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  1. Stackups
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  3. Databases
  4. Databases
  5. Memcached vs Microsoft SQL Server vs SQLite

Memcached vs Microsoft SQL Server vs SQLite

OverviewDecisionsComparisonAlternatives

Overview

Microsoft SQL Server
Microsoft SQL Server
Stacks21.3K
Followers15.5K
Votes540
Memcached
Memcached
Stacks7.9K
Followers5.7K
Votes473
GitHub Stars14.0K
Forks3.3K
SQLite
SQLite
Stacks19.9K
Followers15.2K
Votes535

Memcached vs Microsoft SQL Server vs SQLite: What are the differences?

Introduction:

Key Differences Between Memcached, Microsoft SQL Server, and SQLite:

  1. Type of Database: Memcached is an in-memory key-value store, perfect for quick data retrieval. Microsoft SQL Server is a full-fledged relational database management system that stores data in tables with relationships between them. SQLite is a lightweight, serverless, self-contained database that is best suited for local storage in mobile apps and embedded systems.

  2. Data Persistence: Memcached does not persist data to disk, meaning data is lost upon restarting the server. Microsoft SQL Server and SQLite both support data persistence, allowing data to be stored even after server restarts.

  3. Complexity and Query Language: Microsoft SQL Server offers a comprehensive set of features and a powerful query language with support for complex queries, stored procedures, and triggers. SQLite, on the other hand, is designed to be lightweight and has a simpler SQL implementation without support for advanced database features. Memcached is not a database system but rather a caching system, so it does not support querying like traditional databases.

  4. Scalability: Memcached is highly scalable and can easily distribute data across multiple nodes, making it suitable for high-traffic websites. Microsoft SQL Server and SQLite are limited in scalability compared to Memcached due to their disk-based nature, making them more suitable for smaller to medium-sized applications.

  5. ACID Compliance: Microsoft SQL Server and SQLite both ensure ACID (Atomicity, Consistency, Isolation, Durability) compliance, providing data integrity and reliability. Memcached sacrifices ACID compliance for performance gains as it focuses on caching frequently accessed data rather than ensuring transactional consistency.

  6. Security Features: Microsoft SQL Server offers a wide range of security features such as encryption, access control, and auditing mechanisms to protect data. SQLite lacks advanced security features compared to Microsoft SQL Server and is more suitable for smaller, local applications. Memcached does not offer built-in security features and relies on external mechanisms for securing data.

In Summary, the key differences between Memcached, Microsoft SQL Server, and SQLite lie in their database types, data persistence, complexity, scalability, ACID compliance, and security features.

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Advice on Microsoft SQL Server, Memcached, SQLite

Erin
Erin

IT Specialist

Mar 10, 2020

Needs adviceonMicrosoft SQL ServerMicrosoft SQL ServerMySQLMySQLPostgreSQLPostgreSQL

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:

  1. 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?
  2. 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
Dimelo
Dimelo

Nov 5, 2020

Needs adviceonSQLiteSQLiteMySQLMySQLPostgreSQLPostgreSQL

I need to add a DBMS to my stack, but I don't know which. I'm tempted to learn SQLite since it would be useful to me with its focus on local access without concurrency. However, doing so feels like I would be defeating the purpose of trying to expand my skill set since it seems like most enterprise applications have the opposite requirements.

To be able to apply what I learn to more projects, what should I try to learn? MySQL? PostgreSQL? Something else? Is there a comfortable middle ground between high applicability and ease of use?

671k views671k
Comments
Stephen
Stephen

Senior DevOps Engineer at Vital Beats

Nov 9, 2020

Review

A question you might want to think about is "What kind of experience do I want to gain, by using a DBMS?". If your aim is to have experience with SQL and any related libraries and frameworks for your language of choice (python, I think?), then it kind of doesn't matter too much which you pick so much. As others have said, SQLite would offer you the ability to very easily get started, and would give you a reasonably standard (if a little basic) SQL dialect to work with.

If your aim is actually to have a bit of "operational" experience, in terms of things like what command line tools might be available as standard for the DBMS, understanding how the DBMS handles multiple databases, when to use multiple schemas vs multiple databases, some basic privilege management etc. Then I would recommend PostgreSQL. SQLite's simplicity actually avoids most of these experiences, which is not helpful to you if that is what you hope to learn. MySQL has a few "quirks" to how it manages things like multiple databases, which may lead you to making less good decisions if you tried to take your experience over to different DBMS, especially in bigger enterprise roles. PostgreSQL is kind of a happy middle ground here, with the ability to start PostgreSQL servers via docker or docker-compose making the actual day-to-day management pretty easy, while still giving you experience of the kinds of considerations I have listed above.

At Vital Beats we make use of PostgreSQL, largely because it offers us a happy balance between good management and backup of data, and good standard command line tools, which is essential for us where we are deploying our solutions within Kubernetes / docker, and so more graphical tools are not always appropriate for us. PostgreSQL is also pretty universally supported in terms of language libraries and frameworks, without having to make compromises on how we want to store and layout our data.

316k views316k
Comments

Detailed Comparison

Microsoft SQL Server
Microsoft SQL Server
Memcached
Memcached
SQLite
SQLite

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.

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.

Statistics
GitHub Stars
-
GitHub Stars
14.0K
GitHub Stars
-
GitHub Forks
-
GitHub Forks
3.3K
GitHub Forks
-
Stacks
21.3K
Stacks
7.9K
Stacks
19.9K
Followers
15.5K
Followers
5.7K
Followers
15.2K
Votes
540
Votes
473
Votes
535
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
    Data pages is only 8k
  • 1
    The maximum number of connections is only 14000 connect
  • 1
    Replication can loose the data
Pros
  • 139
    Fast object cache
  • 129
    High-performance
  • 91
    Stable
  • 65
    Mature
  • 33
    Distributed caching system
Cons
  • 2
    Only caches simple types
Pros
  • 163
    Lightweight
  • 135
    Portable
  • 122
    Simple
  • 81
    Sql
  • 29
    Preinstalled on iOS and Android
Cons
  • 2
    Not for multi-process of multithreaded apps
  • 1
    Needs different binaries for each platform

What are some alternatives to Microsoft SQL Server, Memcached, SQLite?

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.

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.

MariaDB

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

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.

Oracle

Oracle

Oracle Database is an RDBMS. An RDBMS that implements object-oriented features such as user-defined types, inheritance, and polymorphism is called an object-relational database management system (ORDBMS). Oracle Database has extended the relational model to an object-relational model, making it possible to store complex business models in a relational database.

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