Use MySQL when you need fast, reliable OLTP, ACID transactions, and broad ecosystem support instead of ClickHouse’s column-store analytics focus.
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.
ACID transactions, foreign-key constraints, and row-level locking keep customer, order, and inventory data consistent even under heavy write load.
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.
For frequent single-row writes, complex multi-row updates, or schema changes that require strong consistency, ClickHouse adds latency and complexity.
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.
Start transaction, write to Orders, decrement Products.stock, insert OrderItems, COMMIT.
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.
Replicate aggregated data into ClickHouse for sub-second dashboards while keeping the source-of-truth in MySQL.
For single-row writes and small result sets, yes. ClickHouse outperforms on large aggregations.
Yes. Store raw data in MySQL, then ETL aggregates into ClickHouse for reporting.
MySQL 8 offers the MySQL HeatWave ColumnStore, but it is separate from the core server. Traditional InnoDB remains best for OLTP.