Overview

Microsoft SQL Server

Stacks20.2K

Followers15.5K

Votes540

Memcached

Stacks8.0K

Followers5.7K

Votes473

GitHub Stars14.0K

Forks3.3K

Memcached vs Microsoft SQL Server: What are the differences?

Introduction

In this article, we will discuss the key differences between Memcached and Microsoft SQL Server.

Scalability: Memcached is designed to be highly scalable and can handle large amounts of data efficiently. It is primarily used for caching purposes and can easily scale horizontally by adding more servers to the network. On the other hand, Microsoft SQL Server is a relational database management system (RDBMS), which is designed for structured data storage and retrieval. While SQL Server can also handle large amounts of data, it primarily scales vertically by upgrading hardware resources.
Data Persistence: Memcached is an in-memory caching system and does not provide built-in support for data persistence. This means that if a server fails or restarts, the cached data is lost. On the contrary, Microsoft SQL Server provides robust data persistence capabilities. It offers various options for data storage, including disk-based storage, transaction logs, and backups, ensuring data durability and recoverability.
Data Structure and Query Language: Memcached is a key-value store and stores data in a simple key-value pair format, making it suitable for caching unstructured or semi-structured data. It does not support complex data structures or a query language. On the other hand, Microsoft SQL Server supports structured data storage and provides a full-featured query language called SQL (Structured Query Language). SQL Server allows complex data modeling, indexing, and querying capabilities, making it suitable for handling structured data.
ACID Compliance: Memcached is not ACID (Atomicity, Consistency, Isolation, Durability) compliant. It does not provide transactional capabilities or enforce data integrity constraints. In contrast, Microsoft SQL Server is fully ACID compliant. It ensures that database transactions are processed in a reliable and consistent manner, allowing for data integrity and preventing data corruption.
Concurrency Control: Memcached does not provide built-in concurrency control mechanisms. It does not handle simultaneous read and write operations on the same data reliably. On the other hand, Microsoft SQL Server offers robust concurrency control mechanisms, allowing multiple transactions to access and modify data concurrently without causing data corruption or inconsistency issues.
Data Schema and Flexibility: Memcached does not enforce any predefined data schema, allowing for flexible data storage and retrieval. It does not require schema definition or schema migrations, making it easy to store and retrieve heterogeneous data. In contrast, Microsoft SQL Server enforces a rigid data schema and requires proper data modeling and schema definition. It ensures data consistency and provides strong data typing and integrity constraints.

In Summary, Memcached is a scalable, in-memory caching system mainly used for unstructured data caching, while Microsoft SQL Server is a robust relational database management system designed for structured data storage, transactional integrity, and complex querying capabilities.

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Advice on Microsoft SQL Server, Memcached

Erin

IT Specialist

Mar 10, 2020

Needs adviceon

Microsoft SQL Server

MySQL

PostgreSQL

I am a Microsoft SQL Server programmer who is a bit out of practice. I have been asked to assist on a new project. The overall purpose is to organize a large number of recordings so that they can be searched. I have an enormous music library but my songs are several hours long. I need to include things like time, date and location of the recording. I don't have a problem with the general database design. I have two primary questions:

I need to use either @{MySQL}|tool:1025| or @{PostgreSQL}|tool:1028| on a @{Linux}|tool:10483| based OS. Which would be better for this application?
I have not dealt with a sound based data type before. How do I store that and put it in a table? Thank you.

668k views668k

Comments

Josip

Senior frontend developer

Aug 31, 2021

Decided

Needed to transform intranet desktop application to the web-based one, as mid-term project. My choice was to use Django/Angular stack - Django since it, in conjunction with Python, enabled rapid development, an Angular since it was stable and enterprise-level framework. Deadlines were somewhat tight since the project to migrate was being developed for several years and had a lot of domain knowledge integrated into it. Definitely was good decision, since deadlines was manageable, juniors were able to enter the project very quickly and we were able to continuously deploy very well.

73.6k views73.6k

Comments

Detailed Comparison

Microsoft SQL Server	Memcached
Microsoft® SQL Server is a database management and analysis system for e-commerce, line-of-business, and data warehousing solutions.	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.
Statistics
GitHub Stars -	GitHub Stars 14.0K
GitHub Forks -	GitHub Forks 3.3K
Stacks 20.2K	Stacks 8.0K
Followers 15.5K	Followers 5.7K
Votes 540	Votes 473
Pros & Cons
Pros 139 Reliable and easy to use 101 High performance 95 Great with .net 65 Works well with .net 56 Easy to maintain Cons 4 Expensive Licensing 2 Microsoft 1 Allwayon can loose data in asycronious mode 1 The maximum number of connections is only 14000 connect 1 Data pages is only 8k	Pros 139 Fast object cache 129 High-performance 91 Stable 65 Mature 33 Distributed caching system Cons 2 Only caches simple types

What are some alternatives to Microsoft SQL Server, Memcached?

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

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 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.

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

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.

MariaDB

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.

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

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 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

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.