StackShareStackShare
Follow on
StackShare

Discover and share technology stacks from companies around the world.

Follow on

© 2025 StackShare. All rights reserved.

Product

  • Stacks
  • Tools
  • Feed

Company

  • About
  • Contact

Legal

  • Privacy Policy
  • Terms of Service
  1. Stackups
  2. Application & Data
  3. Databases
  4. Databases
  5. LokiJS vs MongoDB

LokiJS vs MongoDB

OverviewDecisionsComparisonAlternatives

Overview

MongoDB
MongoDB
Stacks96.6K
Followers82.0K
Votes4.1K
GitHub Stars27.7K
Forks5.7K
LokiJS
LokiJS
Stacks43
Followers57
Votes3
GitHub Stars6.8K
Forks483

LokiJS vs MongoDB: What are the differences?

Introduction

LokiJS and MongoDB are both NoSQL databases used for storing and retrieving data. However, they have key differences that set them apart from each other. In this article, we will explore and highlight these differences.

  1. Data Structure: LokiJS is an in-memory database that saves data in JavaScript objects, making it faster for data retrieval. On the other hand, MongoDB is a document-based database that stores data in BSON (Binary JSON) format, offering more flexibility in handling complex data structures.

  2. Scalability: While both databases can handle a large amount of data, MongoDB is more scalable due to its distributed architecture and horizontal scaling capabilities. LokiJS, being an in-memory database, is limited by the available memory of the system it runs on and may not be suitable for large-scale applications with high data volumes.

  3. Query Language: MongoDB uses a powerful query language called MongoDB Query Language (MQL) that allows for complex and dynamic queries using a JSON-like syntax. LokiJS, on the other hand, uses a simple and lightweight query language that supports basic CRUD (Create, Read, Update, Delete) operations but lacks the advanced querying capabilities of MongoDB.

  4. Indexes: Both databases support indexing for faster data retrieval. However, MongoDB offers a wider range of indexing options, including text indexes, geo-spatial indexes, and compound indexes. LokiJS, being an in-memory database, has limited indexing options, mainly supporting single-field indexes.

  5. Transaction Support: MongoDB supports multi-document ACID (Atomicity, Consistency, Isolation, Durability) transactions, allowing multiple operations to be executed in a single transaction. LokiJS, on the other hand, does not have built-in transaction support and operates on a single-document level, making it less suitable for applications that require complex transactional operations.

  6. Community and Ecosystem: MongoDB has a large and active community, offering extensive support, documentation, and a wide range of libraries and tools. LokiJS, while having its own community, is relatively smaller compared to MongoDB, resulting in fewer resources and options for developers.

In summary, LokiJS and MongoDB differ in their data structure, scalability, query language capabilities, indexing options, transaction support, and community support. These differences make each database more suitable for specific use cases and development needs.

Share your Stack

Help developers discover the tools you use. Get visibility for your team's tech choices and contribute to the community's knowledge.

View Docs
CLI (Node.js)
or
Manual

Advice on MongoDB, LokiJS

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
LokiJS
LokiJS

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.

LokiJS is a document oriented database written in javascript, published under MIT License. Its purpose is to store javascript objects as documents in a nosql fashion and retrieve them with a similar mechanism. Runs in node (including cordova/phonegap and node-webkit), nativescript and the browser.

Flexible data model, expressive query language, secondary indexes, replication, auto-sharding, in-place updates, aggregation, GridFS
-
Statistics
GitHub Stars
27.7K
GitHub Stars
6.8K
GitHub Forks
5.7K
GitHub Forks
483
Stacks
96.6K
Stacks
43
Followers
82.0K
Followers
57
Votes
4.1K
Votes
3
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
  • 3
    Can query the objects directly
Integrations
No integrations available
Node.js
Node.js
NativeScript
NativeScript
Apache Cordova
Apache Cordova
PhoneGap
PhoneGap

What are some alternatives to MongoDB, LokiJS?

Redis

Redis

Redis is an open source (BSD licensed), in-memory data structure store, used as a database, cache, and message broker. Redis provides data structures such as strings, hashes, lists, sets, sorted sets with range queries, bitmaps, hyperloglogs, geospatial indexes, and streams.

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.

Related Comparisons

Bootstrap
Materialize

Bootstrap vs Materialize

Laravel
Django

Django vs Laravel vs Node.js

Bootstrap
Foundation

Bootstrap vs Foundation vs Material UI

Node.js
Spring Boot

Node.js vs Spring-Boot

Liquibase
Flyway

Flyway vs Liquibase