What is DBFlow and what are its top alternatives?
Top Alternatives to DBFlow
The Realm Mobile Platform is a next-generation data layer for applications. Realm is reactive, concurrent, and lightweight, allowing you to work with live, native objects. ...
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. ...
It is an open source Android ORM making development for SQLite databases fun again. It relieves developers from dealing with low-level database requirements while saving development time. ...
Hibernate is a suite of open source projects around domain models. The flagship project is Hibernate ORM, the Object Relational Mapper. ...
Sequelize is a promise-based ORM for Node.js and io.js. It supports the dialects PostgreSQL, MySQL, MariaDB, SQLite and MSSQL and features solid transaction support, relations, read replication and more. ...
SQLAlchemy is the Python SQL toolkit and Object Relational Mapper that gives application developers the full power and flexibility of SQL. ...
Doctrine 2 sits on top of a powerful database abstraction layer (DBAL). One of its key features is the option to write database queries in a proprietary object oriented SQL dialect called Doctrine Query Language (DQL), inspired by Hibernates HQL. ...
It is an object-relational mapper that enables .NET developers to work with relational data using domain-specific objects. It eliminates the need for most of the data-access code that developers usually need to write. ...
DBFlow alternatives & related posts
related Realm posts
related SQLite posts
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?
SQLite is a tricky beast. It's great if you're working single-threaded, but a Terrible Idea if you've got more than one concurrent connection. You use it because it's easy to setup, light, and portable (it's just a file).
In Paperless, we've built a self-hosted web application, so it makes sense to standardise on something small & light, and as we don't have to worry about multiple connections (it's just you using the app), it's a perfect fit.
For users wanting to scale Paperless up to a multi-user environment though, we do provide the hooks to switch to PostgreSQL .
related GreenDAO posts
related Hibernate posts
related Sequelize posts
What is the best way to increase your income as a freelancer in 2019? What frameworks should be the best to learn? React Node.js Docker Kubernetes Sequelize Mongoose MongoDB ExpressJS hapi Based on trends I've picked up a JS full stack. If you need to work under startups you may replace React with Vue.js . If you want to work in outsourcing Angular 2+ may be better.
What is your opinion?
On backend, ExpressJS is a good place to start. Learn how to build semantic REST APIs that pull data from a database. MongoDB is fine, but I would suggest using Mongoose along with it to avoid nesting objects too much. You could alternatively use a SQL database like PostgreSQL, with an ORM like Sequelize to manage the data.
related SQLAlchemy posts
Merging Django ORM with SQLAlchemy for Easier Data Analysis (Video Inside)
Development of products with Django framework is usually easy and straightforward; great documentation, many tools out of the box, plenty of open source libraries and big community. Django ORM takes full control about SQL layer protecting you from mistakes, and underlying details of queries so you can spend more time on designing and building your application structure in Python code. However, sometimes such behavior may hurt - for example, when you’re building a project related to data analysis. Building advanced queries with Django is not very easy; it’s hard to read (in Python) and hard to understand what’s going on in SQL-level without logging or printing generated SQL queries somewhere. Moreover, such queries could not be efficient enough, so this will hit you back when you load more data into DB to play with. In one moment, you can find yourself doing too much raw SQL through Django cursor, and this is the moment when you should do a break and take a look on another interesting tool, which is placed right between ORM layer and the layer of raw SQL queries.