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  1. Stackups
  2. Application & Data
  3. Databases
  4. Databases
  5. Atlas-DB vs MongoDB

Atlas-DB vs MongoDB

OverviewDecisionsComparisonAlternatives

Overview

MongoDB
MongoDB
Stacks96.6K
Followers82.0K
Votes4.1K
GitHub Stars27.7K
Forks5.7K
Atlas-DB
Atlas-DB
Stacks6
Followers77
Votes0
GitHub Stars3.5K
Forks324

Atlas-DB vs MongoDB: What are the differences?

Introduction

MongoDB is a popular NoSQL database used for high-performance data storage and retrieval. Atlas-DB, on the other hand, is a specific version of MongoDB offered as a fully managed cloud database service by MongoDB.

  1. Storage and Scalability: A key difference between Atlas-DB and MongoDB is that Atlas-DB managed service architecture allows for automatic scaling of storage capacity and read/write throughput, while in MongoDB, the manual management of storage and scaling is required.

  2. Data Security: Atlas-DB provides additional security features such as encrypted data storage, network isolation, and compliance certifications compared to MongoDB, which might require extra configurations and setup for security measures.

  3. Automated Backups and Monitoring: Atlas-DB offers automated backups and monitoring tools as part of its fully managed service, easing the burden of database administrators, unlike MongoDB where these tasks need to be manually configured and managed.

  4. High Availability: Atlas-DB offers built-in high availability with automatic failover and self-healing features for uninterrupted service, which might require additional setup and monitoring in MongoDB for achieving the same level of reliability.

  5. Performance Optimization: Atlas-DB's managed service includes performance optimization tools and recommendations, ensuring efficient query execution and index usage, whereas in MongoDB, performance tuning and optimization require manual expertise and monitoring.

  6. Pricing and Support: With Atlas-DB, the pricing model includes a subscription-based fee for the managed service, including support options, while in MongoDB, organizations need to factor in the cost of infrastructure and additional support services separately.

In Summary, Atlas-DB stands out from MongoDB with its fully managed cloud database service architecture, advanced security features, automated backups, high availability, performance optimization tools, and pricing structure including support options.

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Advice on MongoDB, Atlas-DB

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
Atlas-DB
Atlas-DB

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.

Atlas was developed by Netflix to manage dimensional time series data for near real-time operational insight. Atlas features in-memory data storage, allowing it to gather and report very large numbers of metrics, very quickly.

Flexible data model, expressive query language, secondary indexes, replication, auto-sharding, in-place updates, aggregation, GridFS
Manages dimensional time series data; In-memory data storage; Captures operational intelligence
Statistics
GitHub Stars
27.7K
GitHub Stars
3.5K
GitHub Forks
5.7K
GitHub Forks
324
Stacks
96.6K
Stacks
6
Followers
82.0K
Followers
77
Votes
4.1K
Votes
0
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
No community feedback yet

What are some alternatives to MongoDB, Atlas-DB?

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.

dbForge Studio for MySQL

dbForge Studio for MySQL

It is the universal MySQL and MariaDB client for database management, administration and development. With the help of this intelligent MySQL client the work with data and code has become easier and more convenient. This tool provides utilities to compare, synchronize, and backup MySQL databases with scheduling, and gives possibility to analyze and report MySQL tables data.

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.

dbForge Studio for Oracle

dbForge Studio for Oracle

It is a powerful integrated development environment (IDE) which helps Oracle SQL developers to increase PL/SQL coding speed, provides versatile data editing tools for managing in-database and external data.

dbForge Studio for PostgreSQL

dbForge Studio for PostgreSQL

It is a GUI tool for database development and management. The IDE for PostgreSQL allows users to create, develop, and execute queries, edit and adjust the code to their requirements in a convenient and user-friendly interface.

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