When should I use MySQL instead of Redis?

Web application databases needing a fast, reliable, and widely-supported open-source RDBMS. LAMP stack and CMS workloads (WordPress, Drupal) with straightforward CRUD operations. Teams familiar with SQL who need a ubiquitous database with massive community and hosting support

When should I use Redis instead of MySQL?

Ultra-low-latency caching and session storage with sub-millisecond read and write times. Message brokering via Pub/Sub or Redis Streams for simple event-driven workloads. Leaderboards, rate limiting, and real-time counters using atomic data structures

What are the main weaknesses of MySQL?

Fewer advanced SQL features than PostgreSQL: limited window functions, weaker JSON support historically. Oracle ownership raises open-source governance concerns; MariaDB is the common community fork. MyISAM tables (legacy) lack ACID compliance — InnoDB is required for reliable transactions

What are the main weaknesses of Redis?

Data must fit in RAM — not suitable as a primary store for large datasets. Persistence options (RDB snapshots, AOF) add latency or disk I/O overhead. License changed to RSALv2/SSPL in v7.4; Valkey is the open-source fork maintained by the community

MySQL vs Redis: Key Differences for Python Data Engineering

Databases & Data Warehouses

MySQL

Popular Open Source Relational Database

★ 4.7

GPL-2.0 / Commercial (Oracle)

pip install mysql-connector-python

Redis

In-Memory Data Store

★ 4.7

RSALv2 / SSPL (v7.4+)

pip install redis

Side-by-Side Comparison

MySQL

Redis

MySQL

Redis

Best For

✓Web application databases needing a fast, reliable, and widely-supported open-source RDBMS
✓LAMP stack and CMS workloads (WordPress, Drupal) with straightforward CRUD operations
✓Teams familiar with SQL who need a ubiquitous database with massive community and hosting support

✓Ultra-low-latency caching and session storage with sub-millisecond read and write times
✓Message brokering via Pub/Sub or Redis Streams for simple event-driven workloads
✓Leaderboards, rate limiting, and real-time counters using atomic data structures

Best For

✓Web application databases needing a fast, reliable, and widely-supported open-source RDBMS
✓LAMP stack and CMS workloads (WordPress, Drupal) with straightforward CRUD operations
✓Teams familiar with SQL who need a ubiquitous database with massive community and hosting support

✓Ultra-low-latency caching and session storage with sub-millisecond read and write times
✓Message brokering via Pub/Sub or Redis Streams for simple event-driven workloads
✓Leaderboards, rate limiting, and real-time counters using atomic data structures

Weaknesses

•Fewer advanced SQL features than PostgreSQL: limited window functions, weaker JSON support historically
•Oracle ownership raises open-source governance concerns; MariaDB is the common community fork
•MyISAM tables (legacy) lack ACID compliance — InnoDB is required for reliable transactions

•Data must fit in RAM — not suitable as a primary store for large datasets
•Persistence options (RDB snapshots, AOF) add latency or disk I/O overhead
•License changed to RSALv2/SSPL in v7.4; Valkey is the open-source fork maintained by the community

Weaknesses

•Fewer advanced SQL features than PostgreSQL: limited window functions, weaker JSON support historically
•Oracle ownership raises open-source governance concerns; MariaDB is the common community fork
•MyISAM tables (legacy) lack ACID compliance — InnoDB is required for reliable transactions

•Data must fit in RAM — not suitable as a primary store for large datasets
•Persistence options (RDB snapshots, AOF) add latency or disk I/O overhead
•License changed to RSALv2/SSPL in v7.4; Valkey is the open-source fork maintained by the community

License

GPL-2.0 / Commercial (Oracle)

RSALv2 / SSPL (v7.4+)

License

GPL-2.0 / Commercial (Oracle)

RSALv2 / SSPL (v7.4+)

Install

pip install mysql-connector-python

pip install redis

Install

pip install mysql-connector-python

pip install redis

Rating

★ 4.7

Rating

★ 4.7

Key Features

MySQL

1World's most popular open-source relational database
2InnoDB storage engine with ACID transactions and row-level locking
3Replication (primary-replica) for read scaling and disaster recovery
4JSON column type for semi-structured data alongside relational tables
5MySQL Workbench GUI for schema design and query development

Redis

1Sub-millisecond read/write latency for in-memory data structures
2Support for strings, hashes, lists, sets, sorted sets, streams, and more
3Pub/Sub messaging and Redis Streams for event-driven pipeline patterns
4Built-in TTL expiry for automatic cache invalidation
5Redis Cluster for horizontal scaling and high availability

How Python Data Engineers Use These Tools

MySQL

Python data engineers connect to MySQL using `mysql-connector-python` or `PyMySQL`, and use SQLAlchemy with the MySQL dialect for ORM-based pipelines. `pd.read_sql()` pulls query results directly into DataFrames for transformation, and bulk inserts via `executemany()` or LOAD DATA INFILE load processed data back into MySQL tables.

Redis

Python data engineers use Redis via the redis-py library as a high-speed caching layer, rate-limit store, and task queue broker. Redis is the default broker for Celery-based task queues and is used by Apache Airflow for caching pipeline metadata. In data pipelines, Redis stores intermediate results, deduplication sets, and real-time leaderboards that would be too slow to query from a relational database on every request.

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Individual Tool Pages

View MySQL details →View Redis details →

Side-by-Side Comparison

MySQL

Redis

MySQL

Redis

Best For

✓Web application databases needing a fast, reliable, and widely-supported open-source RDBMS
✓LAMP stack and CMS workloads (WordPress, Drupal) with straightforward CRUD operations
✓Teams familiar with SQL who need a ubiquitous database with massive community and hosting support

✓Ultra-low-latency caching and session storage with sub-millisecond read and write times
✓Message brokering via Pub/Sub or Redis Streams for simple event-driven workloads
✓Leaderboards, rate limiting, and real-time counters using atomic data structures

Best For

✓Web application databases needing a fast, reliable, and widely-supported open-source RDBMS
✓LAMP stack and CMS workloads (WordPress, Drupal) with straightforward CRUD operations
✓Teams familiar with SQL who need a ubiquitous database with massive community and hosting support

✓Ultra-low-latency caching and session storage with sub-millisecond read and write times
✓Message brokering via Pub/Sub or Redis Streams for simple event-driven workloads
✓Leaderboards, rate limiting, and real-time counters using atomic data structures

Weaknesses

•Fewer advanced SQL features than PostgreSQL: limited window functions, weaker JSON support historically
•Oracle ownership raises open-source governance concerns; MariaDB is the common community fork
•MyISAM tables (legacy) lack ACID compliance — InnoDB is required for reliable transactions

•Data must fit in RAM — not suitable as a primary store for large datasets
•Persistence options (RDB snapshots, AOF) add latency or disk I/O overhead
•License changed to RSALv2/SSPL in v7.4; Valkey is the open-source fork maintained by the community

Weaknesses

•Fewer advanced SQL features than PostgreSQL: limited window functions, weaker JSON support historically
•Oracle ownership raises open-source governance concerns; MariaDB is the common community fork
•MyISAM tables (legacy) lack ACID compliance — InnoDB is required for reliable transactions

•Data must fit in RAM — not suitable as a primary store for large datasets
•Persistence options (RDB snapshots, AOF) add latency or disk I/O overhead
•License changed to RSALv2/SSPL in v7.4; Valkey is the open-source fork maintained by the community

License

GPL-2.0 / Commercial (Oracle)

RSALv2 / SSPL (v7.4+)

License

GPL-2.0 / Commercial (Oracle)

RSALv2 / SSPL (v7.4+)

Install

pip install mysql-connector-python

pip install redis

Install

pip install mysql-connector-python

pip install redis

Rating

★ 4.7

Rating

★ 4.7

Key Features

MySQL

1World's most popular open-source relational database
2InnoDB storage engine with ACID transactions and row-level locking
3Replication (primary-replica) for read scaling and disaster recovery
4JSON column type for semi-structured data alongside relational tables
5MySQL Workbench GUI for schema design and query development

Redis

1Sub-millisecond read/write latency for in-memory data structures
2Support for strings, hashes, lists, sets, sorted sets, streams, and more
3Pub/Sub messaging and Redis Streams for event-driven pipeline patterns
4Built-in TTL expiry for automatic cache invalidation
5Redis Cluster for horizontal scaling and high availability

How Python Data Engineers Use These Tools