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  1. Stackups
  2. Application & Data
  3. Databases
  4. Databases
  5. MongoDB vs Realm

MongoDB vs Realm

OverviewDecisionsComparisonAlternatives

Overview

MongoDB
MongoDB
Stacks96.6K
Followers82.0K
Votes4.1K
GitHub Stars27.7K
Forks5.7K
Realm
Realm
Stacks279
Followers441
Votes16

MongoDB vs Realm: What are the differences?

MongoDB and Realm are two popular database technologies used in web development. Let's explore the key differences between them.

  1. Schema Design: MongoDB is a NoSQL database that allows flexible and dynamic schema design. It does not require a predefined schema, enabling developers to easily store unstructured data. On the other hand, Realm is a mobile database that supports both NoSQL and SQL-like data models. It requires a defined schema, making it more suitable for structured data.

  2. Real-time Sync: Realm provides real-time synchronization out of the box, allowing multiple devices to collaborate and share data seamlessly. It automatically handles data synchronization across different clients and resolves conflicts. MongoDB, on the other hand, needs additional setup and configuration to achieve real-time sync capabilities.

  3. Offline Capabilities: Realm is designed to work offline and provides built-in support for handling data while disconnected from the server. It automatically syncs the data when the device is back online. MongoDB, on the other hand, requires manual implementation of offline capabilities.

  4. Scalability: MongoDB is highly scalable and can handle large amounts of data and high traffic volumes. It provides built-in sharding and replication capabilities, allowing for efficient distribution of data across multiple servers. Realm, being a mobile database, has limitations in terms of scalability and is more suitable for smaller applications with fewer concurrent users.

  5. Query Language: MongoDB uses the MongoDB Query Language (MQL) for querying and manipulating data. MQL is similar to SQL but with some differences in syntax and functionalities. Realm, on the other hand, uses the Realm Query Language (RQL), which is specifically designed for use with the Realm database.

  6. Development Platform: MongoDB is a standalone database system that can be used with various programming languages and frameworks. It is platform-independent and can be run on Windows, macOS, or Linux. Realm, on the other hand, is primarily designed for mobile platforms and is tightly integrated with mobile app development frameworks like React Native and Xamarin.

In summary, MongoDB is a widely-used NoSQL database known for its flexibility, scalability, and ease of use, suitable for various data storage and retrieval needs in modern applications. Realm, on the other hand, is a mobile database platform designed specifically for offline-first mobile applications, offering features like seamless synchronization, real-time data updates, and cross-platform compatibility, making it ideal for mobile development scenarios.

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Advice on MongoDB, Realm

George
George

Student

Mar 18, 2020

Needs adviceonPostgreSQLPostgreSQLPythonPythonDjangoDjango

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
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
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
MongoDB
Realm
Realm

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.

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.

Flexible data model, expressive query language, secondary indexes, replication, auto-sharding, in-place updates, aggregation, GridFS
Feels like Home - Realm’s data structures look like the Objects and Arrays of your language, but provide additional features such as: querying, relationships & graphs, thread safety, and more.;Memory-Efficient - Realm is not built on SQLite. Instead, a custom C++ core is used to provide memory-efficient access to your data by using Realm objects, which usually consume less RAM than native objects.;F-F-Fast! - Realm offers extraordinary performance compared to SQLite and other persistence solutions.
Statistics
GitHub Stars
27.7K
GitHub Stars
-
GitHub Forks
5.7K
GitHub Forks
-
Stacks
96.6K
Stacks
279
Followers
82.0K
Followers
441
Votes
4.1K
Votes
16
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
  • 7
    Good
  • 3
    Cloud Syncing
  • 3
    Elegant API
  • 2
    React Native Support
  • 1
    Strong Adoption Growth
Cons
  • 1
    No offline support for web till now

What are some alternatives to MongoDB, Realm?

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.

SQLite

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

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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