DBMS > MongoDB vs. Snowflake vs. TerarkDB

System Properties Comparison MongoDB vs. Snowflake vs. TerarkDB

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Editorial information provided by DB-Engines

Name

Description

One of the most popular document stores available both as a fully managed cloud service and for deployment on self-managed infrastructure

Cloud-based data warehousing service for structured and semi-structured data

A key-value store forked from RocksDB with advanced compression algorithms. It can be used standalone or as a storage engine for MySQL and MongoDB

Primary database model

Document store

Relational DBMS

Key-value store

Secondary database models

Spatial DBMS
Search engine

integrated Lucene index, currently in MongoDB Atlas only.
Time Series DBMS

Time Series Collections introduced in Release 5.0
Vector DBMS

currently available in the MongoDB Atlas cloud service only

DB-Engines Ranking measures the popularity of database management systems
Trend Chart

Score	423.96
Rank	#5	Overall
	#1	Document stores

Score	123.20
Rank	#9	Overall
	#6	Relational DBMS

Score	0.04
Rank	#377	Overall
	#58	Key-value stores

Website

www.mongodb.com

www.snowflake.com

github.com/bytedance/terarkdb

Technical documentation

www.mongodb.com/docs/manual

docs.snowflake.net/manuals/index.html

bytedance.larkoffice.com/docs/doccnZmYFqHBm06BbvYgjsHHcKc

Developer

MongoDB, Inc

Snowflake Computing Inc.

ByteDance, originally Terark

Initial release

2009

2014

2016

Current release

6.0.7, June 2023

License

Commercial or Open Source

Open Source

MongoDB Inc.'s Server Side Public License v1. Prior versions were published under GNU AGPL v3.0. Commercial licenses are also available.

commercial

restricted open source version available

Cloud-based only

Only available as a cloud service

MongoDB available as DBaaS (MongoDB Atlas)

yes

DBaaS offerings (sponsored links)

Database as a Service

Providers of DBaaS offerings, please contact us to be listed.

MongoDB Atlas: Global multi-cloud database with unmatched data distribution and mobility across AWS, Azure, and Google Cloud, built-in automation for resource and workload optimization, and so much more.

Implementation language

C++

Server operating systems

Linux
OS X
Solaris
Windows

hosted

Data scheme

schema-free

Although schema-free, documents of the same collection often follow the same structure. Optionally impose all or part of a schema by defining a JSON schema.

yes

support of semi-structured data formats (JSON, XML, Avro)

schema-free

Typing

predefined data types such as float or date

yes

string, integer, double, decimal, boolean, date, object_id, geospatial

yes

XML support

Some form of processing data in XML format, e.g. support for XML data structures, and/or support for XPath, XQuery or XSLT.

yes

Secondary indexes

yes

SQL

Support of SQL

Read-only SQL queries via the MongoDB Atlas SQL Interface

yes

APIs and other access methods

GraphQL
HTTP REST
Prisma
proprietary protocol using JSON

CLI Client
JDBC
ODBC

C++ API
Java API

Supported programming languages

Actionscript

unofficial driver
C
C#
C++
Clojure

unofficial driver
ColdFusion

unofficial driver
D

unofficial driver
Dart

unofficial driver
Delphi

unofficial driver
Erlang
Go
Groovy

unofficial driver
Haskell
Java
JavaScript
Kotlin
Lisp

unofficial driver
Lua

unofficial driver
MatLab

unofficial driver
Perl
PHP
PowerShell

unofficial driver
Prolog

unofficial driver
Python
R

unofficial driver
Ruby
Rust
Scala
Smalltalk

unofficial driver
Swift

JavaScript (Node.js)
Python

C++
Java

Server-side scripts

Stored procedures

JavaScript

user defined functions

Triggers

yes

in MongoDB Atlas only

similar concept for controling cloud resources

Partitioning methods

Methods for storing different data on different nodes

Sharding

Partitioned by hashed, ranged, or zoned sharding keys. Live resharding allows users to change their shard keys as an online operation with zero downtime.

yes

none

Replication methods

Methods for redundantly storing data on multiple nodes

Multi-Source deployments with MongoDB Atlas Global Clusters
Source-replica replication

yes

none

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

Consistency concepts

Methods to ensure consistency in a distributed system

Eventual Consistency

can be individually decided for each read operation
Immediate Consistency

default behaviour

Immediate Consistency

Foreign keys

Referential integrity

typically not used, however similar functionality with DBRef possible

yes

Transaction concepts

Support to ensure data integrity after non-atomic manipulations of data

Multi-document ACID Transactions with snapshot isolation

ACID

Concurrency

Support for concurrent manipulation of data

yes

Durability

Support for making data persistent

yes

optional, enabled by default

yes

In-memory capabilities

Is there an option to define some or all structures to be held in-memory only.

yes

In-memory storage engine introduced with MongoDB version 3.2

yes

User concepts

Access control

Access rights for users and roles

Users with fine-grained authorization concept, user roles and pluggable authentication

More information provided by the system vendor

Specific characteristics

MongoDB provides an integrated suite of cloud database and data services to accelerate...
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Competitive advantages

Built around the flexible document data model and unified API, MongoDB is a developer...
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Typical application scenarios

AI-enriched intelligent apps (Continental, Telefonica, Iron Mountain) Internet of...
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Key customers

ADP, Adobe, Amadeus, AstraZeneca, Auto Trader, Barclays, BBVA, Bosch, Cisco, CERN,...
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Market metrics

Hundreds of millions downloads, over 150,000+ Atlas clusters provisioned every month...
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Licensing and pricing models

MongoDB database server: Server-Side Public License (SSPL) . Commercial licenses...
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