Overview

MongoDB

Stacks96.6K

Followers82.0K

Votes4.1K

GitHub Stars27.7K

Forks5.7K

RxDB

Stacks59

Followers179

Votes63

GitHub Stars22.8K

Forks1.1K

MongoDB vs RxDB: What are the differences?

Introduction:

In this article, we will discuss the key differences between MongoDB and RxDB. Both MongoDB and RxDB are popular database technologies, but they have some distinct features and use cases. Below are six key differences that set them apart from each other.

Data Modeling: MongoDB is a NoSQL database that follows a flexible document-based data model, where data is stored as JSON-like documents. It allows dynamic schema and supports nested data structures. On the other hand, RxDB is a client-side database that stores data in local instances of IndexedDB, allowing offline-first applications. It uses a structured schema defined by models and makes use of observables for reactive programming.
Synchronization: MongoDB is focused on server-side storage and synchronization, providing native replication and sharding capabilities for scaling horizontally and ensuring data availability. It can handle large-scale distributed systems efficiently. Conversely, RxDB is primarily designed for client-side applications and provides real-time synchronization between local instances. It enables seamless data replication and conflict resolution across devices and supports offline-first functionality.
Querying and Indexing: MongoDB offers comprehensive querying capabilities using a powerful query language with support for various operators and aggregation pipelines. It allows indexing on fields for enhanced query performance. RxDB provides query methods similar to MongoDB but with limited functionality. It supports filtering, sorting, and indexing of data on the client-side only. However, querying is optimized for reactive programming and live updates.
Integration: MongoDB integrates well with different programming languages and frameworks, making it versatile for various development scenarios. It has extensive driver support, allowing developers to use MongoDB with ease. RxDB, on the other hand, is specifically built for JavaScript and can be used with popular front-end frameworks like React and Angular. It provides seamless integration with RxJS, enabling reactive programming paradigms.
Scalability: MongoDB is designed to handle large amounts of data and scale horizontally through sharding. It can distribute data across multiple servers, providing high availability and scalability. RxDB, being a client-side database, does not offer the same scalability as MongoDB. It focuses on synchronizing and replicating data across devices rather than scaling server-side infrastructures.
Use Cases: MongoDB is widely used in different industries and applications where scalability, high-performance, and flexible data modeling are required. It is suitable for large-scale and complex systems. RxDB, on the other hand, is more suited for client-side applications that require offline-first functionality, real-time synchronization, and reactive programming.

In summary, MongoDB is a powerful server-side NoSQL database that excels in scalability, flexibility, and performance. It is suitable for complex distributed systems. RxDB, on the other hand, is a client-side database focused on offline-first applications, real-time synchronization, and reactive programming. It offers simplicity and ease of use for JavaScript-based front-end applications.

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Advice on MongoDB, RxDB

George

Student

Mar 18, 2020

Needs adviceon

PostgreSQL

Python

Django

Hello everyone,

Well, I want to build a large-scale project, but I do not know which ORDBMS to choose. The app should handle real-time operations, not chatting, but things like future scheduling or reminders. It should be also really secure, fast and easy to use. And last but not least, should I use them both. I mean PostgreSQL with Python / Django and MongoDB with Node.js? Or would it be better to use PostgreSQL with Node.js?

*The project is going to use React for the front-end and GraphQL is going to be used for the API.

Thank you all. Any answer or advice would be really helpful!

620k views620k

Comments

Ido

Mar 6, 2020

Decided

My data was inherently hierarchical, but there was not enough content in each level of the hierarchy to justify a relational DB (SQL) with a one-to-many approach. It was also far easier to share data between the frontend (Angular), backend (Node.js) and DB (MongoDB) as they all pass around JSON natively. This allowed me to skip the translation layer from relational to hierarchical. You do need to think about correct indexes in MongoDB, and make sure the objects have finite size. For instance, an object in your DB shouldn't have a property which is an array that grows over time, without limit. In addition, I did use MySQL for other types of data, such as a catalog of products which (a) has a lot of data, (b) flat and not hierarchical, (c) needed very fast queries.

575k views575k

Comments

Mike

Mar 20, 2020

Needs advice

We Have thousands of .pdf docs generated from the same form but with lots of variability. We need to extract data from open text and more important - from tables inside the docs. The output of Couchbase/Mongo will be one row per document for backend processing. ADOBE renders the tables in an unusable form.

241k views241k

Comments

Detailed Comparison

MongoDB	RxDB
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.	💻 📱 Reactive, serverless, client-side, offline-first database in javascript. Client-Side Database for Browsers, NodeJS, electron, cordova, react-native and every other javascript-runtime.
Flexible data model, expressive query language, secondary indexes, replication, auto-sharding, in-place updates, aggregation, GridFS	-
Statistics
GitHub Stars 27.7K	GitHub Stars 22.8K
GitHub Forks 5.7K	GitHub Forks 1.1K
Stacks 96.6K	Stacks 59
Followers 82.0K	Followers 179
Votes 4.1K	Votes 63
Pros & Cons
Pros 829 Document-oriented storage 594 No sql 554 Ease of use 465 Fast 410 High performance Cons 6 Very slowly for connected models that require joins 3 Not acid compliant 2 Proprietary query language	Pros 15 Good documentation 13 Subscription to queries 11 Example projects 10 Works 10 Typescript support Cons 4 Bulk operation for updates and other operation
Integrations
No integrations available	Pouchdb CouchDB Cloudant React Angular Ionic Vue.js

What are some alternatives to MongoDB, RxDB?

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.

SQLite

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.

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.