How to Choose MySQL Over ClickHouse

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Why should I use MySQL over ClickHouse for transactional workloads?

Use MySQL when you need fast, reliable OLTP, ACID transactions, and broad ecosystem support instead of ClickHouse’s column-store analytics focus.

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Description

What workload benefits most from MySQL?

High-volume, short-lived OLTP transactions such as creating customers, inserting orders, or updating product stock run faster on MySQL’s row-store engine than on ClickHouse.

Why does MySQL excel at ecommerce use cases?

ACID transactions, foreign-key constraints, and row-level locking keep customer, order, and inventory data consistent even under heavy write load.

How does ClickHouse differ?

ClickHouse’s columnar storage, sparse indexing, and vectorized execution optimize large aggregations (e.g., daily revenue summaries) but make single-row inserts slower and limit JOIN support.

When should I avoid ClickHouse?

For frequent single-row writes, complex multi-row updates, or schema changes that require strong consistency, ClickHouse adds latency and complexity.

How do transactions work in MySQL?

BEGIN; statements wrap INSERTs, UPDATEs, and DELETEs into a single atomic unit that the engine commits or rolls back as a whole—critical for order processing.

Example transaction flow

Start transaction, write to Orders, decrement Products.stock, insert OrderItems, COMMIT.

Best practices for choosing MySQL

1) Normalize schemas. 2) Add composite indexes on foreign keys. 3) Use InnoDB engine for row-level locking. 4) Enable binary logging for point-in-time recovery.

How can I still use ClickHouse?

Replicate aggregated data into ClickHouse for sub-second dashboards while keeping the source-of-truth in MySQL.

Why How to Choose MySQL Over ClickHouse is important

How to Choose MySQL Over ClickHouse Example Usage


-- Retrieve latest orders with customer and item count in MySQL
SELECT c.name,
       o.id                              AS order_id,
       o.order_date,
       SUM(oi.quantity)                 AS total_items,
       o.total_amount
FROM   Orders      o
JOIN   Customers   c ON c.id = o.customer_id
JOIN   OrderItems  oi ON oi.order_id = o.id
GROUP  BY o.id, c.name, o.order_date, o.total_amount
ORDER  BY o.order_date DESC
LIMIT  10;

How to Choose MySQL Over ClickHouse Syntax


-- Create Customers table in MySQL
CREATE TABLE Customers (
    id INT AUTO_INCREMENT PRIMARY KEY,
    name VARCHAR(100) NOT NULL,
    email VARCHAR(255) UNIQUE,
    created_at TIMESTAMP DEFAULT CURRENT_TIMESTAMP
);

-- Equivalent ClickHouse table (not ideal for OLTP)
CREATE TABLE Customers (
    id UInt32,
    name String,
    email String,
    created_at DateTime DEFAULT now()
) ENGINE = MergeTree()
ORDER BY id;

-- Begin a transaction in MySQL
START TRANSACTION;
INSERT INTO Orders (customer_id, order_date, total_amount)
VALUES (1, NOW(), 199.99);
UPDATE Products SET stock = stock - 1 WHERE id = 7;
COMMIT;

Common Mistakes

Frequently Asked Questions (FAQs)

Is MySQL faster than ClickHouse?

For single-row writes and small result sets, yes. ClickHouse outperforms on large aggregations.

Can I use both MySQL and ClickHouse together?

Yes. Store raw data in MySQL, then ETL aggregates into ClickHouse for reporting.

Does MySQL support column-store engines?

MySQL 8 offers the MySQL HeatWave ColumnStore, but it is separate from the core server. Traditional InnoDB remains best for OLTP.

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