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  1. Stackups
  2. Application & Data
  3. Databases
  4. Databases
  5. SQLite vs rqlite

SQLite vs rqlite

OverviewDecisionsComparisonAlternatives

Overview

SQLite
SQLite
Stacks19.9K
Followers15.2K
Votes535
rqlite
rqlite
Stacks9
Followers38
Votes1
GitHub Stars17.1K
Forks754

SQLite vs rqlite: What are the differences?

# Introduction
When considering database solutions for your project, it's essential to compare the key differences between SQLite and rqlite to make an informed decision.

1. **Scalability**: SQLite is designed to be embedded within applications and is suitable for small to medium-sized databases, while rqlite is built to distribute and scale out across multiple nodes. This allows rqlite to handle larger datasets and heavier workloads compared to SQLite.
   
2. **Consistency**: SQLite follows an ACID (Atomicity, Consistency, Isolation, Durability) model, ensuring strong consistency in transactions within a single database file. On the other hand, rqlite is a distributed system and provides eventual consistency, sacrificing immediate consistency for scalability and fault tolerance across multiple nodes.
   
3. **High Availability**: rqlite offers high availability by replicating data across multiple nodes, allowing for failover capabilities and ensuring that the database is still accessible even if one or more nodes fail. In contrast, SQLite does not provide built-in high availability features as it is typically used as an embedded database within a single application.
   
4. **Concurrency Control**: SQLite uses a locking mechanism to manage concurrent access to the database, which may cause contention in high-traffic scenarios. rqlite uses the Raft consensus algorithm for distributed coordination, providing better concurrency control and avoiding bottlenecks when multiple nodes need to access the database simultaneously.
   
5. **Performance**: Due to its embedded design, SQLite may offer better performance for single-node applications with fewer concurrent connections. However, rqlite's distributed architecture enables it to scale horizontally and handle a higher number of read and write requests across multiple nodes, making it more suitable for large-scale applications with high throughput requirements.
   
6. **Deployment Complexity**: While SQLite is easy to deploy within an application requiring minimal setup, rqlite requires configuring and managing a cluster of nodes for distributed deployment. This added complexity in setting up and maintaining a rqlite cluster may be a trade-off for its scalability and fault tolerance capabilities.

In Summary, understanding the key differences between SQLite and rqlite, such as scalability, consistency, high availability, concurrency control, performance, and deployment complexity, can help you choose the right database solution for your specific project requirements.

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Advice on SQLite, rqlite

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

SQLite
SQLite
rqlite
rqlite

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.

rqlite is a distributed relational database, which uses SQLite as its storage engine. rqlite uses Raft to achieve consensus across all the instances of the SQLite databases, ensuring that every change made to the system is made to a quorum of SQLite databases, or none at all.

Statistics
GitHub Stars
-
GitHub Stars
17.1K
GitHub Forks
-
GitHub Forks
754
Stacks
19.9K
Stacks
9
Followers
15.2K
Followers
38
Votes
535
Votes
1
Pros & Cons
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
Pros
  • 1
    So easy

What are some alternatives to SQLite, rqlite?

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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