DBMS > ClickHouse vs. IBM Cloudant vs. JaguarDB vs. MarkLogic vs. SwayDB

System Properties Comparison ClickHouse vs. IBM Cloudant vs. JaguarDB vs. MarkLogic vs. SwayDB

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.

Database as a Service offering based on Apache CouchDB

Performant, highly scalable DBMS for AI and IoT applications

Operational and transactional Enterprise NoSQL database

An embeddable, non-blocking, type-safe key-value store for single or multiple disks and in-memory storage

Primary database model

Relational DBMS

Document store

Key-value store
Vector DBMS

Document store
Native XML DBMS
RDF store

as of version 7
Search engine

Key-value store

Secondary database models

Time Series DBMS

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

Score	16.34
Rank	#38	Overall
	#23	Relational DBMS

Score	2.68
Rank	#106	Overall
	#20	Document stores

Score	0.00
Rank	#383	Overall
	#60	Key-value stores
	#13	Vector DBMS

Score	5.92
Rank	#58	Overall
	#10	Document stores
	#1	Native XML DBMS
	#1	RDF stores
	#6	Search engines

Score	0.00
Rank	#382	Overall
	#59	Key-value stores

Website

clickhouse.com

www.ibm.com/products/cloudant

www.jaguardb.com

www.marklogic.com

swaydb.simer.au

Technical documentation

clickhouse.com/docs

cloud.ibm.com/docs/Cloudant

www.jaguardb.com/support.html

docs.marklogic.com

Developer

Clickhouse Inc.

IBM, Apache Software Foundation

IBM acquired Cloudant in February 2014

DataJaguar, Inc.

MarkLogic Corp.

Simer Plaha

Initial release

2016

2010

2015

2001

2018

Current release

v24.3.2.23-lts, April 2024

3.3 July 2023

11.0, December 2022

License

Commercial or Open Source

Open Source

Apache 2.0

commercial

Open Source

GPL V3.0

commercial

restricted free version is available

Open Source

GNU Affero GPL V3.0

Cloud-based only

Only available as a cloud service

yes

DBaaS offerings (sponsored links)

Database as a Service

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

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Implementation language

C++

Erlang

C++

the server part. Clients available in other languages

C++

Scala

Server operating systems

FreeBSD
Linux
macOS

hosted

Linux

Linux
OS X
Windows

Data scheme

yes

schema-free

yes

schema-free

Schema can be enforced

schema-free

Typing

predefined data types such as float or date

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

Close to ANSI SQL (SQL/JSON + extensions)

A subset of ANSI SQL is implemented

but no views, foreign keys, triggers

yes

SQL92

APIs and other access methods

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

RESTful HTTP/JSON API

JDBC
ODBC

Java API
Node.js Client API
ODBC
proprietary Optic API

Proprietary Query API, introduced with version 9
RESTful HTTP API
SPARQL
WebDAV
XDBC
XQuery
XSLT

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

C#
Java
JavaScript
Objective-C
PHP
Ruby

C
C++
Go
Java
JavaScript (Node.js)
PHP
Python
Ruby
Scala

C
C#
C++
Java
JavaScript (Node.js)
Perl
PHP
Python
Ruby

Java
Kotlin
Scala

Server-side scripts

Stored procedures

yes

View functions (Map-Reduce) in JavaScript

yes

via XQuery or JavaScript

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

key based and custom

Sharding

none

Replication methods

Methods for redundantly storing data on multiple nodes

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

Multi-source replication
Source-replica replication

Multi-source replication

yes

none

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

via Hadoop Connector, HDFS Direct Access and in-database MapReduce jobs

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Eventual Consistency

Immediate Consistency

Foreign keys

Referential integrity

Transaction concepts

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

atomic operations within a document possible

ACID

can act as a resource manager in an XA/JTA transaction

Atomic execution of operations

Concurrency

Support for concurrent manipulation of data

yes

Optimistic locking

yes

Durability

Support for making data persistent

yes

In-memory capabilities

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

yes

yes, with Range Indexes

yes

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 for users can be defined per database

rights management via user accounts

Role-based access control at the document and subdocument levels

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