DBMS > mSQL vs. Spark SQL vs. Stardog vs. Valentina Server

System Properties Comparison mSQL vs. Spark SQL vs. Stardog vs. Valentina Server

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Editorial information provided by DB-Engines

Name

Description

mSQL (Mini SQL) is a simple and lightweight RDBMS

Spark SQL is a component on top of 'Spark Core' for structured data processing

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

Object-relational database and reports server

Primary database model

Relational DBMS

Graph DBMS
RDF store

Relational DBMS

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

Score	1.27
Rank	#169	Overall
	#76	Relational DBMS

Score	18.04
Rank	#33	Overall
	#20	Relational DBMS

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

Score	0.21
Rank	#325	Overall
	#144	Relational DBMS

Website

hughestech.com.au/products/msql

spark.apache.org/sql

www.stardog.com

www.valentina-db.net

Technical documentation

spark.apache.org/docs/latest/sql-programming-guide.html

docs.stardog.com

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

Developer

Hughes Technologies

Apache Software Foundation

Stardog-Union

Paradigma Software

Initial release

1994

2014

2010

1999

Current release

4.4, October 2021

3.5.0 ( 2.13), September 2023

7.3.0, May 2020

5.7.5

License

Commercial or Open Source

commercial

free licenses can be provided

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

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

Implementation language

Scala

Java

Server operating systems

AIX
HP-UX
Linux
OS X
Solaris SPARC/x86
Windows

Linux
OS X
Windows

Linux
macOS
Windows

Linux
OS X
Windows

Data scheme

yes

schema-free and OWL/RDFS-schema support

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.

Import/export of XML data possible

Secondary indexes

yes

supports real-time indexing in full-text and geospatial

yes

SQL

Support of SQL

A subset of ANSI SQL is implemented

no subqueries, aggregate functions, views, foreign keys, triggers

SQL-like DML and DDL statements

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

yes

APIs and other access methods

JDBC
ODBC

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++
Delphi
Java
Perl
PHP
Tcl

Java
Python
R
Scala

.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

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

none

yes, utilizing Spark Core

none

Replication methods

Methods for redundantly storing data on multiple nodes

none

Multi-source replication in HA-Cluster

MapReduce

Offers an API for user-defined Map/Reduce methods

Consistency concepts

Methods to ensure consistency in a distributed system

none

Immediate Consistency in HA-Cluster

Foreign keys

Referential integrity

yes

relationships in graphs

yes

Transaction concepts

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

ACID

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

User concepts

Access control

Access rights for users and roles

fine grained access rights according to SQL-standard

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