Quickstart guide for MariaDB ColumnStore
MariaDB ColumnStore is a specialized columnar storage engine designed for high-performance analytical processing and big data workloads. Unlike traditional row-based storage engines, ColumnStore organizes data by columns, which is highly efficient for analytical queries that often access only a subset of columns across vast datasets.
MariaDB ColumnStore is a columnar storage engine that integrates with MariaDB Server. It employs a massively parallel distributed data architecture, making it ideal for processing petabytes of data with linear scalability. It was originally ported from InfiniDB and is released under the GPL license.
Exceptional Analytical Performance: Delivers superior performance for complex analytical queries (OLAP) due to its columnar nature, which minimizes disk I/O by reading only necessary columns.
High Data Compression: Columnar storage allows for much higher compression ratios compared to row-based storage, reducing disk space usage and improving query speed.
Massive Scalability: Designed to scale horizontally across multiple nodes, processing petabytes of data with ease.
MariaDB ColumnStore utilizes a distributed architecture with different components working together:
User Module (UM): Handles incoming SQL queries, optimizes them for columnar processing, and distributes tasks.
Performance Module (PM): Manages data storage, compression, and execution of query fragments on the data segments.
Data Files: Data is stored in column-segments across the nodes, highly compressed.
MariaDB ColumnStore is installed as a separate package that integrates with MariaDB Server. The exact installation steps vary depending on your operating system and desired deployment type (single server or distributed cluster).
General Steps (conceptual):
Install MariaDB Server: Ensure you have a compatible MariaDB Server version installed (e.g., MariaDB 10.5.4 or later).
Install ColumnStore Package: Download and install the specific MariaDB ColumnStore package for your OS. This package includes the ColumnStore storage engine and its associated tools.
Linux (e.g., Debian/Ubuntu): You would typically add the MariaDB repository configured for ColumnStore and then install mariadb-plugin-columnstore.
Once MariaDB ColumnStore is installed and configured, you can create and interact with ColumnStore tables using standard SQL.
Specify ENGINE=ColumnStore when creating your table. Note that ColumnStore tables do not support primary keys in the same way as InnoDB, as their primary focus is analytical processing.
You can insert data using standard INSERT statements. For large datasets, bulk loading utilities (for instance, LOAD DATA INFILE) are highly recommended for performance.
Perform analytical queries. ColumnStore will efficiently process these, often leveraging its columnar nature and parallelism.
Real-time Analytics: Capable of handling real-time analytical queries efficiently.
Single Server vs. Distributed: For a single-server setup, you install all ColumnStore components on one machine. For a distributed setup, you install and configure components across multiple machines.
Configure MariaDB: After installation, you might need to adjust your MariaDB server configuration (my.cnf or equivalent) to properly load and manage the ColumnStore engine.
Initialize ColumnStore: Run a specific columnstore-setup or post-install script to initialize the ColumnStore environment.
CREATE TABLE sales_data (
sale_id INT,
product_name VARCHAR(255),
category VARCHAR(100),
sale_date DATE,
quantity INT,
price DECIMAL(10, 2)
) ENGINE=ColumnStore;INSERT INTO sales_data (sale_id, product_name, category, sale_date, quantity, price) VALUES
(1, 'Laptop', 'Electronics', '2023-01-15', 1, 1200.00),
(2, 'Mouse', 'Electronics', '2023-01-15', 2, 25.00),
(3, 'Keyboard', 'Electronics', '2023-01-16', 1, 75.00);-- Get total sales per category
SELECT category, SUM(quantity * price) AS total_sales
FROM sales_data
WHERE sale_date BETWEEN '2023-01-01' AND '2023-01-31'
GROUP BY category
ORDER BY total_sales DESC;
-- Count distinct products
SELECT COUNT(DISTINCT product_name) FROM sales_data;MariaDB ColumnStore Quickstart Guides provide concise, Docker-friendly steps to quickly set up, configure, and explore the ColumnStore analytic engine.
This page details MariaDB ColumnStore hardware requirements (CPU, RAM, storage, and network).
MariaDB ColumnStore is designed for analytical workloads and scales linearly with hardware resources. While the performance generally improves with more CPU cores, memory, and servers, understanding the minimum hardware specifications is crucial for successful deployment, especially in development and production environments.
MariaDB ColumnStore's performance directly benefits from additional hardware resources:
More CPU cores
More memory allows for more data caching (reducing I/O), and more servers enable a larger distributed architecture.
HDDs vs. SSDs: SSDs don't deliver as much benefit as you might assume because ColumnStore is optimized towards block streaming, which usually performs well enough on HDDs.
Bare metal vs. virtual servers: Bare metal servers are recommended — they provide additional performance because ColumnStore can fully consume CPU cores and memory.
The specifications differentiate between a basic development environment and a production-ready setup:
CPU: A minimum of 8 CPU cores.
Memory (RAM): A minimum of 32 GB.
Storage: Local disk storage is acceptable for development purposes.
CPU: A minimum of 64 CPU cores.
This recommendation underscores the highly parallel nature of ColumnStore, which can effectively utilize a large number of cores for analytical processing.
Memory (RAM): A minimum of 128 GB.
Adequate memory is critical for caching data and intermediate results, directly impacting query performance.
Storage: StorageManager (S3) is recommended.
This implies leveraging cloud-object storage (like AWS S3 or compatible services) for scalable and durable data persistence in production.
Network interconnectivity plays a role for multi-server deployments.
Minimum Network: A minimum of a 1 Gigabit (1G) network is recommended.
This facilitates efficient data transfer between nodes via TCP/IP for replication and query processing across the distributed architecture. For optimal performance in heavy-load scenarios, higher bandwidth (for instance, 10G or more) is highly beneficial.
Adhering to these minimum specifications will provide a baseline for ColumnStore functionality. For specific workload requirements, it's always advisable to conduct performance testing and scale hardware accordingly.
For AWS, ColumnStore internal testing generally uses m4.4xlarge instance types as a cost-effective middle ground. The R4.8xlarge has also been tested, and performs about twice as fast for about twice the price.
MariaDB ColumnStore Minimum Hardware Specification Documentation
This page is: Copyright © 2025 MariaDB. All rights reserved.
This page is: Copyright © 2025 MariaDB. All rights reserved.