DBMS > ClickHouse vs. MarkLogic vs. Percona Server for MongoDB vs. Valentina Server

System Properties Comparison ClickHouse vs. MarkLogic vs. Percona Server for MongoDB vs. Valentina Server

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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.

Operational and transactional Enterprise NoSQL database

A drop-in replacement for MongoDB Community Edition with enterprise-grade features.

Object-relational database and reports server

Primary database model

Relational DBMS

Document store
Native XML DBMS
RDF store

as of version 7
Search engine

Document store

Relational DBMS

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

Score	0.52
Rank	#254	Overall
	#39	Document stores

Score	0.17
Rank	#327	Overall
	#145	Relational DBMS

Website

clickhouse.com

www.marklogic.com

www.percona.com/mongodb/software/percona-server-for-mongodb

www.valentina-db.net

Technical documentation

clickhouse.com/docs

docs.marklogic.com

docs.percona.com/percona-distribution-for-mongodb

valentina-db.com/docs/dokuwiki/v5/doku.php

Developer

Clickhouse Inc.

MarkLogic Corp.

Percona

Paradigma Software

Initial release

2016

2001

2015

1999

Current release

v24.4.1.2088-stable, May 2024

11.0, December 2022

3.4.10-2.10, November 2017

5.7.5

License

Commercial or Open Source

Open Source

Apache 2.0

commercial

restricted free version is available

Open Source

GPL Version 2

commercial

Cloud-based only

Only available as a cloud service

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.

Implementation language

C++

Server operating systems

FreeBSD
Linux
macOS

Linux
OS X
Windows

Linux

Linux
OS X
Windows

Data scheme

yes

schema-free

Schema can be enforced

schema-free

yes

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)

yes

SQL92

yes

APIs and other access methods

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

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

proprietary protocol using JSON

ODBC

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

Actionscript
C
C#
C++
Clojure
ColdFusion
D
Dart
Delphi
Erlang
Go
Groovy
Haskell
Java
JavaScript
Lisp
Lua
MatLab
Perl
PHP
PowerShell
Prolog
Python
R
Ruby
Scala
Smalltalk

.Net
C
C#
C++
Objective-C
PHP
Ruby
Visual Basic
Visual Basic.NET

Server-side scripts

Stored procedures

yes

via XQuery or JavaScript

JavaScript

yes

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

key based and custom

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

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

yes

Source-replica replication

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

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

yes

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Eventual Consistency
Immediate Consistency

Foreign keys

Referential integrity

yes

Transaction concepts

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

ACID

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

Concurrency

Support for concurrent manipulation of data

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

via In-Memory Engine

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.

Role-based access control at the document and subdocument levels

Access rights for users and roles

fine grained access rights according to SQL-standard

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