Apache Doris vs RRDtool

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 Doris and RRDtool so you can quickly see how they compare against each other.

The primary purpose of this article is to compare how Apache Doris 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 Doris Overview

Apache Doris is an MPP-based interactive SQL data warehousing system designed for reporting and analysis. It is known for its high performance, real-time analytics capabilities, and ease of use. Apache Doris integrates technologies from Google Mesa and Apache Impala. Unlike other SQL-on-Hadoop systems, Doris is designed to be a simple and tightly coupled system that does not rely on external dependencies. It aims to provide a streamlined and efficient solution for data warehousing and analytics.

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 Doris for Time Series Data

Apache Doris can be effectively used with time series data for real-time analytics and reporting. With its high performance and sub-second response time, Doris can handle massive amounts of time-stamped data and provide timely query results. It supports both high-concurrent point query scenarios and high-throughput complex analysis scenarios, making it suitable for analyzing time series data with varying levels of complexity.

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 Doris Key Concepts

• MPP (Massively Parallel Processing): Apache Doris leverages MPP architecture, which allows it to distribute data processing across multiple nodes, enabling parallel execution and scalability.
• SQL: Apache Doris supports SQL as the query language, providing a familiar and powerful interface for data analysis and reporting.
• Point Query: Point query refers to retrieving a specific data point or a small subset of data from the database.
• Complex Analysis: Apache Doris can handle complex analysis scenarios that involve processing large volumes of data and performing advanced computations and aggregations.

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 Doris Architecture

Apache Doris is based on MPP architecture, which enables it to distribute data and processing across multiple nodes for parallel execution. It is a standalone system and does not depend on other systems or frameworks. Apache Doris combines the technology of Google Mesa and Apache Impala to provide a simple and tightly coupled system for data warehousing and analytics. It leverages SQL as the query language and supports efficient data processing and query optimization techniques to ensure high performance and scalability.

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.