DBMS > ClickHouse vs. Ehcache vs. Microsoft Azure Cosmos DB vs. MongoDB vs. Riak KV

System Properties Comparison ClickHouse vs. Ehcache vs. Microsoft Azure Cosmos DB vs. MongoDB vs. Riak KV

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.

A widely adopted Java cache with tiered storage options

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

Distributed, fault tolerant key-value store

Primary database model

Relational DBMS

Key-value store

Document store
Graph DBMS
Key-value store
Wide column store

Document store

Key-value store

with links between data sets and object tags for the creation of secondary indexes

Secondary database models

Time Series 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	16.20
Rank	#37	Overall
	#23	Relational DBMS

Score	5.23
Rank	#68	Overall
	#8	Key-value stores

Score	29.85
Rank	#27	Overall
	#4	Document stores
	#2	Graph DBMS
	#3	Key-value stores
	#3	Wide column stores

Score	423.96
Rank	#5	Overall
	#1	Document stores

Score	4.44
Rank	#80	Overall
	#9	Key-value stores

Website

clickhouse.com

www.ehcache.org

azure.microsoft.com/services/cosmos-db

www.mongodb.com

Technical documentation

clickhouse.com/docs

www.ehcache.org/documentation

learn.microsoft.com/azure/cosmos-db

www.mongodb.com/docs/manual

www.tiot.jp/riak-docs/riak/kv/latest

Developer

Clickhouse Inc.

Terracotta Inc, owned by Software AG

Microsoft

MongoDB, Inc

OpenSource, formerly Basho Technologies

Initial release

2016

2009

2014

2009

Current release

v24.3.2.23-lts, April 2024

3.10.0, March 2022

6.0.7, June 2023

3.2.0, December 2022

License

Commercial or Open Source

Open Source

Apache 2.0

Open Source

Apache Version 2; commercial licenses available

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.

Open Source

Apache version 2, commercial enterprise edition

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.

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.
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.

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++

Java

C++

Erlang

Server operating systems

FreeBSD
Linux
macOS

All OS with a Java VM

hosted

Linux
OS X
Solaris
Windows

Linux
OS X

Data scheme

yes

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.

schema-free

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

restricted

SQL

Support of SQL

Close to ANSI SQL (SQL/JSON + extensions)

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

JCache

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

GraphQL
HTTP REST
Prisma
proprietary protocol using JSON

HTTP API
Native Erlang Interface

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

Java

.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

unofficial client library
C#
C++

unofficial client library
Clojure

unofficial client library
Dart

unofficial client library
Erlang
Go

unofficial client library
Groovy

unofficial client library
Haskell

unofficial client library
Java
JavaScript

unofficial client library
Lisp

unofficial client library
Perl

unofficial client library
PHP
Python
Ruby
Scala

unofficial client library
Smalltalk

unofficial client library

Server-side scripts

Stored procedures

yes

JavaScript

Erlang

Triggers

yes

Cache Event Listeners

JavaScript

yes

in MongoDB Atlas only

yes

pre-commit hooks and post-commit hooks

Partitioning methods

Methods for storing different data on different nodes

key based and custom

Sharding

by using Terracotta Server

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.

Sharding

no "single point of failure"

Replication methods

Methods for redundantly storing data on multiple nodes

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

yes

by using Terracotta Server

yes

Implicit feature of the cloud service

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

selectable replication factor

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

Tunable Consistency (Strong, Eventual, Weak)

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

Eventual Consistency

Foreign keys

Referential integrity

typically not used, however similar functionality with DBRef possible

links between data sets can be stored

Transaction concepts

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

yes

supports JTA and can work as an XA resource

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

Durability

Support for making data persistent

yes

using a tiered cache-storage approach

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

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.

Access rights can be defined down to the item level

Access rights for users and roles

yes, using Riak Security

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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