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  1. Stackups
  2. Application & Data
  3. In-Memory Databases
  4. In Memory Databases
  5. MariaDB vs Redis

MariaDB vs Redis

OverviewDecisionsComparisonAlternatives

Overview

Redis
Redis
Stacks61.9K
Followers46.5K
Votes3.9K
GitHub Stars42
Forks6
MariaDB
MariaDB
Stacks16.5K
Followers12.8K
Votes468
GitHub Stars6.6K
Forks1.9K

MariaDB vs Redis: What are the differences?

Introduction

MariaDB and Redis are both popular open-source databases used in web development. However, they have key differences in terms of data storage, data processing, scalability, data persistence, data structure, and data querying.

  1. Data Storage: MariaDB is a traditional relational database that stores data in tables with a predefined schema. On the other hand, Redis is an in-memory data structure store that can store data in various formats such as strings, hashes, lists, sets, and sorted sets.

  2. Data Processing: MariaDB is designed to handle complex SQL queries and supports advanced functionalities such as joins, subqueries, and transaction management. In contrast, Redis primarily focuses on simple key-value operations and does not provide the same level of complexity for data processing.

  3. Scalability: MariaDB can scale horizontally by adding more servers and distributing the data across them. It supports sharding and replication to improve performance and handle large datasets. Redis, on the other hand, provides high performance and scalability through its in-memory architecture but lacks built-in features for horizontal scaling.

  4. Data Persistence: MariaDB ensures data persistence by writing the data to disk. It supports different storage engines, including InnoDB and MyISAM, which provide durability even in the event of a system failure. Redis, however, primarily stores data in memory and offers optional persistence mechanisms such as snapshotting and appending-only file (AOF) persistence.

  5. Data Structure: MariaDB stores data in a structured manner using tables with columns and rows. It enforces a schema where columns have defined data types and constraints. Redis, on the other hand, allows for flexible data structures and does not require a predefined schema. It can store and manipulate data in a variety of formats based on its use case.

  6. Data Querying: MariaDB uses SQL (Structured Query Language) for querying and manipulating data. It provides a rich set of relational operations and supports complex queries. Redis, on the other hand, uses its own set of commands for data querying and manipulation. It provides simple operations like setting, getting, and deleting data based on keys.

In Summary, MariaDB is a traditional relational database with support for complex queries and structured data storage, while Redis is an in-memory data structure store optimized for high performance, flexibility, and simplicity in data manipulation.

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Advice on Redis, MariaDB

Maxim
Maxim

student at USI

Aug 25, 2020

Needs adviceonNode.jsNode.jsMongooseMongoosePostgreSQLPostgreSQL

Hi all. I am an informatics student, and I need to realise a simple website for my friend. I am planning to realise the website using Node.js and Mongoose, since I have already done a project using these technologies. I also know SQL, and I have used PostgreSQL and MySQL previously.

The website will show a possible travel destination and local transportation. The database is used to store information about traveling, so only admin will manage the content (especially photos). While clients will see the content uploaded by the admin. I am planning to use Mongoose because it is very simple and efficient for this project. Please give me your opinion about this choice.

321k views321k
Comments
Omran
Omran

CTO & Co-founder at Bonton Connect

Jun 19, 2020

Needs advice

We actually use both Mongo and SQL databases in production. Mongo excels in both speed and developer friendliness when it comes to geospatial data and queries on the geospatial data, but we also like ACID compliance hence most of our other data (except on-site logs) are stored in a SQL Database (MariaDB for now)

582k views582k
Comments

Detailed Comparison

Redis
Redis
MariaDB
MariaDB

Redis is an open source (BSD licensed), in-memory data structure store, used as a database, cache, and message broker. Redis provides data structures such as strings, hashes, lists, sets, sorted sets with range queries, bitmaps, hyperloglogs, geospatial indexes, and streams.

Started by core members of the original MySQL team, MariaDB actively works with outside developers to deliver the most featureful, stable, and sanely licensed open SQL server in the industry. MariaDB is designed as a drop-in replacement of MySQL(R) with more features, new storage engines, fewer bugs, and better performance.

-
Replication;Insert Delayed;Events;Dynamic;Columns;Full-text;Search;GIS;Locale;Settings;subqueries;Timezones;Triggers;XML;Functions;Views;SSL;Show Profile
Statistics
GitHub Stars
42
GitHub Stars
6.6K
GitHub Forks
6
GitHub Forks
1.9K
Stacks
61.9K
Stacks
16.5K
Followers
46.5K
Followers
12.8K
Votes
3.9K
Votes
468
Pros & Cons
Pros
  • 888
    Performance
  • 542
    Super fast
  • 514
    Ease of use
  • 444
    In-memory cache
  • 324
    Advanced key-value cache
Cons
  • 15
    Cannot query objects directly
  • 3
    No secondary indexes for non-numeric data types
  • 1
    No WAL
Pros
  • 149
    Drop-in mysql replacement
  • 100
    Great performance
  • 74
    Open source
  • 55
    Free
  • 44
    Easy setup

What are some alternatives to Redis, MariaDB?

MongoDB

MongoDB

MongoDB stores data in JSON-like documents that can vary in structure, offering a dynamic, flexible schema. MongoDB was also designed for high availability and scalability, with built-in replication and auto-sharding.

MySQL

MySQL

The MySQL software delivers a very fast, multi-threaded, multi-user, and robust SQL (Structured Query Language) database server. MySQL Server is intended for mission-critical, heavy-load production systems as well as for embedding into mass-deployed software.

PostgreSQL

PostgreSQL

PostgreSQL is an advanced object-relational database management system that supports an extended subset of the SQL standard, including transactions, foreign keys, subqueries, triggers, user-defined types and functions.

Microsoft SQL Server

Microsoft SQL Server

Microsoft® SQL Server is a database management and analysis system for e-commerce, line-of-business, and data warehousing solutions.

SQLite

SQLite

SQLite is an embedded SQL database engine. Unlike most other SQL databases, SQLite does not have a separate server process. SQLite reads and writes directly to ordinary disk files. A complete SQL database with multiple tables, indices, triggers, and views, is contained in a single disk file.

Cassandra

Cassandra

Partitioning means that Cassandra can distribute your data across multiple machines in an application-transparent matter. Cassandra will automatically repartition as machines are added and removed from the cluster. Row store means that like relational databases, Cassandra organizes data by rows and columns. The Cassandra Query Language (CQL) is a close relative of SQL.

Memcached

Memcached

Memcached is an in-memory key-value store for small chunks of arbitrary data (strings, objects) from results of database calls, API calls, or page rendering.

RethinkDB

RethinkDB

RethinkDB is built to store JSON documents, and scale to multiple machines with very little effort. It has a pleasant query language that supports really useful queries like table joins and group by, and is easy to setup and learn.

ArangoDB

ArangoDB

A distributed free and open-source database with a flexible data model for documents, graphs, and key-values. Build high performance applications using a convenient SQL-like query language or JavaScript extensions.

InfluxDB

InfluxDB

InfluxDB is a scalable datastore for metrics, events, and real-time analytics. It has a built-in HTTP API so you don't have to write any server side code to get up and running. InfluxDB is designed to be scalable, simple to install and manage, and fast to get data in and out.

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