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MongoDB VS DuckDB

Compare MongoDB VS DuckDB and see what are their differences

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MongoDB logo MongoDB

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

DuckDB logo DuckDB

DuckDB is an in-process SQL OLAP database management system
  • MongoDB Landing page
    Landing page //
    2023-10-21
  • DuckDB Landing page
    Landing page //
    2023-06-18

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.

DuckDB features and specs

  • Lightweight
    DuckDB is a lightweight database that is easy to install and use without requiring a separate server process.
  • In-Memory Processing
    It supports efficient in-memory execution, which makes it suitable for analytical queries that require quick data processing.
  • Columnar Storage
    DuckDB uses a columnar storage format that optimizes for analytical workloads by improving read performance for large datasets.
  • Integration with Data Science Tools
    The database integrates well with popular data science tools and libraries such as Pandas, R, and Jupyter Notebooks.
  • SQL Support
    DuckDB offers full support for SQL, allowing users to leverage their existing SQL knowledge without having to learn new query languages.
  • Open Source
    DuckDB is open-source, enabling users to inspect the code, contribute to its development, and use it without licensing costs.

Possible disadvantages of DuckDB

  • Limited Scalability
    DuckDB is optimized for single-node operations, which may not be suitable for scaling out to large, distributed data workloads.
  • Relatively New
    As a newer database system, DuckDB might lack some features and optimizations found in more mature database systems.
  • Lack of Advanced Features
    DuckDB may not support some advanced database management features like complex transactions and user permissions found in other database systems.
  • Community and Support
    Being a less mature project, it might not have as large a community or extensive documentation and support as other established database systems.
  • Limited Distributed Processing
    DuckDB currently focuses more on local data processing and may not be the best choice for applications needing distributed computing capabilities.

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

DuckDB videos

+ Add

DuckDB An Embeddable Analytical Database

More videos:

  • Review - DuckDB: Hi-performance SQL queries on pandas dataframe (Python)
  • Review - DuckDB An Embeddable Analytical Database

Category Popularity

0-100% (relative to MongoDB and DuckDB)

MongoDB

DuckDB

Databases
86 86%
Databases
14% 14
NoSQL Databases
100 100%
NoSQL Databases
0% 0
Big Data
0 0%
Big Data
100% 100
Relational Databases
87 87%
Relational Databases
13% 13

User comments

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Reviews

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

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

DuckDB Reviews

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

Social recommendations and mentions

Based on our record, DuckDB should be more popular than MongoDB. It has been mentiond 37 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 / 7 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 / about 1 year 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 / about 1 year 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: almost 3 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: almost 3 years ago
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DuckDB mentions (37)

  • From OLTP to OLAP: Streaming Databases into MotherDuck with Estuary
    DuckDB is an open source analytical database designed with a clear goal: to make complex queries fast and simple without heavy infrastructure. Instead of being a traditional client-server database, DuckDB is embedded. It runs inside the host process, which reduces overhead and makes it easy to integrate directly into applications, notebooks, or scripts. Several features stand out:. - Source: dev.to / 8 days ago
  • DuckDB + Iceberg: The ultimate synergy
    Apache Iceberg and DuckDB have established themselves as key players in data architecture landscape. With DuckDB 1.4's native support for Iceberg writes, combined with Apache Polaris and MinIO, this promising stack offers efficiency, scalability, and flexibility. - Source: dev.to / 14 days ago
  • DuckDB on AWS Lambda: The Easy Way with Layers
    It seemed like the perfect opportunity to explore DuckDB, an in-process analytical database known for its efficiency and simplicity. - Source: dev.to / 23 days ago
  • From Go to Rust: Supercharging Our ClickHouse UDFs with Alloy
    While our Go-based implementation has served us well, we've been exploring whether Rust—with its rapidly maturing Ethereum ecosystem—could take us even further. The potential benefits are compelling: better performance, enhanced safety, and improved portability that could make it easier to bring these UDFs to other analytical engines like DataFusion or DuckDB. - Source: dev.to / 3 months ago
  • Show HN: TextQuery – Query CSV, JSON, XLSX Files with SQL
    Have you seen duckdb? https://duckdb.org/ It's basically what you're building, but more low-level. Really cool, to be honest -- serves the same market too. Do you have any significant differentiator, other than charts? - Source: Hacker News / 5 months ago
View more

What are some alternatives?

When comparing MongoDB and DuckDB, 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.

ClickHouse - ClickHouse is an open-source column-oriented database management system that allows generating analytical data reports in real time.

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

Apache Arrow - Apache Arrow is a cross-language development platform for in-memory data.

MySQL - The world's most popular open source database

Apache Parquet - Apache Parquet is a columnar storage format available to any project in the Hadoop ecosystem.

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