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  1. Stackups
  2. Application & Data
  3. Relational Databases
  4. SQL Database As A Service
  5. Amazon RDS vs SQLite

Amazon RDS vs SQLite

OverviewDecisionsComparisonAlternatives

Overview

Amazon RDS
Amazon RDS
Stacks16.2K
Followers10.8K
Votes761
SQLite
SQLite
Stacks19.9K
Followers15.2K
Votes535

Amazon RDS vs SQLite: What are the differences?

Key Differences between Amazon RDS and SQLite

Amazon RDS and SQLite are two popular database management systems that have distinct features and capabilities. Here are six key differences between Amazon RDS and SQLite:

  1. Scalability: Amazon RDS is designed for scalable and flexible database deployments, allowing users to easily manage the storage capacity as their needs grow. On the other hand, SQLite does not have built-in scalability features and is more suitable for smaller-scale applications with limited storage requirements.

  2. Cloud vs. Local: Amazon RDS is a cloud-based service that provides high availability and reliability by hosting the databases on the cloud infrastructure. SQLite, on the other hand, is a self-contained database engine that runs locally, making it suitable for offline or embedded applications where cloud connectivity is not always available.

  3. Multi-user Support: Amazon RDS offers robust multi-user support, making it suitable for applications with multiple concurrent users. It provides features such as automated backups, replication, and failover to ensure data integrity. SQLite, on the other hand, is primarily designed for single-user applications and does not provide built-in support for concurrent access.

  4. Performance and Scalability: Amazon RDS is built to handle high traffic and large datasets, offering better performance and scalability compared to SQLite. It leverages cloud-based infrastructure and can be configured for automatic scaling and load balancing. SQLite, on the other hand, is optimized for local storage and performs well in low to moderate traffic scenarios.

  5. Database Administration: Amazon RDS provides a managed database service where tasks such as patching, backups, and monitoring are handled by Amazon. Users only need to focus on application development and usage. SQLite, in contrast, requires manual administration and maintenance tasks such as backups, updates, and monitoring to be performed by the application developer or administrator.

  6. Cost: Amazon RDS is a paid service and the cost depends on factors such as the instance size, storage, and data transfer. It offers different pricing tiers and flexible billing options. SQLite, on the other hand, is free and open-source, making it a cost-effective choice for small-scale applications or projects with limited budgets.

In summary, Amazon RDS provides a scalable, cloud-based database management service suitable for multi-user applications with high traffic and storage requirements. SQLite, on the other hand, is a self-contained, local database engine optimized for single-user or offline applications with limited scalability and smaller datasets.

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Advice on Amazon RDS, 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
Anonymous
Anonymous

Oct 29, 2019

Needs advice

Hi everyone! I am a high school student, starting a massive project. I'm building a system for a boarding school to be better connected to their students and be more efficient with information. In the meantime, I am developing a website and an android app. What's the best datastore I can use? I need to be able to access student data on the app from the main database and send push notifications. Also feed updates. What's the best approach? What's the best tool I can use to deploy the website and the database? One for testing and prototyping, and an official one... Thanks in advance!!!!

366k views366k
Comments

Detailed Comparison

Amazon RDS
Amazon RDS
SQLite
SQLite

Amazon RDS gives you access to the capabilities of a familiar MySQL, Oracle or Microsoft SQL Server database engine. This means that the code, applications, and tools you already use today with your existing databases can be used with Amazon RDS. Amazon RDS automatically patches the database software and backs up your database, storing the backups for a user-defined retention period and enabling point-in-time recovery. You benefit from the flexibility of being able to scale the compute resources or storage capacity associated with your Database Instance (DB Instance) via a single API call.

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.

Pre-configured Parameters;Monitoring and Metrics;Automatic Software Patching;Automated Backups;DB Snapshots;DB Event Notifications;Multi-Availability Zone (Multi-AZ) Deployments;Provisioned IOPS;Push-Button Scaling;Automatic Host Replacement;Replication;Isolation and Security
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Statistics
Stacks
16.2K
Stacks
19.9K
Followers
10.8K
Followers
15.2K
Votes
761
Votes
535
Pros & Cons
Pros
  • 165
    Reliable failovers
  • 156
    Automated backups
  • 130
    Backed by amazon
  • 92
    Db snapshots
  • 87
    Multi-availability
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 Amazon RDS, 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.

Memcached

Memcached

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.

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.

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