DBMS > ClickHouse vs. Fujitsu Enterprise Postgres vs. Galaxybase vs. Microsoft Azure Cosmos DB vs. MongoDB

System Properties Comparison ClickHouse vs. Fujitsu Enterprise Postgres vs. Galaxybase vs. Microsoft Azure Cosmos DB vs. MongoDB

Editorial information provided by DB-Engines

Name

Description

A high-performance, column-oriented SQL DBMS for online analytical processing (OLAP) that uses all available system resources to their full potential to process each analytical query as fast as possible. It is available as both an open-source software and a cloud offering.

Enterprise-grade PostgreSQL-based DBMS with security enhancements such as Transparent Data Encryption and Data Masking, plus high-availability and performance improvement features.

Scalable, ACID-compliant native distributed parallel graph platform

Globally distributed, horizontally scalable, multi-model database service

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

Primary database model

Relational DBMS

Graph DBMS

Document store
Graph DBMS
Key-value store
Wide column store

Document store

Secondary database models

Time Series DBMS

Document store
Spatial DBMS

Spatial DBMS

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	16.34
Rank	#38	Overall
	#23	Relational DBMS

Score	0.31
Rank	#285	Overall
	#129	Relational DBMS

Score	0.00
Rank	#383	Overall
	#39	Graph DBMS

Score	29.04
Rank	#27	Overall
	#4	Document stores
	#2	Graph DBMS
	#3	Key-value stores
	#3	Wide column stores

Score	421.65
Rank	#5	Overall
	#1	Document stores

Website

clickhouse.com

www.postgresql.fastware.com

galaxybase.com

azure.microsoft.com/services/cosmos-db

www.mongodb.com

Technical documentation

clickhouse.com/docs

www.postgresql.fastware.com/product-manuals

learn.microsoft.com/azure/cosmos-db

www.mongodb.com/docs/manual

Developer

Clickhouse Inc.

PostgreSQL Global Development Group, Fujitsu Australia Software Technology

Chuanglin(Createlink) Technology Co., Ltd 浙江创邻科技有限公司

Microsoft

MongoDB, Inc

Initial release

2016

2017

2014

2009

Current release

v24.4.1.2088-stable, May 2024

Fujitsu Enterprise Postgres 14, January 2022

Nov 20, November 2021

6.0.7, June 2023

License

Commercial or Open Source

Open Source

Apache 2.0

commercial

Open Source

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

Cloud-based only

Only available as a cloud service

yes

MongoDB available as DBaaS (MongoDB Atlas)

DBaaS offerings (sponsored links)

Database as a Service

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

ClickHouse Cloud: Get the performance you love from open source ClickHouse in a serverless offering that takes care of the details so you can spend more time getting insight out of the fastest database on earth.
Aiven for Clickhouse: Managed cloud data warehousing with high-speed analytics.
DoubleCloud: Fully managed ClickHouse alongside best-in-class managed open-source services to build analytics at scale.

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.
MongoDB Flex @ STACKIT offers managed MongoDB Instances with adjustable CPU, RAM, storage amount and speed, in enterprise grade to perfectly match all application requirements. All services are 100% GDPR-compliant.

Implementation language

C++

C and Java

C++

Server operating systems

FreeBSD
Linux
macOS

Linux
Windows

Linux

hosted

Linux
OS X
Solaris
Windows

Data scheme

yes

Strong typed schema

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.

Typing

predefined data types such as float or date

yes

JSON types

yes

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

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.

Secondary indexes

yes

All properties auto-indexed by default

yes

SQL

Support of SQL

Close to ANSI SQL (SQL/JSON + extensions)

yes

SQL-like query language

Read-only SQL queries via the MongoDB Atlas SQL Interface

APIs and other access methods

gRPC
HTTP REST
JDBC
MySQL wire protocol
ODBC
PostgreSQL wire protocol
Proprietary protocol

ADO.NET
JDBC
native C library
ODBC
streaming API for large objects

Browser interface
console (shell)
Graph API (Gremlin)
OpenCypher
Proprietary native API

DocumentDB API
Graph API (Gremlin)
MongoDB API
RESTful HTTP API
Table API

GraphQL
HTTP REST
Prisma
proprietary protocol using JSON

Supported programming languages

3rd party library
C++
Elixir

3rd party library
Go

3rd party library
Java

3rd party library
JavaScript (Node.js)

3rd party library
Kotlin

3rd party library
Nim

3rd party library
Perl

3rd party library
PHP

3rd party library
Python

3rd party library
R

3rd party library
Ruby

3rd party library
Rust
Scala

3rd party library

.Net
C
C++
Delphi
Java
JavaScript (Node.js)
Perl
PHP
Python
Tcl

Go
Java
Python

.Net
C#
Java
JavaScript
JavaScript (Node.js)
MongoDB client drivers written for various programming languages
Python

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

Server-side scripts

Stored procedures

yes

user defined functions

user defined procedures and functions

JavaScript

Triggers

yes

JavaScript

yes

in MongoDB Atlas only

Partitioning methods

Methods for storing different data on different nodes

key based and custom

partitioning by range, list and by hash

Sharding

Implicit feature of the cloud service

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.

Replication methods

Methods for redundantly storing data on multiple nodes

Asynchronous and synchronous physical replication; geographically distributed replicas; support for object storages.

Source-replica replication

yes

Implicit feature of the cloud service

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

MapReduce

Offers an API for user-defined Map/Reduce methods

with Hadoop integration

Integration with Hadoop/HDInsight on Azure*

yes

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Bounded Staleness
Consistent Prefix
Eventual Consistency
Immediate Consistency

Consistency level configurable on request level
Session Consistency

Eventual Consistency

can be individually decided for each read operation
Immediate Consistency

default behaviour

Foreign keys

Referential integrity

yes

Relationships in graphs

typically not used, however similar functionality with DBRef possible

Transaction concepts

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

ACID

Multi-item ACID transactions with snapshot isolation within a partition

Multi-document ACID Transactions with snapshot isolation

Concurrency

Support for concurrent manipulation of data

yes

yes, multi-version concurrency control (MVCC)

yes

Durability

Support for making data persistent

yes

optional, enabled by default

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

User concepts

Access control

Access rights for users and roles. Column and row based policies. Quotas and resource limits. Pluggable authentication with LDAP and Kerberos. Password based, X.509 certificate, and SSH key authentication.

fine grained access rights according to SQL-standard

Role-based access control

Access rights can be defined down to the item level

Access rights for users and roles

More information provided by the system vendor

Specific characteristics

100% compatible with community PostgreSQL
» more

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

Built-in TDE and Data Masking security. In-Memory Columnar Index, and a high speed...
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Built around the flexible document data model and unified API, MongoDB is a developer...
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Typical application scenarios

Transactional payments applications, reporting and mixed workloads.
» more

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,...
» more

Market metrics

Over 30 years experience in database technology. Over 20 years in Postgres development...
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Hundreds of millions downloads, over 150,000+ Atlas clusters provisioned every month...
» more

Licensing and pricing models

Core based licensing
» more

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

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and for displaying vendor-provided information such as key customers, competitive advantages and market metrics.