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About ClickHouse
ClickHouse is an open-source, columnar database management system (DBMS) designed for online analytical processing (OLAP) of large volumes of data. ClickHouse is optimized for high-performance queries on very large datasets. It is particularly well-suited for offline data analytics, business intelligence, and log/event analysis due to its ability to handle massive amounts of data quickly and efficiently.
Click here to read the full report of GreptimeDB vs. ClickHouse in log scenarios.
Click here to read the full report of GreptimeDB vs. ClickHouse in log scenarios.
GreptimeDB vs. ClickHouse
| Feature/Aspect | GreptimeDB​ | ClickHouse​ |
|---|---|---|
| Data Model​ | Observability Database​ | Columnar-based data warehouse ​ |
| Value model​ | Multi-Value​ | Multi-Value​ |
| Multi-model​ | Metrics​, Logs & Traces​ | Yes​​ |
| Ingestion Protocols​ ​ | SQL​ gRPC​ InfluxDB Line Protocol​ Prometheus Remote Storage​ OpenTelemetry​ | SQL​ Supports many integrations​ ​ |
| Query Languages​ | SQL & PromQL​ | SQL​ |
| Continuous Aggregation​ | Yes (in SQL)​ | Yes (Materialized View in SQL)​ |
| Use cases​ | Monitoring, observability, IoT data analysis, real-time analytics​ | Real-time analytics, big data processing, event logging, monitoring, IoT, data warehousing​ |
| Architecture​ ​ | Cloud-native and flexible architecture, scaled from edge to cloud.​ | True column-oriented DBMS. Data is stored by columns, and during the execution of arrays (vectors or chunks of columns). Deployed as an on-premise service in private or managed service in the cloud.​ |
| Storage Format​ | Apache Parquet​ | MergeTree Engine Family​ |
| License​ | Apache 2.0​ | Apache 2.0​ |
| Scalability​ | Opensource both single-node and cluster versions.​ By leveraging Object Storage (S3, and others), separating compute and storage will lead to scaling stateless compute nodes arbitrarily.​ | Horizontally scalable with support for data sharding, replication, and distributed querying​ ​ |
| Written Language​ | Rust​ | C++​ |
