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

JSON Server vs MongoDB

OverviewDecisionsComparisonAlternatives

Overview

MongoDB
MongoDB
Stacks96.6K
Followers82.0K
Votes4.1K
GitHub Stars27.7K
Forks5.7K
JSON Server
JSON Server
Stacks133
Followers189
Votes7
GitHub Stars75.3K
Forks7.2K

JSON Server vs MongoDB: What are the differences?

Introduction

JSON Server and MongoDB are both technologies that are widely used in web development. While they both have similarities in that they are used for managing data, there are also key differences between the two. In this article, we will explore the main differences between JSON Server and MongoDB.

1. Storage:

JSON Server is a simple database that stores data in JSON format. It is typically used for prototyping or mocking APIs. On the other hand, MongoDB is a NoSQL database that uses a document-oriented data model. It stores data in a flexible, JSON-like format called BSON.

2. Scalability:

JSON Server is not designed to handle large amounts of data or high traffic loads. It is more suitable for small-scale projects or development environments. MongoDB, on the other hand, is built for scalability and can handle large amounts of data and high traffic loads. It can be easily scaled horizontally by adding more servers to distribute the load.

3. Querying Language:

JSON Server uses a simple RESTful API to query and manipulate data. It supports basic CRUD operations (Create, Read, Update, Delete). MongoDB, on the other hand, uses a powerful query language called MongoDB Query Language (MQL). MQL allows for advanced querying capabilities such as complex filtering, aggregation, and indexing.

4. Schema:

JSON Server does not enforce a strict schema. It allows for flexible data structures and does not require predefined schemas or migrations. This makes it easy to work with during development but may lead to data inconsistency in production. MongoDB, on the other hand, supports dynamic schemas. It allows for the definition of schemas and provides validation rules for data integrity.

5. Transactions:

JSON Server does not natively support transactions. Each request is independent and changes are immediately persisted. MongoDB, on the other hand, supports ACID (Atomicity, Consistency, Isolation, Durability) transactions. Transactions allow for multiple operations to be executed as a single unit of work, ensuring data integrity.

6. Community Support:

JSON Server has a smaller community compared to MongoDB. It is a lightweight tool that is primarily used for development purposes. MongoDB, on the other hand, has a large and active community. It is a matured database technology with extensive documentation, tutorials, and community support.

In Summary, JSON Server and MongoDB differ in terms of storage, scalability, querying language, schema, transactions, and community support.

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Advice on MongoDB, JSON Server

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
JSON Server
JSON Server

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.

Created with <3 for front-end developers who need a quick back-end for prototyping and mocking.

Flexible data model, expressive query language, secondary indexes, replication, auto-sharding, in-place updates, aggregation, GridFS
-
Statistics
GitHub Stars
27.7K
GitHub Stars
75.3K
GitHub Forks
5.7K
GitHub Forks
7.2K
Stacks
96.6K
Stacks
133
Followers
82.0K
Followers
189
Votes
4.1K
Votes
7
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
    Stupid simple

What are some alternatives to MongoDB, JSON Server?

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.

Postman

Postman

It is the only complete API development environment, used by nearly five million developers and more than 100,000 companies worldwide.

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.

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