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In the latest performance tests:
GreptimeDB’s write throughput is more than 2x that of InfluxDB, and its query speed in complex query scenarios can reach up to 11x that of InfluxDB.
GreptimeDB’s Log Engine rivals or even outperforms ClickHouse and Elasticsearch in terms of write performance, resource usage, and compression efficiency.
In edge scenarios, GreptimeDB’s data compression ratio is 19x that of SQLite, with write performance being 1.7x higher.
In comparison tests with Grafana Mimir, GreptimeDB demonstrated the ability to support 100 nodes in a single cluster, highlighting its horizontal scalability.
This article provides a brief review and summary based on these performance reports.
1. GreptimeDB vs. InfluxDB
Test Content: Large-scale data ingestion and querying
Results: GreptimeDB significantly outperforms InfluxDB in write throughput, especially in storage environments based on EBS and S3, where GreptimeDB reaches write performance of 234,000 rows/second and 231,000 rows/second, respectively, compared to InfluxDB's lower 109,000 rows/second. Additionally, in most complex query scenarios, GreptimeDB’s query speed is up to 11x faster than InfluxDB. For datasets exceeding 1 billion rows, GreptimeDB’s distributed version demonstrates excellent horizontal and vertical scalability, whereas the open-source version of InfluxDB struggles with such volumes.
Detailed Report: GreptimeDB vs. InfluxDB Performance Benchmark
2. GreptimeDB vs. ClickHouse vs. Elasticsearch
Test Content: Write and query performance of log data (including multi-column text and single-column full-text index scenarios with comparisons of write rates, resource consumption, and query performance).
Results: GreptimeDB shows significant advantages in write performance and resource utilization, particularly in complex multi-table query scenarios where its response time is noticeably faster than Elasticsearch. Additionally, GreptimeDB excels in data compression and storage efficiency, reducing storage costs while maintaining high performance.
Detailed Report: GreptimeDB vs. ClickHouse vs. Elasticsearch — Log Engine Performance Benchmark
3. GreptimeDB vs. SQLite
Test Content: Write, query, and resource consumption in embedded and edge scenarios
Results: GreptimeDB significantly outperforms SQLite in handling complex queries, particularly in scenarios involving large-scale data ingestion and real-time analysis. GreptimeDB Edge’s write performance is 1.7x that of SQLite, and its data compression ratio is 19x higher. Although GreptimeDB consumes more memory, its CPU consumption is lower, and users can flexibly adjust the balance between CPU, memory, and compression rate through configuration. In comparison, SQLite performs adequately in lightweight applications but falls short in large-scale data processing and complex queries.
Detailed Report: GreptimeDB vs. SQLite - A Performance Comparison Report on the Qualcomm 8155 Platform
4. GreptimeDB vs. Grafana Mimir
Test Content: Performance comparison between GreptimeDB and Grafana Mimir.
Results: The test validated GreptimeDB’s architecture’s scalability under ultra-large-scale clusters, with lower resource consumption under the same data scale. When compared to Grafana Mimir, which also uses object storage, GreptimeDB requires more than 5x less CPU and memory resources for processing equivalent data scales.
Detailed Report: GreptimeDB vs. Grafana Mimir - First Official Benchmark for High Volume Write In Performance
Conclusion
The benchmark results clearly highlight GreptimeDB’s exceptional performance and flexibility across diverse application scenarios. From large-scale data ingestion to complex queries and edge or embedded environments, GreptimeDB consistently stands out as a robust and competitive choice.
These tests not only validate our technical capabilities but also underscore GreptimeDB's ability to deliver tangible value to users. We are confident that this performance evaluation will assist you in making an informed decision when choosing the right database solution for your needs.
Ready to experience the power of GreptimeDB firsthand? Visit our GitHub page to download and try it today. For any questions, feel free to request a demo here.
About Greptime
We help industries that generate large amounts of time-series data, such as Connected Vehicles (CV), IoT, and Observability, to efficiently uncover the hidden value of data in real-time.
Visit the latest version from any device to get started and get the most out of your data.
- GreptimeDB, written in Rust, is a distributed, open-source, time-series database designed for scalability, efficiency, and powerful analytics.
- Edge-Cloud Integrated TSDB is designed for the unique demands of edge storage and compute in IoT. It tackles the exponential growth of edge data by integrating a multimodal edge-side database with cloud-based GreptimeDB Enterprise. This combination reduces traffic, computing, and storage costs while enhancing data timeliness and business insights.
- GreptimeCloud is a fully-managed cloud database-as-a-service (DBaaS) solution built on GreptimeDB. It efficiently supports applications in fields such as observability, IoT, and finance.
Star us on GitHub or join GreptimeDB Community on Slack to get connected. Also, you can go to our contribution page to find some interesting issues to start with.
