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 MySQL so you can quickly see how they compare against each other.

The primary purpose of this article is to compare how Apache Doris and MySQL 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 vs MySQL Breakdown


 
Database Model

Data warehouse

Relational database

Architecture

Doris can be deployed on-premises or in the cloud and is compatible with various data formats such as Parquet, ORC, and JSON.

MySQL uses a client-server model with a multi-layered server design. It supports the SQL query language and offers various storage engines, such as InnoDB and MyISAM, for different use cases. MySQL can be deployed on-premises, in the cloud, or as a managed service.

License

Apache 2.0

GNU General Public License v2 (for the open-source Community Edition)

Use Cases

Interactive analytics, data warehousing, real-time data analysis, reporting, dashboarding

Web applications, e-commerce, data warehousing, content management systems, business applications

Scalability

Horizontally scalable with distributed storage and compute

Supports vertical scaling by adding more resources to a single node; horizontal scaling can be achieved through replication, sharding, and third-party tools

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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.

MySQL Overview

MySQL is an open source relational database management system that was first released in 1995. It is one of the most popular databases worldwide due to its ease of use, reliability, and performance. MySQL is widely used for web applications, online transaction processing, and data warehousing. Oracle Corporation acquired MySQL in 2010, but it remains open source software with an active community of contributors.


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.

MySQL for Time Series Data

MySQL can be used for storing and analyzing time series data, but it will not be as efficient as a dedicated time series databases. MySQL’s flexibility and support for various indexing techniques can make it a suitable choice for small to medium sized time series datasets. For large-scale time series data workloads, with high write throughput or use cases where low latency queries are required, MySQL will tend to struggle unless highly customized.


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.

MySQL Key Concepts

  • Table: A collection of related data organized in rows and columns, which is the primary structure for storing data in MySQL.
  • Primary Key: A unique identifier for each row in a table, used to enforce data integrity and enable efficient querying.
  • Foreign Key: A column or set of columns in a table that refers to the primary key in another table, used to establish relationships between tables.


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.

MySQL Architecture

MySQL is a relational database management system that uses SQL for defining and manipulating data. It follows the client-server model, where a MySQL server accepts connections from multiple clients and processes their queries. MySQL’s architecture includes a storage engine framework that allows users to choose from different storage engines, such as InnoDB, MyISAM, or Memory, to optimize the database for specific use cases.

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Apache Doris Features

High Performance

Apache Doris is designed for high-performance data analytics, delivering sub-second query response times even with massive amounts of data.

Real-Time Analytics

Apache Doris enables real-time data analysis, allowing users to gain insights and make informed decisions based on up-to-date information.

Scalability

Apache Doris can scale horizontally by adding more nodes to the cluster, allowing for increased data storage and processing capacity.

MySQL Features

ACID compliance

MySQL supports transactions and adheres to the ACID (Atomicity, Consistency, Isolation, Durability) properties, ensuring data integrity and consistency.

Scalability

MySQL can scale both vertically and horizontally, depending on the storage engine and configuration.

Replication and high availability

MySQL supports various replication techniques, including master-slave and master-master replication, to provide high availability and fault tolerance.


Apache Doris Use Cases

Real-Time Analytics

Apache Doris is well-suited for real-time analytics scenarios where timely insights and analysis of large volumes of data are crucial. It enables businesses to monitor and analyze real-time data streams, make data-driven decisions, and detect patterns or anomalies in real time.

Reporting and Business Intelligence

Apache Doris can be used for generating reports and conducting business intelligence activities. It supports fast and efficient querying of data, allowing users to extract meaningful insights and visualize data for reporting and analysis purposes.

Data Warehousing

Apache Doris is suitable for building data warehousing solutions that require high-performance analytics and querying capabilities. It provides a scalable and efficient platform for storing, managing, and analyzing large volumes of data for reporting and decision-making.

MySQL Use Cases

Web applications

MySQL is a popular choice for powering web applications, content management systems, and e-commerce platforms due to its flexibility, ease of use, and performance.

Online transaction processing (OLTP)

MySQL is suitable for OLTP systems that require high concurrency, fast response times, and support for transactions.

Data warehousing

While not specifically designed for data warehousing, MySQL can be used for small to medium-sized data warehouses, leveraging its support for indexing, partitioning, and other optimization techniques.


Apache Doris Pricing Model

As an open-source project, Apache Doris is freely available for usage and does not require any licensing fees. Users can download the source code and set up Apache Doris on their own infrastructure without incurring any direct costs. However, it’s important to consider the operational costs associated with hosting and maintaining the database infrastructure.

MySQL Pricing Model

MySQL is available in multiple editions with different feature sets and pricing models. The MySQL Community Edition is open source and free to use, while the MySQL Enterprise Edition includes additional features, such as advanced security, monitoring, and management tools, and requires a subscription. Pricing for the Enterprise Edition depends on the number of server instances and the level of support required.