TSDB Comparison: Cassandra vs. TDengine

TDengine Team

With industries ranging from IoT to manufacturing generating and collecting a constantly increasing amount of time-series data, the growth of the time-series database (TSDB) market over the past five years has not come as a surprise. This popularity has resulted in a large number of time series DB solutions coming on the market, sometimes making it difficult to choose the best time series database for a certain business scenario. This article compares two databases that can be used for time-series data processing – Cassandra and TDengine – to help you determine which is right for your use case.

Apache Cassandra is an open-source NoSQL distributed database known for enabling fault tolerance on commodity hardware. Although Cassandra is an Apache Foundation project, a commercial version is also provided by DataStax. While Cassandra is not a time-series database, it does have some characteristics suited for time-series data processing and has been used in similar scenarios.

TDengine is an open-source time-series database that differentiates itself with high performance, a distributed cloud-native architecture, and built-in caching, data subscription, and stream processing that simplify the overall system design.

The following table compares the basic information of Cassandra vs. TDengine.

Initial release20082017
Main development languageJavaC
Main query languageCQL (proprietary)Standard SQL
Operating systemsLinux, macOS, and WindowsLinux, macOS, and Windows

The following table indicates specific features supported by Cassandra vs. TDengine.

SQL syntax
Private deployment
System connection management
Query task management
Data import
Data export
Web management
Multi-layer storage
Telegraf data collection
Grafana data visualization
C/C++ connector
JDBC support
Go connector
Python connector
Database configuration
Replica configuration
Data retention policy
Data partitioning
Stream processing
Data subscription
Microsecond precision
Limits and offsets