Overview

SQLite

Stacks19.5K

Followers15.2K

Votes535

WatermelonDB

Stacks12

Followers123

Votes1

GitHub Stars11.3K

Forks626

SQLite vs WatermelonDB: What are the differences?

Introduction:

SQLite and WatermelonDB are both database management systems that can be used in web development. However, there are several key differences between the two.

Data Synchronization: SQLite is a traditional client-side database that runs directly on the device or the server. On the other hand, WatermelonDB is a client-to-server database that enables real-time and bi-directional data synchronization between clients and servers. This means that multiple clients can access and modify the database simultaneously, ensuring data integrity and consistency across all devices.
Data Querying: SQLite uses SQL (Structured Query Language) for data querying and manipulation. Developers can write complex SQL queries to retrieve and manipulate data from the database. WatermelonDB, on the other hand, uses a more efficient and streamlined query language called QueryDSL. It allows for powerful and flexible querying of data using a simple and intuitive syntax.
Offline Support: SQLite does not have built-in offline support. It requires an internet connection to access the database. WatermelonDB, on the other hand, is designed to work seamlessly offline. It has built-in support for caching data on the client-side, allowing users to access and modify data even when a network connection is not available. Once the connection is restored, the changes are automatically synced with the server.
Performance: SQLite is known for its high performance and efficiency. It is a lightweight and standalone database system that can handle large amounts of data with minimal resource usage. WatermelonDB takes advantage of SQLite as a storage engine but adds its own optimizations for better performance in a client-to-server environment. It utilizes advanced techniques, such as automatic data batching and smart indexing, to enhance query performance.
Schema Management: In SQLite, the database schema needs to be managed manually. Developers have to write and execute SQL statements to create, modify, and delete tables and columns. WatermelonDB, on the other hand, provides a more convenient and declarative way of managing the schema. It provides an intuitive schema definition language that allows developers to define the database schema in a more concise and structured manner.
Integration with Frameworks: SQLite can be easily integrated with various programming languages and frameworks. It provides native support and APIs for popular programming languages like C, C++, Java, Python, and more. WatermelonDB, on the other hand, is specifically designed for JavaScript and React Native development. It integrates seamlessly with modern JavaScript frameworks like React and React Native, providing a more intuitive and seamless development experience.

In summary, SQLite is a traditional client-side database that relies on SQL for querying and lacks built-in offline support, while WatermelonDB is a client-to-server database with real-time data synchronization, optimized performance, and offline support. WatermelonDB also offers a more streamlined query language, schema management, and seamless integration with JavaScript frameworks.

Advice on SQLite, WatermelonDB

Dimelo

Nov 5, 2020

Needs adviceon

SQLite

MySQL

PostgreSQL

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

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

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	WatermelonDB
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.	WatermelonDB is a new way of dealing with user data in React Native and React web apps. It's optimized for building complex applications in React Native, and the number one goal is real-world performance. In simple words, your app must launch fast.
Statistics
GitHub Stars -	GitHub Stars 11.3K
GitHub Forks -	GitHub Forks 626
Stacks 19.5K	Stacks 12
Followers 15.2K	Followers 123
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 Undefined is not an object (evaluating 'columnSchema.ty
Integrations
No integrations available	RxJS React React Native

What are some alternatives to SQLite, WatermelonDB?

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

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 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 is a database management and analysis system for e-commerce, line-of-business, and data warehousing solutions.

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 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

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 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

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 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.