StackShareStackShare
Follow on
StackShare

Discover and share technology stacks from companies around the world.

Follow on

© 2025 StackShare. All rights reserved.

Product

  • Stacks
  • Tools
  • Feed

Company

  • About
  • Contact

Legal

  • Privacy Policy
  • Terms of Service
  1. Stackups
  2. Application & Data
  3. Databases
  4. Databases
  5. Memcached vs SQLite

Memcached vs SQLite

OverviewDecisionsComparisonAlternatives

Overview

Memcached
Memcached
Stacks7.9K
Followers5.7K
Votes473
GitHub Stars14.0K
Forks3.3K
SQLite
SQLite
Stacks19.9K
Followers15.2K
Votes535

Memcached vs SQLite: What are the differences?

Key differences between Memcached and SQLite

Memcached and SQLite are both popular data management systems, but they have some key differences that set them apart. Here are six specific differences between the two:

  1. Data Storage: Memcached is a distributed memory caching system, while SQLite is a file-based relational database management system. Memcached stores data in the server's RAM, making it extremely fast for retrieving frequently accessed data. On the other hand, SQLite stores data in disk files, making it better suited for persistent storage and larger volumes of data.

  2. Data Structure: Memcached is a key-value store, where data is stored and retrieved based on unique keys. It does not support complex data structures like tables or indexes. SQLite, on the other hand, supports the use of structured tables with rows, columns, and indexes. This allows for more advanced data organization and querying capabilities.

  3. Concurrency: Memcached is designed to handle high levels of concurrent access, making it suitable for use in distributed and highly scalable environments. It uses a multi-threaded architecture and allows for parallel access to data. SQLite, on the other hand, is more suited for single-user or small-scale applications, as it relies on file-level locking for concurrency control.

  4. Transaction Support: Memcached does not provide built-in support for transactions. It is primarily used for caching and does not guarantee atomicity or consistency in data operations. SQLite, on the other hand, supports full ACID (Atomicity, Consistency, Isolation, Durability) properties and allows for transactional control over data operations.

  5. Query Language: While Memcached does not provide a query language, SQLite supports the SQL (Structured Query Language) standard. This allows for complex data querying and manipulation using SQL statements like SELECT, INSERT, UPDATE, and DELETE. SQLite's support for SQL makes it more suitable for applications that require powerful querying capabilities.

  6. Deployment and Setup: Memcached is typically used as an in-memory caching layer in front of a web application or database. It is easy to deploy and does not require complex setup or configuration. SQLite, on the other hand, requires setting up a database file and configuring access permissions. It is often used as an embedded database within applications and requires more effort for initial setup.

In summary, Memcached is a distributed caching system with fast in-memory storage and limited functionality, while SQLite is a file-based relational database with robust data querying and transactional support. The choice between Memcached and SQLite depends on the specific requirements of the application, such as data volume, concurrency needs, and the need for transactional control.

Share your Stack

Help developers discover the tools you use. Get visibility for your team's tech choices and contribute to the community's knowledge.

View Docs
CLI (Node.js)
or
Manual

Advice on Memcached, SQLite

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?

670k views670k
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
Jasmine
Jasmine

Feb 12, 2021

Decided

Backend:

  • Considering that our main app functionality involves data processing, we chose Python as the programming language because it offers many powerful math libraries for data-related tasks. We will use Flask for the server due to its good integration with Python. We will use a relational database because it has good performance and we are mostly dealing with CSV files that have a fixed structure. We originally chose SQLite, but after realizing the limitations of file-based databases, we decided to switch to PostgreSQL, which has better compatibility with our hosting service, Heroku.
175k views175k
Comments

Detailed Comparison

Memcached
Memcached
SQLite
SQLite

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
14.0K
GitHub Stars
-
GitHub Forks
3.3K
GitHub Forks
-
Stacks
7.9K
Stacks
19.9K
Followers
5.7K
Followers
15.2K
Votes
473
Votes
535
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
  • 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 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.

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.

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.

Related Comparisons

Bootstrap
Materialize

Bootstrap vs Materialize

Laravel
Django

Django vs Laravel vs Node.js

Bootstrap
Foundation

Bootstrap vs Foundation vs Material UI

Node.js
Spring Boot

Node.js vs Spring-Boot

Liquibase
Flyway

Flyway vs Liquibase