Choosing the right database is a critical choice when building any software application. All databases have different strengths and weaknesses when it comes to performance, so deciding which database has the most benefits and the most minor downsides for your specific use case and data model is an important decision. Below you will find an overview of the key concepts, architecture, features, use cases, and pricing models of Apache Cassandra and RRDtool so you can quickly see how they compare against each other.

The primary purpose of this article is to compare how Apache Cassandra and RRDtool perform for workloads involving time series data, not for all possible use cases. Time series data typically presents a unique challenge in terms of database performance. This is due to the high volume of data being written and the query patterns to access that data. This article doesn’t intend to make the case for which database is better; it simply provides an overview of each database so you can make an informed decision.

Apache Cassandra vs RRDtool Breakdown


 
Database Model

Distributed wide-column database

Time series database

Architecture

Apache Cassandra follows a masterless, peer-to-peer architecture, where each node in the cluster is functionally the same and communicates with other nodes using a gossip protocol. Data is distributed across nodes in the cluster using consistent hashing, and Cassandra supports tunable consistency levels for read and write operations. It can be deployed on-premises, in the cloud, or as a managed service

RRDtool is a single-node, non-distributed database generally deployed on a single machine

License

Apache 2.0

GNU GPLv2

Use Cases

High write throughput applications, time series data, messaging systems, recommendation engines, IoT

Monitoring, observability, Network performance tracking, System metrics, Log data storage

Scalability

Horizontally scalable with support for data partitioning, replication, and linear scalability as nodes are added

Limited scalability- more suitable for small to medium-sized datasets

Apache Cassandra Overview

Apache Cassandra is a highly scalable, distributed, and decentralized NoSQL database designed to handle large amounts of data across many commodity servers. Originally created by Facebook, Cassandra is now an Apache Software Foundation project. Its primary focus is on providing high availability, fault tolerance, and linear scalability, making it a popular choice for applications with demanding workloads and low-latency requirements.

RRDtool Overview

RRDtool, short for Round-Robin Database Tool, is an open-source, high-performance data logging and graphing system designed to handle time series data. Created by Tobias Oetiker in 1999, RRDtool is specifically built for storing and visualizing time-series data, such as network bandwidth, temperatures, or CPU load. Its primary feature is the efficient storage of data points, using a fixed-size database that automatically aggregates and archives older data points, ensuring that the database size remains constant over time.


Apache Cassandra for Time Series Data

Cassandra can be used for handling time series data due to its distributed architecture and support for time-based partitioning. Time series data can be efficiently stored and retrieved using partition keys based on time ranges, ensuring quick access to data points.

RRDtool for Time Series Data

RRDtool was created for time series data storage and visualization, making it a great fit for applications that require efficient handling of this type of data. Its round-robin database structure ensures constant storage space usage while providing automatic data aggregation and archiving. However, RRDtool may not be suitable for applications that require complex queries or relational data storage, as its focus is primarily on time series data.


Apache Cassandra Key Concepts

  • Column Family: Similar to a table in a relational database, a column family is a collection of rows, each consisting of a key-value pair.
  • Partition Key: A unique identifier used to distribute data across multiple nodes in the cluster, ensuring even distribution and fast data retrieval.
  • Replication Factor: The number of copies of data stored across different nodes in the cluster to provide fault tolerance and high availability.
  • Consistency Level: A configurable parameter that determines the trade-off between read/write performance and data consistency across the cluster.

RRDtool Key Concepts

  • Round-robin database: A fixed-size database that stores time-series data using a circular buffer, overwriting older data as new data is added.
  • RRD file: A single file that contains all the configuration and data for an RRDtool database.
  • Consolidation function: A function that aggregates multiple data points into a single data point, such as AVERAGE, MIN, MAX, or LAST.


Apache Cassandra Architecture

Cassandra uses a masterless, peer-to-peer architecture, in which all nodes are equal, and there is no single point of failure. This design ensures high availability and fault tolerance. Cassandra’s data model is a hybrid between a key-value and column-oriented system, where data is partitioned across nodes based on partition keys and stored in column families. Cassandra supports tunable consistency, allowing users to adjust the balance between data consistency and performance based on their specific needs.

RRDtool Architecture

RRDtool is a specialized time series database that does not use SQL or a traditional relational data model. Instead, it employs a round-robin database structure, with data points stored in a fixed-size, circular buffer. RRDtool is a command-line tool that can be used to create and update RRD files, as well as generate graphs and reports from the stored data. It can be integrated with various scripting languages, such as Perl, Python, and Ruby, through available bindings.

Free Time-Series Database Guide

Get a comprehensive review of alternatives and critical requirements for selecting yours.

Apache Cassandra Features

Linear Scalability

Cassandra can scale horizontally, adding nodes to the cluster to accommodate growing workloads and maintain consistent performance.

High Availability

With no single point of failure and support for data replication, Cassandra ensures data is always accessible, even in the event of node failures.

Tunable Consistency

Users can balance between data consistency and performance by adjusting consistency levels based on their application’s requirements.

RRDtool Features

Efficient Data Storage

RRDtool’s round-robin database structure ensures constant storage space usage, automatically aggregating and archiving older data points.

Graphing

RRDtool provides powerful graphing capabilities, allowing users to generate customizable graphs and reports from the stored time series data.

Cross-Platform Support

RRDtool is available on various platforms, including Linux, Unix, macOS, and Windows.


Apache Cassandra Use Cases

Messaging and Social Media Platforms

Cassandra’s high availability and low-latency make it suitable for messaging and social media applications that require fast, consistent access to user data.

IoT and Distributed Systems

With its ability to handle large amounts of data across distributed nodes, Cassandra is an excellent choice for IoT applications and other distributed systems that generate massive data streams.

E-commerce

Cassandra is a good fit for E-commerce use cases because it has the ability to support things like real-time inventory status and it’s architecture also allows for reduced latency by allowing region specific data to be closer to users.

RRDtool Use Cases

Network Monitoring

RRDtool is often used in network monitoring applications to store and visualize metrics such as bandwidth usage, latency, and packet loss.

Environmental Monitoring

RRDtool can be used to track and visualize environmental data, such as temperature, humidity, and air pressure, over time.

System Performance Monitoring

RRDtool is suitable for storing and displaying system performance metrics, like CPU usage, memory consumption, and disk I/O, for server and infrastructure monitoring.


Apache Cassandra Pricing Model

Apache Cassandra is an open-source project, and there are no licensing fees associated with its use. However, costs can arise from hardware, hosting, and operational expenses when deploying a self-managed Cassandra cluster. Additionally, several managed Cassandra services, such as DataStax Astra and Amazon Keyspaces, offer different pricing models based on factors like data storage, request throughput, and support.

RRDtool Pricing Model

RRDtool is an open-source software, freely available for use under the GNU General Public License. Users can download, use, and modify the software at no cost. There are no commercial licensing options or paid support services offered directly by the project.

Get started with InfluxDB for free

InfluxDB Cloud is the fastest way to start storing and analyzing your time series data.