GreptimeDB vs. ClickHouse | Greptime

Join us for a virtual meetup on Zoom at 8 PM, July 31 (PDT) about using One Time Series Database for Both Metrics and Logs 👉🏻 Register Now

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.

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++

Join our community

Get the latest updates and discuss with other users.