MariaDB vs StarRocks

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 MariaDB and StarRocks so you can quickly see how they compare against each other.

The primary purpose of this article is to compare how MariaDB and StarRocks 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.

MariaDB Overview

MariaDB is an open-source relational database management system (RDBMS) that was created as a fork of MySQL in 2009 by the original developers of MySQL, led by Michael Widenius. The primary goal of MariaDB was to provide an open-source and community-driven alternative to MySQL, which was acquired by Oracle Corporation in 2008. MariaDB is compatible with MySQL and has enhanced features, better performance, and improved security. It is widely used by organizations worldwide and is supported by the MariaDB Foundation, which ensures its continued open-source development.

StarRocks Overview

StarRocks is an open source high-performance analytical data warehouse that enables real-time, multi-dimensional, and highly concurrent data analysis. It features an MPP (Massively Parallel Processing) architecture and is equipped with a fully vectorized execution engine and a columnar storage engine that supports real-time updates.

MariaDB for Time Series Data

While MariaDB is not specifically designed for time series data, it can be used to store, process, and analyze time series data due to its flexible and extensible architecture. SQL support, along with analytics optimized storage engines like ColumnStore make it suitable for handling time series data at smaller levels of data volume.

StarRocks for Time Series Data

StarRocks is primarily focused on data warehousing workloads but can be used for time series data. StarRocks can be used for real time analytics and historical data analysis.

MariaDB Key Concepts

• Storage Engines: MariaDB supports multiple storage engines, each optimized for specific types of workloads or data storage requirements. Examples include InnoDB, MyISAM, Aria, and ColumnStore.
• Galera Cluster: A synchronous, multi-master replication solution for MariaDB that allows for high availability, fault tolerance, and load balancing.
• MaxScale: A database proxy for MariaDB that provides advanced features such as query routing, load balancing, and security.
• Connectors: MariaDB provides a variety of connectors to allow applications to interact with the database using various programming languages and APIs.

StarRocks Key Concepts

• MPP Architecture: StarRocks utilizes an MPP architecture, which enables parallel processing and distributed execution of queries, allowing for high-performance and scalability.
• Vectorized Execution Engine: StarRocks employs a fully vectorized execution engine that leverages SIMD (Single Instruction, Multiple Data) instructions to process data in batches, resulting in optimized query performance.
• Columnar Storage Engine: The columnar storage engine in StarRocks organizes data by column, which improves query performance by only accessing the necessary columns during query execution.
• Cost-Based Optimizer (CBO): StarRocks includes a fully-customized cost-based optimizer that evaluates different query execution plans and selects the most efficient plan based on estimated costs.
• Materialized View: StarRocks supports intelligent materialized views, which are precomputed summaries of data that accelerate query performance by providing faster access to aggregated data.

MariaDB Architecture

MariaDB is a relational database that uses the SQL language for querying and data manipulation. Its architecture is based on a client-server model, with clients interacting with the server through various connectors and APIs. MariaDB supports multiple storage engines, allowing users to choose the most suitable engine for their specific use case. The database also offers replication and clustering options for high availability and load balancing.

StarRocks Architecture

StarRock’s architecture includes a fully vectorized execution engine and a columnar storage engine for efficient data processing and storage. It also incorporates features like a cost-based optimizer and materialized views for optimized query performance. StarRocks supports real-time and batch data ingestion from a variety of sources and enables direct analysis of data stored in data lakes without data migration