Citus vs MongoDB

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Citus
Citus

29
30
+ 1
8
MongoDB
MongoDB

19.4K
15.8K
+ 1
3.9K
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Citus vs MongoDB: What are the differences?

Citus: Worry-free Postgres for SaaS. Built to scale out. Citus is worry-free Postgres for SaaS. Made to scale out, Citus is an extension to Postgres that distributes queries across any number of servers. Citus is available as open source, as on-prem software, and as a fully-managed service; MongoDB: The database for giant ideas. 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.

Citus and MongoDB belong to "Databases" category of the tech stack.

"Multi-core Parallel Processing" is the top reason why over 3 developers like Citus, while over 788 developers mention "Document-oriented storage" as the leading cause for choosing MongoDB.

Citus and MongoDB are both open source tools. It seems that MongoDB with 16.3K GitHub stars and 4.1K forks on GitHub has more adoption than Citus with 3.64K GitHub stars and 273 GitHub forks.

What is Citus?

It's an extension to Postgres that distributes data and queries in a cluster of multiple machines. Its query engine parallelizes incoming SQL queries across these servers to enable human real-time (less than a second) responses on large datasets.

What is MongoDB?

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.
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    What are some alternatives to Citus and MongoDB?
    CockroachDB
    Cockroach Labs is the company building CockroachDB, an open source, survivable, strongly consistent, scale-out SQL database.
    TimescaleDB
    TimescaleDB: An open-source database built for analyzing time-series data with the power and convenience of SQL — on premise, at the edge, or in the cloud.
    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 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 is a database management and analysis system for e-commerce, line-of-business, and data warehousing solutions.
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    Decisions about Citus and MongoDB
    MongoDB
    MongoDB

    I starting using MongoDB because it was much easier to implement in production then hosted SQL, and found that a lot of the limitation you think of from a document store vs a relational database were overcome by connecting the application to a graphql API, making retrieval seamless. Mongos latest upgrades as well as Stitch and Mongo mobile make it a perfect fit especially if your application will be cross platform web and mobile.

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    Anton Sidelnikov
    Anton Sidelnikov
    Backend Developer at Beamery · | 8 upvotes · 9.6K views
    PostgreSQL
    PostgreSQL
    MongoDB
    MongoDB

    In my opinion PostgreSQL is totally over MongoDB - not only works with structured data & SQL & strict types, but also has excellent support for unstructured data as separate data type (you can store arbitrary JSONs - and they may be also queryable, depending on one of format's you may choose). Both writes & reads are much faster, then in Mongo. So you can get best on Document NoSQL & SQL in single database..

    Formal downside of PostgreSQL is clustering scalability. There's not simple way to build distributed a cluster. However, two points:

    1) You will need much more time before you need to actually scale due to PG's efficiency. And if you follow database-per-service pattern, maybe you won't need ever, cause dealing few billion records on single machine is an option for PG.

    2) When you need to - you do it in a way you need, including as a part of app's logic (e.g. sharding by key, or PG-based clustering solution with strict model), scalability will be very transparent, much more obvious than Mongo's "cluster just works (but then fails)" replication.

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    Zach Coffin
    Zach Coffin
    Software Developer · | 4 upvotes · 8.1K views
    PostgreSQL
    PostgreSQL
    MongoDB
    MongoDB

    I started using PostgreSQL because I started a job at a company that was already using it as well as MongoDB. The main difference between the two from my perspective is that postgres columns are a chore to add/remove/modify whereas you can throw whatever you want into a mongo collection. And personally I prefer the query language for postgres over that of mongo, but they both have their merits. Maybe someday I'll be a DBA and have more insight to share but for now there's my 2 cents.

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    Antonio Sanchez
    Antonio Sanchez
    CEO at Kokoen GmbH · | 13 upvotes · 149.2K views
    atKokoen GmbHKokoen GmbH
    PHP
    PHP
    Laravel
    Laravel
    MySQL
    MySQL
    Go
    Go
    MongoDB
    MongoDB
    JavaScript
    JavaScript
    Node.js
    Node.js