Database Comparison

SQLite vs MySQL: Which Database Should You Use in 2026?

SQLite and MySQL are both SQL databases, but they solve fundamentally different problems. This guide covers architecture, performance, syntax differences, concurrency, and when to use each one.

Mar 12, 2026 18 min read

Quick Comparison Table

Before diving into the details, here is a side-by-side overview of SQLite and MySQL across the dimensions that matter most:

Feature	SQLite	MySQL
Architecture	Serverless, embedded. Runs inside your app process.	Client-server. Runs as a separate daemon/service.
Server Required	No. Just a single file on disk.	Yes. Requires installation and configuration.
Concurrency	Single writer at a time. Multiple readers with WAL mode.	Full multi-user. Row-level locking, connection pooling.
Max DB Size	281 TB (theoretical). Practical limit around 1-10 GB.	No hard limit. Handles terabytes in production.
Data Types	Type affinity (5 storage classes). Flexible.	Strict type system. Many specialized types.
Setup Complexity	Zero. No install, no config, no users.	Moderate. Install server, create users, set permissions.
Best For	Mobile apps, prototyping, embedded systems, small sites.	Web apps, multi-user systems, large-scale production.

Both are SQL databases. Both use the same query language at their core. But the architectural difference between embedded and client-server changes everything about when and how you should use them.

Architecture: Embedded vs Client-Server

The architecture difference is the single most important distinction between SQLite and MySQL. Every other difference flows from this one decision.

SQLite: serverless and embedded

SQLite is not a separate program. It is a C library that you link directly into your application. When your app reads or writes data, SQLite operates on a single file on disk. There is no server process, no network communication, no socket connections. Your application IS the database server.

The entire database (tables, indexes, schema, data) lives in one cross-platform file. You can copy that file to another machine, email it, put it in a Git repository, or back it up with a simple file copy. There is nothing else to manage.

# Python - SQLite just works. No server needed.
import sqlite3

# This creates the database file if it does not exist
conn = sqlite3.connect('myapp.db')
cursor = conn.cursor()

cursor.execute('''
    CREATE TABLE IF NOT EXISTS users (
        id INTEGER PRIMARY KEY AUTOINCREMENT,
        name TEXT NOT NULL,
        email TEXT UNIQUE NOT NULL,
        created_at TEXT DEFAULT CURRENT_TIMESTAMP
    )
''')

cursor.execute("INSERT INTO users (name, email) VALUES (?, ?)",
               ("Alice", "alice@example.com"))
conn.commit()
conn.close()
# That is it. No server to install, no ports to configure.

MySQL: client-server with network access

MySQL runs as a standalone server process (mysqld) that listens on a network port (default 3306). Your application connects to it as a client, sends SQL queries over the network, and receives results back. Multiple clients can connect simultaneously from different machines.

This architecture adds complexity but enables features that SQLite cannot provide: user authentication, access control, replication to other servers, and concurrent access from many applications at once.

# Python - MySQL requires a running server
import mysql.connector

# Must have MySQL server running and user created first
conn = mysql.connector.connect(
    host='localhost',
    port=3306,
    user='app_user',
    password='secure_password',
    database='myapp'
)
cursor = conn.cursor()

cursor.execute('''
    CREATE TABLE IF NOT EXISTS users (
        id INT AUTO_INCREMENT PRIMARY KEY,
        name VARCHAR(100) NOT NULL,
        email VARCHAR(255) UNIQUE NOT NULL,
        created_at TIMESTAMP DEFAULT CURRENT_TIMESTAMP
    )
''')

cursor.execute("INSERT INTO users (name, email) VALUES (%s, %s)",
               ("Alice", "alice@example.com"))
conn.commit()
conn.close()

Notice the differences already: MySQL needs a host, port, username, and password. It uses AUTO_INCREMENT instead of AUTOINCREMENT. It uses VARCHAR with length limits instead of just TEXT. These small syntax differences add up across a real application.

Setup and Configuration

SQLite: zero configuration

Setting up SQLite means doing nothing. There is no installation step. Python, PHP, and most languages include SQLite bindings by default. You create a database by opening a connection to a filename. If the file does not exist, SQLite creates it.

There are no users to create, no permissions to set, no configuration files to edit, no services to start, no ports to open, and no logs to monitor. The database is just a file, and your application manages access to it.

# SQLite setup: literally nothing
sqlite3 myapp.db "CREATE TABLE test (id INTEGER PRIMARY KEY, name TEXT);"
# Done. Database exists and is ready.

MySQL: install, configure, secure

MySQL requires a multi-step setup process. You install the server, run the security script, create databases, create users, and grant permissions. On a production server, you also configure buffer sizes, connection limits, logging, and backups.

# MySQL setup on Ubuntu
sudo apt install mysql-server
sudo mysql_secure_installation

# Create database and user
sudo mysql -u root -p
CREATE DATABASE myapp;
CREATE USER 'app_user'@'localhost' IDENTIFIED BY 'secure_password';
GRANT ALL PRIVILEGES ON myapp.* TO 'app_user'@'localhost';
FLUSH PRIVILEGES;
EXIT;

This is not necessarily a downside. The setup process gives you user management, access control, and network configuration. But for a prototype, a mobile app, or a developer tool, it is overhead you may not need.

Syntax Differences

Both SQLite and MySQL speak SQL, but there are meaningful differences in syntax and behavior. These catch developers who switch between the two or who need to write queries that work on both. If you use AI2SQL, it handles these dialect differences automatically.

Auto-increment primary keys

-- SQLite
CREATE TABLE users (
    id INTEGER PRIMARY KEY AUTOINCREMENT,
    name TEXT NOT NULL
);

-- MySQL
CREATE TABLE users (
    id INT AUTO_INCREMENT PRIMARY KEY,
    name VARCHAR(100) NOT NULL
);

SQLite uses AUTOINCREMENT (one word). MySQL uses AUTO_INCREMENT (with underscore). In SQLite, you actually do not need AUTOINCREMENT at all. An INTEGER PRIMARY KEY column automatically becomes a rowid alias and auto-increments. The AUTOINCREMENT keyword just prevents rowid reuse after deletion.

Type affinity vs strict types

-- SQLite: type affinity means this works (even though it should not)
CREATE TABLE products (price REAL);
INSERT INTO products (price) VALUES ('not a number');
-- SQLite stores it as TEXT. No error.

-- MySQL: strict types enforce data integrity
CREATE TABLE products (price DECIMAL(10,2));
INSERT INTO products (price) VALUES ('not a number');
-- ERROR 1366: Incorrect decimal value

This is one of the biggest gotchas. SQLite lets you put any value in any column regardless of the declared type. MySQL enforces types strictly. This means SQLite is more forgiving during development but can hide data quality issues that surface later in production.

ALTER TABLE limitations

-- MySQL: full ALTER TABLE support
ALTER TABLE users ADD COLUMN age INT DEFAULT 0;
ALTER TABLE users DROP COLUMN age;
ALTER TABLE users MODIFY COLUMN name VARCHAR(200);
ALTER TABLE users RENAME COLUMN name TO full_name;

-- SQLite (before 3.35.0): very limited ALTER TABLE
ALTER TABLE users ADD COLUMN age INTEGER DEFAULT 0;  -- Works
ALTER TABLE users DROP COLUMN age;                    -- Works (3.35.0+)
ALTER TABLE users RENAME COLUMN name TO full_name;    -- Works (3.25.0+)
-- Cannot change column type or constraints without recreating the table

SQLite has gradually added ALTER TABLE support over the years, but it still cannot modify a column's type or constraints. The workaround is to create a new table, copy data, drop the old table, and rename the new one. MySQL handles all schema changes directly.

GLOB vs LIKE

-- SQLite supports GLOB (case-sensitive, uses * and ?)
SELECT * FROM users WHERE name GLOB 'A*';     -- Names starting with A
SELECT * FROM users WHERE name GLOB 'A??ce';  -- 5-letter names starting with A, ending with ce

-- MySQL does not have GLOB. Use LIKE or REGEXP
SELECT * FROM users WHERE name LIKE 'A%';              -- Names starting with A
SELECT * FROM users WHERE name REGEXP '^A..ce$';       -- Pattern matching

-- Both support LIKE, but case sensitivity differs
SELECT * FROM users WHERE name LIKE 'alice';
-- SQLite: case-insensitive for ASCII by default
-- MySQL: depends on collation (ci = case-insensitive, cs = case-sensitive)

Concurrency and Locking

Concurrency handling is where the architectural difference between SQLite and MySQL has the most practical impact.

SQLite: single writer, file-level locking

SQLite uses file-level locking. Only one process can write to the database at a time. When a write is in progress, other writers must wait. In the default journal mode, readers also block during writes.

WAL (Write-Ahead Logging) mode significantly improves this. With WAL enabled, readers never block writers and writers never block readers. But you still only get one writer at a time. If two processes try to write simultaneously, one gets a SQLITE_BUSY error and must retry.

-- Enable WAL mode for better concurrency
PRAGMA journal_mode=WAL;

-- Set a busy timeout so writes retry instead of failing immediately
PRAGMA busy_timeout=5000;  -- Wait up to 5 seconds

For a single-user application or a website with moderate traffic, this is perfectly fine. SQLite can handle hundreds of concurrent readers and processes writes fast enough that the single-writer limitation rarely causes problems below around 100,000 daily visitors.

MySQL: multi-user, row-level locking

MySQL (with the InnoDB engine) uses row-level locking. Multiple users can write to different rows in the same table simultaneously without blocking each other. Only operations on the same row are serialized.

-- MySQL: these can run simultaneously from different connections
-- Connection 1: updates user 1
UPDATE users SET name = 'Alice Updated' WHERE id = 1;

-- Connection 2: updates user 2 (no waiting)
UPDATE users SET name = 'Bob Updated' WHERE id = 2;

-- Connection 3: reads user 3 (no waiting, MVCC snapshot)
SELECT * FROM users WHERE id = 3;

MySQL also supports connection pooling, where a pool of database connections is shared across application threads. This is critical for web applications where each HTTP request needs database access. Connection pooling with SQLite is possible but offers fewer benefits since writes are still serialized.

Performance Comparison

Performance depends entirely on the workload. Neither database is universally faster. Here is where each one wins:

SQLite is faster for:

Single-user read operations. No network overhead, no protocol parsing, no authentication. SQLite reads data directly from the file into your application's memory. For simple queries on datasets under 1GB, SQLite is often 2-5x faster than MySQL because there is zero network latency.
Small to medium datasets. When the entire database fits in the OS page cache (typically under a few GB), SQLite's simplicity gives it a meaningful speed advantage. There is no query planner communication overhead, no result serialization over the wire.
Embedded and edge use cases. On mobile devices, IoT hardware, and edge servers, SQLite's minimal resource usage and zero-config nature make it the only practical choice. It runs in environments where MySQL simply cannot.
Bulk inserts in a single transaction. Wrapping thousands of inserts in a single SQLite transaction can be extremely fast because it writes directly to disk without network round-trips.

-- SQLite: bulk insert is blazing fast in a transaction
BEGIN TRANSACTION;
INSERT INTO logs (event, timestamp) VALUES ('page_view', '2026-03-12 10:00:00');
INSERT INTO logs (event, timestamp) VALUES ('click', '2026-03-12 10:00:01');
-- ... thousands more
COMMIT;
-- 100,000 inserts in under 1 second on modern hardware

MySQL is faster for:

Concurrent users. When 50 users are reading and writing simultaneously, MySQL's row-level locking and connection pooling keep everything running smoothly. SQLite would serialize all writes and create contention.
Large datasets. MySQL's query optimizer, buffer pool, and indexing strategies are designed for datasets measured in tens or hundreds of gigabytes. SQLite's simpler query planner works well for smaller datasets but does not optimize as aggressively for complex queries on large tables.
Write-heavy workloads. Applications with constant concurrent writes (social media, real-time analytics, messaging) need MySQL's ability to handle multiple writers in parallel.
Network access. When your database needs to serve multiple application servers, MySQL's client-server architecture is the only option. SQLite cannot be accessed over a network (without third-party tools like LiteFS or Litestream).

A practical rule of thumb: if your application has a single process accessing the database and the data fits on one machine, benchmark SQLite first. You might be surprised how far it takes you.

Data Types

The way SQLite and MySQL handle data types is fundamentally different, and this difference causes more migration bugs than any other feature.

SQLite: type affinity

SQLite has only five storage classes: NULL, INTEGER, REAL, TEXT, and BLOB. When you declare a column as VARCHAR(255) or DECIMAL(10,2), SQLite maps it to one of these five classes using affinity rules. But it does not enforce the type. You can store a string in an integer column.

-- SQLite type affinity examples
CREATE TABLE demo (
    a INTEGER,   -- Affinity: INTEGER
    b TEXT,       -- Affinity: TEXT
    c REAL,       -- Affinity: REAL
    d BLOB,       -- Affinity: BLOB (none)
    e VARCHAR(50) -- Affinity: TEXT (VARCHAR maps to TEXT)
);

-- All of these work in SQLite
INSERT INTO demo (a, b, c) VALUES ('hello', 42, 'world');
-- Column 'a' is INTEGER affinity but stores 'hello' as TEXT
-- Column 'b' is TEXT affinity but stores 42 as INTEGER
-- Column 'c' is REAL affinity but stores 'world' as TEXT

Starting with SQLite 3.37.0 (2021), you can use STRICT tables that enforce types like MySQL does. But this is opt-in and most existing SQLite databases do not use it.

MySQL: strict type system

MySQL has dozens of data types, each with specific storage sizes and validation rules:

Integers: TINYINT (1 byte), SMALLINT (2), MEDIUMINT (3), INT (4), BIGINT (8)
Decimals: DECIMAL(precision, scale), FLOAT, DOUBLE
Strings: CHAR(n), VARCHAR(n), TEXT, MEDIUMTEXT, LONGTEXT
Date/Time: DATE, TIME, DATETIME, TIMESTAMP, YEAR
Binary: BINARY, VARBINARY, BLOB, MEDIUMBLOB, LONGBLOB
Other: ENUM, SET, JSON, spatial types

MySQL enforces these types at insert time. If you try to put a string into an INT column, you get an error (in strict mode, which is the default since MySQL 5.7). This catches data quality issues immediately rather than letting bad data accumulate.

The practical impact: if you develop with SQLite and deploy with MySQL, test your data validation thoroughly. Queries that work fine in SQLite may fail in MySQL because of type enforcement. Our MySQL cheat sheet covers the full type system.

Feature Comparison

MySQL advantages

Stored procedures and functions. MySQL supports complex server-side logic written in SQL. You can encapsulate business rules in the database itself. SQLite has no stored procedure support.
Full trigger support. MySQL triggers can fire on INSERT, UPDATE, and DELETE with BEFORE and FOR EACH ROW semantics. SQLite supports triggers but with more limited functionality.
User management and permissions. MySQL has a complete authentication and authorization system. You can grant specific permissions on specific tables to specific users. SQLite has no concept of users or permissions at the database level.
Replication. MySQL supports primary-replica replication, group replication, and InnoDB Cluster for high availability. You can distribute read load across multiple servers. SQLite runs on a single machine (though tools like LiteFS add replication).
Full-text search. MySQL's FULLTEXT indexes provide built-in search with relevance scoring, boolean operators, and natural language queries. SQLite has FTS5, which is capable but requires compiling with the extension enabled.
Views with CHECK OPTION. MySQL supports updatable views with CHECK OPTION to enforce constraints. SQLite views are read-only.

SQLite advantages

Zero administration. No server to monitor, no logs to rotate, no upgrades to schedule, no security patches to apply. The database is a file. Back it up by copying the file.
Portability. A SQLite database file works on any platform without modification. Copy it from Linux to Windows to macOS to your phone. The file format is stable and guaranteed to be compatible until at least 2050.
In-memory mode. Open a database as :memory: and it runs entirely in RAM. Perfect for testing, caching, and temporary data processing. MySQL can use memory engines but they are more limited.
JSON support. SQLite's JSON1 extension provides powerful JSON functions for querying and manipulating JSON data stored in TEXT columns. You can index JSON fields and use them in WHERE clauses.
Deterministic builds. SQLite produces the same database file given the same inputs. This makes it useful for reproducible builds, data archiving, and forensics.
Tiny footprint. The SQLite library is under 1MB. It runs on everything from smartphones to satellites. MySQL's minimum installation is hundreds of megabytes.

When to Use SQLite

SQLite is the right choice in more situations than most developers realize. It is the most deployed database engine in the world (every smartphone has multiple SQLite databases), and it works well beyond mobile:

Mobile apps (iOS and Android). SQLite is the default local database for both platforms. Core Data on iOS and Room on Android both use SQLite under the hood. For on-device data storage, there is no alternative that comes close.
Desktop applications (Electron, Tauri, native). Desktop apps like Firefox, Chrome, Slack, and thousands of Electron apps use SQLite for local state, caches, and user data. If your app runs on the user's machine, use SQLite.
Embedded systems and IoT. Devices with limited resources (Raspberry Pi, industrial controllers, automotive systems) need a database that is small, fast, and requires no administration. SQLite is purpose-built for this. Check out our SQLite cheat sheet for quick reference.
Testing and prototyping. Use SQLite during development to avoid setting up a database server. Django and Rails both support SQLite for development and testing. Your tests run faster because there is no network overhead.
Small to medium websites. Sites with under 100,000 daily visitors can run on SQLite, especially with WAL mode. The Ruby on Rails community has embraced this approach, and frameworks like Litestack make it production-ready.
Data analysis and ETL. SQLite is excellent for one-off data analysis. Load a CSV file, run SQL queries, export results. No server setup, no cleanup afterward. Just delete the file when you are done.
Edge computing. Applications running at the edge (CDN workers, Cloudflare Durable Objects, fly.io) use SQLite because each edge node needs its own independent database. There is no central server in edge computing by definition.

When to Use MySQL

MySQL is the right choice when your application outgrows what a single-file database can handle. These are the scenarios where MySQL's complexity pays for itself:

Web applications with concurrent users. Any website or API where multiple users read and write simultaneously needs MySQL's row-level locking and connection pooling. E-commerce sites, SaaS applications, content management systems, and social platforms all benefit from MySQL's concurrency model.
Multi-server deployments. If your application runs on more than one server, SQLite cannot share its file across machines. MySQL's client-server architecture lets any number of application servers connect to a single database. Add read replicas to scale reads horizontally.
User authentication and access control. When different users or services need different levels of database access, MySQL's built-in permission system handles this at the database level. SQLite relies entirely on file system permissions.
Datasets larger than a few gigabytes. While SQLite can technically handle large databases, MySQL's query optimizer, buffer pool management, and indexing strategies are designed for large-scale data. If your database is growing past 1-5 GB and receiving concurrent access, MySQL will perform better.
Team collaboration. When multiple developers need to work with the same data (staging database, shared dev environment), MySQL provides a centralized database that everyone connects to. SQLite requires each developer to have their own copy.
High availability requirements. MySQL supports automatic failover, replication, and clustering. If your application cannot tolerate database downtime, MySQL's replication features (or managed services like Amazon RDS, PlanetScale, or Vitess) provide the reliability guarantees you need.
WordPress and PHP applications. MySQL is the default database for WordPress, Laravel, Drupal, and most PHP frameworks. The ecosystem, tooling, hosting support, and documentation assume MySQL.

Migration: SQLite to MySQL

Many projects start with SQLite and later need to migrate to MySQL as they grow. This is a valid strategy, but be aware of the key differences that will bite you during migration:

Data type mapping

-- SQLite types        → MySQL equivalents
-- INTEGER             → INT or BIGINT
-- REAL                → DOUBLE or DECIMAL
-- TEXT                → VARCHAR(n) or TEXT
-- BLOB               → BLOB
-- INTEGER PRIMARY KEY → INT AUTO_INCREMENT PRIMARY KEY

-- Watch out for:
-- SQLite BOOLEAN      → MySQL TINYINT(1) or BOOLEAN
-- SQLite datetime     → MySQL DATETIME or TIMESTAMP
-- SQLite no ENUM      → MySQL ENUM('value1', 'value2')

Syntax changes required

-- AUTOINCREMENT → AUTO_INCREMENT
-- SQLite
CREATE TABLE orders (id INTEGER PRIMARY KEY AUTOINCREMENT);
-- MySQL
CREATE TABLE orders (id INT AUTO_INCREMENT PRIMARY KEY);

-- Date functions differ
-- SQLite
SELECT date('now', '-7 days');
SELECT strftime('%Y-%m', created_at);
-- MySQL
SELECT DATE_SUB(NOW(), INTERVAL 7 DAY);
SELECT DATE_FORMAT(created_at, '%Y-%m');

-- String concatenation
-- SQLite
SELECT first_name || ' ' || last_name AS full_name FROM users;
-- MySQL
SELECT CONCAT(first_name, ' ', last_name) AS full_name FROM users;

If you are migrating queries between SQLite and MySQL, AI2SQL's SQLite to MySQL converter handles these dialect differences automatically. Paste your SQLite query, select MySQL as the target, and get working MySQL syntax.

What to test after migration

Data type enforcement: values that SQLite accepted silently may fail in MySQL
Case sensitivity: MySQL table names are case-sensitive on Linux but not on macOS/Windows
NULL handling: subtle differences in how NULLs interact with UNIQUE constraints
Date and time functions: completely different function names and formats
GROUP BY behavior: MySQL's ONLY_FULL_GROUP_BY mode is stricter than SQLite

How AI2SQL Helps

Whether you are working with SQLite or MySQL, AI2SQL eliminates the friction of remembering syntax differences between database dialects.

Write queries in plain English. Describe what you need, select your target database (SQLite or MySQL), and AI2SQL generates the correct syntax. No need to remember whether it is AUTOINCREMENT or AUTO_INCREMENT, strftime or DATE_FORMAT.

Convert between dialects. Have a SQLite query that needs to run on MySQL? Paste it into AI2SQL's converter and get working MySQL syntax with all the type, function, and syntax differences handled automatically.

Learn the differences. Every converted query comes with explanations of what changed and why. This builds your understanding of both database dialects over time, so you write better SQL regardless of which database you use.

If you are building with SQLite, MySQL, or both, try AI2SQL free and stop worrying about syntax.

Frequently Asked Questions

What is the main difference between SQLite and MySQL?

SQLite is a serverless, embedded database that stores everything in a single file and runs inside your application process. MySQL is a client-server database that runs as a separate service, supports multiple concurrent users, and communicates over a network. SQLite requires zero configuration while MySQL requires installation, user setup, and server management.

Is SQLite faster than MySQL?

SQLite is faster for single-user read operations, small to medium datasets, and embedded use cases because it has no network overhead and no client-server communication. MySQL is faster for concurrent multi-user access, large datasets exceeding 1GB, and write-heavy workloads because it supports row-level locking, connection pooling, and query caching across connections.

Can SQLite handle a production website?

Yes, SQLite can handle production websites with moderate traffic, roughly under 100,000 visits per day. Many successful websites run on SQLite, including those built with Ruby on Rails and Django. However, for high-traffic sites with many concurrent writers or multi-server deployments, MySQL or PostgreSQL is a better choice because SQLite only allows one writer at a time.

How do I migrate from SQLite to MySQL?

Migrating from SQLite to MySQL requires adjusting data types (SQLite uses type affinity while MySQL uses strict types), changing AUTOINCREMENT to AUTO_INCREMENT, updating date and time functions, and handling differences in ALTER TABLE support. AI2SQL can help convert your SQLite queries to MySQL syntax automatically. You can also use tools like sqlite3-to-mysql for schema and data migration.

Should I use SQLite or MySQL for a mobile app?

For local data storage on mobile devices, SQLite is the clear choice. It is embedded in both Android and iOS by default, requires no server, and works offline. If your mobile app needs to sync data with a backend or share data between users, use MySQL (or another server database) on the backend while keeping SQLite on the device for local caching and offline support.