MySQL vs Redis
A detailed comparison
Compare MySQL and Redis for time series and OLAP workloads
Learn About Time Series DatabasesChoosing 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 MySQL and Redis so you can quickly see how they compare against each other.
The primary purpose of this article is to compare how MySQL and Redis 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.
MySQL vs Redis Breakdown
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 |
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| Database Model | Relational database |
In-memory database |
| Architecture | MySQL uses a client-server model with a multi-layered server design. It supports the SQL query language and offers various storage engines, such as InnoDB and MyISAM, for different use cases. MySQL can be deployed on-premises, in the cloud, or as a managed service. |
Redis can be deployed on-premises, in the cloud, or as a managed service |
| License | GNU General Public License v2 (for the open-source Community Edition) |
BSD 3 |
| Use Cases | Web applications, e-commerce, data warehousing, content management systems, business applications |
Caching, message brokering, real-time analytics, session storage, geospatial data processing |
| Scalability | Supports vertical scaling by adding more resources to a single node; horizontal scaling can be achieved through replication, sharding, and third-party tools |
Horizontally scalable via partitioning and clustering, supports data replication |
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MySQL Overview
MySQL is an open source relational database management system that was first released in 1995. It is one of the most popular databases worldwide due to its ease of use, reliability, and performance. MySQL is widely used for web applications, online transaction processing, and data warehousing. Oracle Corporation acquired MySQL in 2010, but it remains open source software with an active community of contributors.
Redis Overview
Redis, which stands for Remote Dictionary Server, is an open-source, in-memory data structure store that can be used as a database, cache, and message broker. It was created by Salvatore Sanfilippo in 2009 and has since gained significant popularity due to its high performance and flexibility. Redis supports various data structures, such as strings, hashes, lists, sets, sorted sets with range queries, bitmaps, hyperloglogs, and geospatial indexes with radius queries.
MySQL for Time Series Data
MySQL can be used for storing and analyzing time series data, but it will not be as efficient as a dedicated time series databases. MySQL’s flexibility and support for various indexing techniques can make it a suitable choice for small to medium sized time series datasets. For large-scale time series data workloads, with high write throughput or use cases where low latency queries are required, MySQL will tend to struggle unless highly customized.
Redis for Time Series Data
Redis has a dedicated module for working with time series data called RedisTimeSeries. RedisTimeSeries offers functionality like downsampling, data retention policies, and specialized queries for time series data in Redis. Being an in-memory database, Redis will be very fast for reading and writing time series data, but due to the cost of RAM compared to disk using Redis could become expensive depending on the size of your dataset. If your use case doesn’t require extremely fast response times, you could save money by going with a more traditional time series database.
MySQL Key Concepts
- Table: A collection of related data organized in rows and columns, which is the primary structure for storing data in MySQL.
- Primary Key: A unique identifier for each row in a table, used to enforce data integrity and enable efficient querying.
- Foreign Key: A column or set of columns in a table that refers to the primary key in another table, used to establish relationships between tables.
Redis Key Concepts
- In-memory store: Redis stores data in memory, which allows for faster data access and manipulation compared to disk-based databases .
- Data structures: Redis supports a wide range of data structures, including strings, hashes, lists, sets, and more, which provide flexibility in how data is modeled and stored.
- Persistence: Redis offers optional data persistence, allowing data to be periodically saved to disk or written to a log for durability.
- Pub/Sub: Redis provides a publish/subscribe messaging system, enabling real-time communication between clients without the need for a centralized message broker.
MySQL Architecture
MySQL is a relational database management system that uses SQL for defining and manipulating data. It follows the client-server model, where a MySQL server accepts connections from multiple clients and processes their queries. MySQL’s architecture includes a storage engine framework that allows users to choose from different storage engines, such as InnoDB, MyISAM, or Memory, to optimize the database for specific use cases.
Redis Architecture
Redis is a NoSQL database that uses a key-value data model, where each key is associated with a value stored as one of Redis’ supported data structures. The database is single-threaded, which simplifies its internal architecture and reduces contention. Redis can be deployed as a standalone server, a cluster, or a master-replica setup for scalability and high availability. The Redis Cluster mode automatically shards data across multiple nodes, providing data partitioning and fault tolerance.
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MySQL Features
ACID compliance
MySQL supports transactions and adheres to the ACID (Atomicity, Consistency, Isolation, Durability) properties, ensuring data integrity and consistency.
Scalability
MySQL can scale both vertically and horizontally, depending on the storage engine and configuration.
Replication and high availability
MySQL supports various replication techniques, including master-slave and master-master replication, to provide high availability and fault tolerance.
Redis Features
Atomicity
Redis supports atomic operations on complex data types, allowing developers to perform powerful operations without worrying about race conditions or other concurrent processing issues.
Broad data structure support
Redis supports a range of data structures such as lists, sets, sorted sets, hashes, bitmaps, hyperloglog, and geospatial indexes. This flexibility allows developers to use Redis for a wide variety of tasks by using data structures that are optimized for their data in terms of performance characteristics.
Pub/Sub messaging
Redis provides a publish/subscribe messaging system for real-time communication between clients.
Lua Scripting
Developers can run Lua scripts in the Redis server, enabling complex operations to be executed atomically in the server itself, reducing network round trips.
MySQL Use Cases
Web applications
MySQL is a popular choice for powering web applications, content management systems, and e-commerce platforms due to its flexibility, ease of use, and performance.
Online transaction processing (OLTP)
MySQL is suitable for OLTP systems that require high concurrency, fast response times, and support for transactions.
Data warehousing
While not specifically designed for data warehousing, MySQL can be used for small to medium-sized data warehouses, leveraging its support for indexing, partitioning, and other optimization techniques.
Redis Use Cases
Caching
Redis is often used as a cache to store frequently accessed data and reduce the load on other databases or services, improving application performance and reducing latency.
Task queues
Redis can be used to implement task queues, which are useful for managing tasks that take longer to process and should be executed asynchronously. This is particularly common in web applications, where background tasks can be processed independently of the request/response cycle
Real-time analysis and machine learning
Redis’ high performance and low-latency data access make it suitable for real-time analysis and machine learning applications, such as processing streaming data, media streaming, and handling time-series data. This can be achieved using Redis’ data structures and capabilities like sorted sets, timestamps, and pub/sub messaging.
MySQL Pricing Model
MySQL is available in multiple editions with different feature sets and pricing models. The MySQL Community Edition is open source and free to use, while the MySQL Enterprise Edition includes additional features, such as advanced security, monitoring, and management tools, and requires a subscription. Pricing for the Enterprise Edition depends on the number of server instances and the level of support required.
Redis Pricing Model
Redis is open-source software, which means it can be deployed and used freely on your own infrastructure. However, there are also managed Redis services available, such as Redis Enterprise which offer additional features, support, and ease of deployment. Pricing for these services typically depends on factors like the size of the instance, data storage, and data transfer.
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