Software Alternatives, Accelerators & Startups
Register | Login

MongoDB VS pipenv

Compare MongoDB VS pipenv and see what are their differences

ASocks
Clear, Fast & Unlimited. Residential & Mobile Proxies For Best Price. featured
Note: These products don't have any matching categories. If you think this is a mistake, please edit the details of one of the products and suggest appropriate categories.
Contents:
  1. » Base Details
  2. » Videos
  3. » Reviews
  4. » Alternatives

MongoDB logo MongoDB

MongoDB (from "humongous") is a scalable, high-performance NoSQL database.

pipenv logo pipenv

Python Development Workflow for Humans. Contribute to pypa/pipenv development by creating an account on GitHub.
  • MongoDB Landing page
    Landing page //
    2023-10-21
  • pipenv Landing page
    Landing page //
    2023-08-26

MongoDB features and specs

  • Scalability
    MongoDB offers horizontal scaling through sharding, allowing it to handle large volumes of data and enabling distributed computing.
  • Flexible Schema
    It allows for a flexible schema design using BSON (Binary JSON), making it easier to iterate and change application data models.
  • High Performance
    MongoDB is optimized for read and write throughput, making it suitable for real-time applications.
  • Rich Query Language
    Supports a rich and expressive query language that allows for efficient querying and analytics.
  • Built-in Replication
    Provides robust replication mechanisms for high availability and redundancy.
  • Geospatial Indexing
    Offers powerful geospatial indexing capabilities, useful for location-based applications.
  • Aggregation Framework
    Enables complex data manipulations and transformations using the aggregation pipeline framework.
  • Cross-Platform
    Works on multiple operating systems, enhancing its versatility and deployment options.

Possible disadvantages of MongoDB

  • Memory Usage
    MongoDB can consume a large amount of memory due to its use of memory-mapped files, which may be a concern for some applications.
  • Complex Transactions
    While MongoDB supports ACID transactions, they can be more complex to implement and less efficient compared to traditional relational databases.
  • Data Redundancy
    The flexible schema design can lead to data redundancy and increased storage costs if not managed carefully.
  • Limited Joins
    Joins are supported but can be less efficient and more limited compared to relational databases, affecting complex relational data querying.
  • Indexing Overhead
    Extensive indexing can introduce overhead and impact performance, especially during write operations.
  • Learning Curve
    Requires a different mindset and understanding compared to traditional relational databases, which can present a learning curve for new users.
  • Lacks Mature Analytical Tools
    The ecosystem for analytical tools around MongoDB is not as mature as those for traditional relational databases, which might limit advanced analytics capabilities.
  • Cost
    The cost of using MongoDB's cloud services (MongoDB Atlas) can be high, especially for large-scale deployments.

pipenv features and specs

  • Integrated Workflow
    Pipenv combines the functionalities of pip and virtualenv, providing a seamless environment for package installation and management, making the development workflow more efficient and organized.
  • Automatic Virtual Environment Management
    Automatically creates and manages a virtual environment for projects, ensuring that dependencies are maintained separately and do not interfere with the system Python or other projects.
  • Lock File Generation
    Generates a Pipfile.lock to ensure deterministic builds, making sure that installations are consistent across different environments or deployments.
  • User-Friendly Package Installation
    Simplifies package installation with a straightforward and intuitive interface. Pipenv handles both direct package specification and environment management in a unified manner.
  • Environment Consistency
    By using the Pipfile and Pipfile.lock, Pipenv ensures that all developers working on a project have a consistent set of dependencies, reducing 'it works on my machine' issues.
  • Dependency Resolution
    Pipenv uses an advanced dependency resolver, helping to avoid dependency conflicts that can occur with complex package requirements.

Possible disadvantages of pipenv

  • Performance Overhead
    The dependency resolution process can sometimes be slow, which might be noticeable in larger projects or when installing multiple packages at once.
  • Limited Flexibility
    Pipenv abstracts away some of pip and virtualenv’s flexibility, which might limit advanced configurations or setups required by more complex projects.
  • Complexity for Simple Projects
    May add unnecessary complexity for simple or small projects where virtualenv and pip would suffice without additional layers.
  • Slower Updates
    Pipenv may lag behind updates compared to pip and virtualenv due to its additional integration layer, meaning it might not always provide immediate support for the latest Python packaging developments.
  • Learning Curve
    Requires initial learning and adjustment for developers who are accustomed to using pip and virtualenv separately, potentially slowing down onboarding for new team members.

Analysis of MongoDB

Overall verdict

  • MongoDB is generally regarded as a good database solution for applications needing flexibility, scalability, and fast development times. However, it may not be the best choice for applications requiring complex transactions or where ACID compliance is critical, as it originally prioritized availability over consistency. Recent improvements, including multi-document transactions, have addressed some concerns, making it more versatile.

Why this product is good

  • MongoDB is considered a good choice for certain types of applications due to its flexible schema design, scalability, horizontal scaling capabilities, and ease of use for developers who require rapid development cycles. It supports a wide range of data types and allows for full-text search, geospatial queries, and aggregation operations. MongoDB's document-oriented storage makes it well-suited for handling large volumes of unstructured data. Its robust ecosystem, including Atlas for cloud deployments, adds to its appeal by offering automated scaling, backups, and distributed architecture.

Recommended for

  • Applications requiring high scalability and performance with unstructured data
  • Real-time analytics and big data applications
  • Web and mobile applications needing rapid development and flexible data models
  • Projects that benefit from cloud-native solutions with managed services

MongoDB videos

+ Add

MySQL vs MongoDB

More videos:

  • Review - The Good and Bad of MongoDB
  • Review - what is mongoDB

pipenv videos

+ Add

Pipenv Crash Course

More videos:

  • Tutorial - How to use Pipenv to Manage Python Dependencies (Tutorial)
  • Review - venv, pyenv, pypi, pip, pipenv, pyWTF?

Category Popularity

0-100% (relative to MongoDB and pipenv)

MongoDB

pipenv

Databases
100 100%
Databases
0% 0
Front End Package Manager
0 0%
Front End Package Manager
100% 100
NoSQL Databases
100 100%
NoSQL Databases
0% 0
Package Manager
0 0%
Package Manager
100% 100

User comments

Share your experience with using MongoDB and pipenv. For example, how are they different and which one is better?
Log in or Post with

Reviews

These are some of the external sources and on-site user reviews we've used to compare MongoDB and pipenv

MongoDB Reviews

10 Top Firebase Alternatives to Ignite Your Development in 2024
MongoDB’s superpower lies in its flexibility. Its document-based model lets you store data in a free-form, schema-less way, making it adaptable to evolving application needs. Need to add a new field or change the structure of your data? No problem, MongoDB handles it with ease.
Source: genezio.com
Top 7 Firebase Alternatives for App Development in 2024
MongoDB Realm provides a robust alternative to Firebase, especially for apps requiring a flexible data model. Key features include:
Source: signoz.io
Announcing FerretDB 1.0 GA - a truly Open Source MongoDB alternative
MongoDB is no longer open source. We want to bring MongoDB database workloads back to its open source roots. We are enabling PostgreSQL and other database backends to run MongoDB workloads, retaining the opportunities provided by the existing ecosystem around MongoDB.
Source: blog.ferretdb.io
16 Top Big Data Analytics Tools You Should Know About
The database added a new feature to its list of attributes called MongoDB Atlas. It is a global cloud database technology that allows to deploy a fully managed MongoDB across AWS, Google Cloud, and Azure with its built-in automation for resource, workload optimization and to reduce the time required to handle the database.
Source: www.analytixlabs.co.in
9 Best MongoDB alternatives in 2019
MongoDB is an open source NoSQL DBMS which uses a document-oriented database model. It supports various forms of data. However, in MongoDB data consumption is high due to de-normalization.
Source: www.guru99.com

pipenv Reviews

We have no reviews of pipenv yet.
Be the first one to post

Social recommendations and mentions

Based on our record, MongoDB should be more popular than pipenv. It has been mentiond 18 times since March 2021. We are tracking product recommendations and mentions on various public social media platforms and blogs. They can help you identify which product is more popular and what people think of it.

MongoDB mentions (18)

  • Creating AI Memories using Rig & MongoDB
    In this article, we’ll build a CLI tool using the Rig AI framework and MongoDB for retrieval-augmented generation (RAG). This tool will store summarized conversations in a database and retrieve them when needed, enabling the AI to maintain context over time. - Source: dev.to / 3 months ago
  • The Adventures of Blink S2e2: Database, Contained
    Have a Mongo database holding the various phrases we're going to use and potentially configuration data for the frontend as well. - Source: dev.to / 10 months ago
  • Introducing Perseid: The Product-oriented JS framework
    It's also worth mentioning that Perseid provides out-of-the-box support for React, VueJS, Svelte, MongoDB, MySQL, PostgreSQL, Express and Fastify. - Source: dev.to / 9 months ago
  • DocumentDB Elastic Cluster Pricing
    Does anyone know if the most basic Elastic Cluster instance of DocumentDB carries any monthly fixed cost or is it just on-demand cost? Another words if I run like 10,000 queries against the DB per month, what kind of bill would I expect? This is for a super small app. I am currently using mongodb free tier , but want to migrate everything to AWS. Can't seem to find a straight answer to the pricing question. Source: over 2 years ago
  • I wrote some scripts for converting the UTZOO Usenet archive to a Mongo Database
    You can use either MongoDB.com's dashboard (if you host a remote database) or Mongo Compass to run queries on the data or you can modify the express middleware with your own queries. I'm still working on the API, so it's not very robust yet. I will update this when it is. Source: over 2 years ago
View more

pipenv mentions (6)

  • Generate pip requirements.txt file based on imports of any project
    https://github.com/pypa/pipenv Pipenv was last updated 10 hours ago. Looks like it's still an active project to me. - Source: Hacker News / 8 months ago
  • Adding Virtual Environments to Git Repo
    Pipenv solves this by having both kinds of requirement files: Pipfile lists package names and known constraints on which versions can be used, while Pipfile.lock gives specific package versions with hashes. Theoretically the Pipfile (and its lockfile) format were supposed to be a standard that many different tools could use, but I haven't seen it get adopted much outside of pipenv itself, so I'm not sure if it's... Source: about 2 years ago
  • Top 10 Python security best practices
    Alternatively, you can look into Pipenv, which has a lot more tools to develop secure applications with. - Source: dev.to / almost 3 years ago
  • Why and how to use conda?
    I’m partial to pipenv but it does depend on pyenv (which works on Windows albeit via WSL, no?). Source: about 3 years ago
  • How to make a Python package in 2021
    I think I went through the same progression — thinking pipenv was the official solution before deciding it isn’t. To add to the confusion, I just realized that pipenv [1] is currently owned by the Python Packaging Authority (PyPA) which also owns the official pip [2] and virtualenv [3]. [1]: https://github.com/pypa/pipenv [2]: https://github.com/pypa/pip [3]: https://github.com/pypa/virtualenv. - Source: Hacker News / about 4 years ago
View more

What are some alternatives?

When comparing MongoDB and pipenv, you can also consider the following products

Redis - Redis is an open source in-memory data structure project implementing a distributed, in-memory key-value database with optional durability.

Python Poetry - Python packaging and dependency manager.

PostgreSQL - PostgreSQL is a powerful, open source object-relational database system.

Conda - Binary package manager with support for environments.

MySQL - The world's most popular open source database

pip - The PyPA recommended tool for installing Python packages.

Loading...