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 Azure Data Explorer and RRDtool so you can quickly see how they compare against each other.

The primary purpose of this article is to compare how Azure Data Explorer 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.

Azure Data Explorer vs RRDtool Breakdown


 
Database Model

Columnar database

Time series database

Architecture

ADX can be deployed in the Azure cloud as a managed service and is easily integrated with other Azure services and tools for seamless data processing and analytics.

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

License

Closed source

GNU GPLv2

Use Cases

Log and telemetry data analysis, real-time analytics, security and compliance analysis, IoT data processing

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

Scalability

Highly scalable with support for horizontal scaling, sharding, and partitioning

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

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Azure Data Explorer Overview

Azure Data Explorer is a cloud-based, fully managed, big data analytics platform offered as part of the Microsoft Azure platform. It was announced by Microsoft in 2018 and is available as a PaaS offering. Azure Data Explorer provides high-performance capabilities for ingesting and querying telemetry, logs, and time series data.

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.


Azure Data Explorer for Time Series Data

Azure Data Explorer is well-suited for handling time series data. Its high-performance capabilities and ability to ingest large volumes of data make it suitable for analyzing and querying time series data in near real-time. With its advanced query operators, such as calculated columns, searching and filtering on rows, group by-aggregates, and joins, Azure Data Explorer enables efficient analysis of time series data. Its scalable architecture and distributed nature ensure that it can handle the velocity and volume requirements of time series data effectively.

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.


Azure Data Explorer Key Concepts

  • Relational Data Model: Azure Data Explorer is a distributed database based on relational database management systems. It supports entities such as databases, tables, functions, and columns. Unlike traditional RDBMS, Azure Data Explorer does not enforce constraints like key uniqueness, primary keys, or foreign keys. Instead, the necessary relationships are established at query time.
  • Kusto Query Language (KQL): Azure Data Explorer uses KQL, a powerful and expressive query language, to enable users to explore and analyze their data with ease.
  • Extents: In Azure Data Explorer, data is organized into units called extents, which are immutable, compressed sets of records that can be efficiently stored and queried.

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.


Azure Data Explorer Architecture

Azure Data Explorer is built on a cloud-native, distributed architecture that supports both NoSQL and SQL-like querying capabilities. It is a columnar storage-based database that leverages compressed, immutable data extents for efficient storage and retrieval. The core components of Azure Data Explorer’s architecture include the Control Plane, Data Management, and Query Processing. The Control Plane is responsible for managing resources and metadata, while the Data Management component handles data ingestion and organization. Query Processing is responsible for executing queries and returning results to users.

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.

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Azure Data Explorer Features

High-performance data ingestion

Azure Data Explorer can ingest data at a rate of 200 MB per second per node, offering fast and efficient data ingestion capabilities.

Data visualization

Azure Data Explorer integrates seamlessly with popular data visualization tools like Power BI, Grafana, and Jupyter Notebooks, allowing users to easily visualize and analyze their data.

Advanced analytics

The Kusto Query Language (KQL) supports advanced analytics features such as time series analysis, pattern recognition, and anomaly detection, enabling users to gain deeper insights from their data.

Flexible schema

Unlike traditional relational databases, Azure Data Explorer does not enforce constraints like key uniqueness, primary keys, or foreign keys. This flexibility allows for dynamic schema changes and the ability to handle semi-structured and unstructured data.

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.


Azure Data Explorer Use Cases

Log analytics

Azure Data Explorer is commonly used for log analytics, where it can ingest, store, and analyze large volumes of log data generated by applications, servers, and infrastructure. Organizations can use Azure Data Explorer to monitor application performance, troubleshoot issues, detect anomalies, and gain insights into user behavior. The ability to analyze log data in near real-time enables proactive issue resolution and improved operational efficiency.

Telemetry analytics

Azure Data Explorer is well-suited for telemetry analytics, where it can process and analyze data generated by IoT devices, sensors, and applications. Organizations can use Azure Data Explorer to monitor device health, optimize resource utilization, and detect anomalies in telemetry data. The platform’s scalability and high-performance capabilities make it ideal for handling the large volumes of data generated by IoT devices.

Time series analysis

Azure Data Explorer is used for time series analysis, where it can ingest and analyze time-stamped data points collected over time. This use case is applicable in various industries, including finance, healthcare, manufacturing, and energy. Organizations can use Azure Data Explorer to analyze trends, detect patterns, and forecast future events based on historical time series data. The platform’s advanced query operators and real-time analysis capabilities enable organizations to derive valuable insights from time series data.

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.


Azure Data Explorer Pricing Model

Azure Data Explorer’s pricing model is based on a pay-as-you-go approach, where customers are billed based on their usage of the service. The pricing is determined by factors such as the amount of data ingested, the amount of data stored, and the number of queries executed. Additionally, customers can choose between different pricing tiers that offer varying levels of performance and features. Azure Data Explorer also provides options for reserved capacity, which allows customers to reserve resources for a fixed period of time at a discounted rate.

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.