DBMS > MarkLogic vs. Microsoft Azure AI Search vs. OushuDB vs. SQLite vs. Valentina Server

System Properties Comparison MarkLogic vs. Microsoft Azure AI Search vs. OushuDB vs. SQLite vs. Valentina Server

Editorial information provided by DB-Engines

Name

Description

Operational and transactional Enterprise NoSQL database

Search-as-a-service for web and mobile app development

A data warehouse powered by Apache HAWQ supporting descriptive analysis and advanced machine learning

Widely used embeddable, in-process RDBMS

Object-relational database and reports server

Primary database model

Document store
Native XML DBMS
RDF store

as of version 7
Search engine

Search engine

Relational DBMS

Secondary database models

Vector 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	5.52
Rank	#59	Overall
	#6	Search engines

Score	0.10
Rank	#355	Overall
	#154	Relational DBMS

Score	111.41
Rank	#10	Overall
	#7	Relational DBMS

Score	0.21
Rank	#325	Overall
	#144	Relational DBMS

Website

www.progress.com/marklogic

azure.microsoft.com/en-us/services/search

www.oushu.com/product/oushuDB

www.sqlite.org

www.valentina-db.net

Technical documentation

www.progress.com/marklogic/documentation

learn.microsoft.com/en-us/azure/search

www.oushu.com/documentation

www.sqlite.org/docs.html

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

Developer

MarkLogic Corp.

Microsoft

Oushu

Dwayne Richard Hipp

Paradigma Software

Initial release

2001

2015

2000

1999

Current release

11.0, December 2022

4.0.1, August 2020

3.46.0 (23 May 2024), May 2024

5.7.5

License

Commercial or Open Source

commercial

restricted free version is available

commercial

Open Source

Public Domain

commercial

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.

Implementation language

C++

Server operating systems

Linux
OS X
Windows

hosted

Linux

server-less

Linux
OS X
Windows

Data scheme

schema-free

Schema can be enforced

yes

dynamic column types

yes

Typing

predefined data types such as float or date

yes

not rigid because of 'dynamic typing' concept.

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

yes

SQL92

Full-featured ANSI SQL support

yes

SQL-92 is not fully supported

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

RESTful HTTP API

JDBC
ODBC

ADO.NET

inofficial driver
JDBC

inofficial driver
ODBC

inofficial driver

ODBC

Supported programming languages

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

C#
Java
JavaScript
Python

C
C++

Actionscript
Ada
Basic
C
C#
C++
D
Delphi
Forth
Fortran
Haskell
Java
JavaScript
Lisp
Lua
MatLab
Objective-C
OCaml
Perl
PHP
PL/SQL
Python
R
Ruby
Scala
Scheme
Smalltalk
Tcl

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

Server-side scripts

Stored procedures

yes

via XQuery or JavaScript

yes

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

Implicit feature of the cloud service

yes

none

Replication methods

Methods for redundantly storing data on multiple nodes

yes

Implicit feature of the cloud service

none

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

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

Hadoop integration

Consistency concepts

Methods to ensure consistency in a distributed system

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

ACID

Concurrency

Support for concurrent manipulation of data

yes

via file-system locks

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

yes

using Azure authentication

Kerberos, SSL and role based access

fine grained access rights according to SQL-standard

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