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  1. Stackups
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  4. Databases
  5. MariaDB vs Memcached

MariaDB vs Memcached

OverviewDecisionsComparisonAlternatives

Overview

Memcached
Memcached
Stacks7.9K
Followers5.7K
Votes473
GitHub Stars14.0K
Forks3.3K
MariaDB
MariaDB
Stacks16.5K
Followers12.8K
Votes468
GitHub Stars6.6K
Forks1.9K

MariaDB vs Memcached: What are the differences?

Introduction

In this article, we will explore the key differences between MariaDB and Memcached. Both MariaDB and Memcached are popular open-source database technologies used in web applications. However, they serve different purposes and possess distinct characteristics.

  1. Data Storage and Retrieval: MariaDB is a fully-featured relational database management system (RDBMS) that offers comprehensive support for structured data storage, retrieval, and manipulation. It supports complex queries, transactions, and various data types. On the other hand, Memcached is a high-performance distributed caching system that allows for fast and efficient retrieval of data from memory. It is mainly used for caching frequently-accessed data to improve application performance.

  2. Query Language: MariaDB uses Structured Query Language (SQL) as its primary language for communicating with the database. SQL provides a powerful and standardized way to interact with relational databases. In contrast, Memcached does not support SQL. Instead, it offers a simple key-value interface, allowing developers to store and retrieve data using unique keys.

  3. Data Persistence: MariaDB ensures data persistence, meaning that data is saved to disk and can be recovered in case of system failures or restarts. It offers various storage engines, including InnoDB and MyISAM, each with its own strengths and features. On the other hand, Memcached does not provide native data persistence. It stores data solely in memory and does not save it to disk. As a result, data is lost if the Memcached server restarts or crashes.

  4. Scaling Capabilities: MariaDB is designed to support scaling both vertically and horizontally. It can handle large amounts of data and high concurrent user traffic by utilizing features like replication, sharding, and clustering. Memcached, on the other hand, focuses on horizontal scaling, allowing for the distribution of data across multiple servers. It provides a decentralized caching layer, which can be easily scaled by adding more Memcached nodes to handle increasing data loads.

  5. Concurrency Control: MariaDB employs robust concurrency control mechanisms to ensure data integrity in multi-user environments. It supports various levels of isolation, transaction management, and locking mechanisms to prevent conflicts and data inconsistencies. Memcached, on the other hand, does not provide built-in support for concurrency control. It is designed for simple read and write operations and does not handle complex transactions or locking mechanisms.

  6. Data Analysis and Complexity: MariaDB is well-suited for applications that require complex data analysis, reporting, and business intelligence. It offers features like joins, subqueries, and aggregations, enabling developers to perform complex data manipulations and analysis. On the other hand, Memcached is not intended for data analysis or complex query operations. It is primarily used as a cache layer to improve application performance by reducing database load and speeding up data retrieval.

In summary, MariaDB is a feature-rich RDBMS suitable for storing and managing structured data, supporting complex queries, and providing data persistence, while Memcached is a high-performance caching system designed for fast data retrieval and horizontal scalability, but lacking data persistence and complex query capabilities.

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Advice on Memcached, 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

Memcached
Memcached
MariaDB
MariaDB

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.

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
14.0K
GitHub Stars
6.6K
GitHub Forks
3.3K
GitHub Forks
1.9K
Stacks
7.9K
Stacks
16.5K
Followers
5.7K
Followers
12.8K
Votes
473
Votes
468
Pros & Cons
Pros
  • 139
    Fast object cache
  • 129
    High-performance
  • 91
    Stable
  • 65
    Mature
  • 33
    Distributed caching system
Cons
  • 2
    Only caches simple types
Pros
  • 149
    Drop-in mysql replacement
  • 100
    Great performance
  • 74
    Open source
  • 55
    Free
  • 44
    Easy setup

What are some alternatives to Memcached, 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.

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.

CouchDB

CouchDB

Apache CouchDB is a database that uses JSON for documents, JavaScript for MapReduce indexes, and regular HTTP for its API. CouchDB is a database that completely embraces the web. Store your data with JSON documents. Access your documents and query your indexes with your web browser, via HTTP. Index, combine, and transform your documents with JavaScript.

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