DBMS > MarkLogic vs. MySQL vs. Prometheus vs. Stardog vs. Valentina Server

System Properties Comparison MarkLogic vs. MySQL vs. Prometheus vs. Stardog vs. Valentina Server

Editorial information provided by DB-Engines

Name

Description

Operational and transactional Enterprise NoSQL database

Widely used open source RDBMS

Open-source Time Series DBMS and monitoring system

Enterprise Knowledge Graph platform and graph DBMS with high availability, high performance reasoning, and virtualization

Object-relational database and reports server

Primary database model

Document store
Native XML DBMS
RDF store

as of version 7
Search engine

Relational DBMS

Key/Value like access via memcached API

Time Series DBMS

Graph DBMS
RDF store

Relational DBMS

Secondary database models

Document store
Spatial DBMS

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

Score	5.18
Rank	#63	Overall
	#11	Document stores
	#1	Native XML DBMS
	#1	RDF stores
	#7	Search engines

Score	1061.34
Rank	#2	Overall
	#2	Relational DBMS

Score	7.69
Rank	#50	Overall
	#3	Time Series DBMS

Score	2.07
Rank	#122	Overall
	#11	Graph DBMS
	#6	RDF stores

Score	0.21
Rank	#325	Overall
	#144	Relational DBMS

Website

www.progress.com/marklogic

Technical documentation

www.progress.com/marklogic/documentation

dev.mysql.com/doc

prometheus.io/docs

docs.stardog.com

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

Developer

MarkLogic Corp.

Oracle

since 2010, originally MySQL AB, then Sun

Stardog-Union

Paradigma Software

Initial release

2001

1995

2015

2010

1999

Current release

11.0, December 2022

8.4.0, April 2024

7.3.0, May 2020

5.7.5

License

Commercial or Open Source

commercial

restricted free version is available

Open Source

GPL version 2. Commercial licenses with extended functionallity are available

Open Source

Apache 2.0

commercial

60-day fully-featured trial license; 1-year fully-featured non-commercial use license for academics/students

commercial

Cloud-based only

Only available as a cloud service

DBaaS offerings (sponsored links)

Database as a Service

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Implementation language

C++

C and C++

Java

Server operating systems

Linux
OS X
Windows

FreeBSD
Linux
OS X
Solaris
Windows

Linux
Windows

Linux
macOS
Windows

Linux
OS X
Windows

Data scheme

schema-free

Schema can be enforced

yes

schema-free and OWL/RDFS-schema support

yes

Typing

predefined data types such as float or date

yes

Numeric data only

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

Import of XML data possible

Import/export of XML data possible

Secondary indexes

yes

supports real-time indexing in full-text and geospatial

yes

SQL

Support of SQL

yes

SQL92

yes

with proprietary extensions

Yes, compatible with all major SQL variants through dedicated BI/SQL Server

yes

APIs and other access methods

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

ADO.NET
JDBC
ODBC
Proprietary native API

RESTful HTTP/JSON API

GraphQL query language
HTTP API
Jena RDF API
OWL
RDF4J API
Sesame REST HTTP Protocol
SNARL
SPARQL
Spring Data
Stardog Studio
TinkerPop 3

ODBC

Supported programming languages

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

Ada
C
C#
C++
D
Delphi
Eiffel
Erlang
Haskell
Java
JavaScript (Node.js)
Objective-C
OCaml
Perl
PHP
Python
Ruby
Scheme
Tcl

.Net
C++
Go
Haskell
Java
JavaScript (Node.js)
Python
Ruby

.Net
Clojure
Groovy
Java
JavaScript
Python
Ruby

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

Server-side scripts

Stored procedures

yes

via XQuery or JavaScript

yes

proprietary syntax

user defined functions and aggregates, HTTP Server extensions in Java

yes

Triggers

yes

via event handlers

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

horizontal partitioning, sharding with MySQL Cluster or MySQL Fabric

Sharding

none

Replication methods

Methods for redundantly storing data on multiple nodes

yes

Multi-source replication
Source-replica replication

yes

by Federation

Multi-source replication in HA-Cluster

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

none

Immediate Consistency in HA-Cluster

Foreign keys

Referential integrity

yes

not for MyISAM storage engine

yes

relationships in graphs

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

ACID

not for MyISAM storage engine

ACID

Concurrency

Support for concurrent manipulation of data

yes

table locks or row locks depending on storage engine

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, with Range Indexes

yes

User concepts

Access control

Role-based access control at the document and subdocument levels

Users with fine-grained authorization concept

no user groups or roles

Access rights for users and roles

fine grained access rights according to SQL-standard

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