Benchmarking InfluxDB vs Cassandra - InfluxDB outperforms Cassandra by 4.5x
In this technical paper, we’ll compare the performance and features of InfluxDB v1.7.2 and Cassandra 3.11.3 for common time series workloads, specifically looking at the rates of data ingestion, on-disk data compression, and query performance. This data should prove valuable to developers and architects evaluating the suitability of these technologies for their use case.
InfluxDB is an open-source time series database written in Go. At its core is a custom-built storage engine called the Time-Structured Merge (TSM) Tree, which is optimized for time series data. Controlled by a custom SQL-like query language named InfluxQL, InfluxDB provides out-of-the-box support for mathematical and statistical functions across time ranges and is perfect for custom monitoring and metrics collection, real-time analytics, plus IoT and sensor data workloads.
Cassandra is a distributed, non-relational database written in Java, originally built at Facebook and open-sourced in 2008. It officially became part of the Apache Foundation in 2010. It is a general-purpose platform that provides a partitioned row store, which offers features of both key-value and column-oriented data stores.
Our goal with this benchmarking test was to create a consistent, up-to-date comparison that reflects the latest developments in both InfluxDB and Cassandra. Periodically, we’ll re-run these benchmarks and update this document with our findings. All of the code for these benchmarks are available on GitHub. Feel free to open up issues or pull requests on that repository or if you have any questions, comments, or suggestions.