuration for self-hosted HA deployments
- +PostgreSQL compatibility minimizes migration effort
- +Survives node and zone failures automatically
- +Global multi-region with low-latency reads via follower reads
- +Free tier for development and small workloads
- −More expensive than single-node PostgreSQL for simple use cases
- −Distributed transaction overhead vs single-node performance
At a Glance
Frequently Asked Questions
Related Comparisons
Sources
- 1.ClickHouse Official Pricing–Vendor pricing page
- 2.CockroachDB Official Pricing–Vendor pricing page
- 3.ClickHouse Official Website–Official product website
- 4.CockroachDB Official Website–Official product website