DBMS > Microsoft SQL Server vs. Rockset vs. Spark SQL vs. Virtuoso

System Properties Comparison Microsoft SQL Server vs. Rockset vs. Spark SQL vs. Virtuoso

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Editorial information provided by DB-Engines

Name

Description

Microsofts flagship relational DBMS

A scalable, reliable search and analytics service in the cloud, built on RocksDB

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

Virtuoso is a multi-model hybrid-RDBMS that supports management of data represented as relational tables and/or property graphs

Primary database model

Relational DBMS

Document store

Relational DBMS

Document store
Graph DBMS
Native XML DBMS
Relational DBMS
RDF store
Search engine

Secondary database models

Document store
Graph DBMS
Spatial DBMS

Relational DBMS
Search engine

Spatial DBMS

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

Score	824.29
Rank	#3	Overall
	#3	Relational DBMS

Score	0.79
Rank	#211	Overall
	#35	Document stores

Score	18.96
Rank	#33	Overall
	#20	Relational DBMS

Score	4.26
Rank	#78	Overall
	#13	Document stores
	#4	Graph DBMS
	#2	Native XML DBMS
	#42	Relational DBMS
	#2	RDF stores
	#9	Search engines

Website

www.microsoft.com/en-us/sql-server

rockset.com

spark.apache.org/sql

virtuoso.openlinksw.com

Technical documentation

learn.microsoft.com/en-US/sql/sql-server

docs.rockset.com

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

docs.openlinksw.com/virtuoso

Developer

Microsoft

Rockset

Apache Software Foundation

OpenLink Software

Initial release

1989

2019

2014

1998

Current release

SQL Server 2022, November 2022

3.5.0 ( 2.13), September 2023

7.2.11, September 2023

License

Commercial or Open Source

commercial

restricted free version is available

commercial

Open Source

Apache 2.0

Open Source

GPLv2, extended commercial license available

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++

Scala

Server operating systems

Linux
Windows

hosted

Linux
OS X
Windows

AIX
FreeBSD
HP-UX
Linux
OS X
Solaris
Windows

Data scheme

yes

schema-free

yes

SQL - Standard relational schema
RDF - Quad (S, P, O, G) or Triple (S, P, O)
XML - DTD, XML Schema
DAV - freeform filesystem objects, plus User Defined Types a/k/a Dynamic Extension Type

Typing

predefined data types such as float or date

yes

dynamic typing

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

ingestion from XML files supported

yes

Secondary indexes

yes

all fields are automatically indexed

yes

SQL

Support of SQL

yes

Read-only SQL queries, including JOINs

SQL-like DML and DDL statements

yes

SQL-92, SQL-200x, SQL-3, SQLX

APIs and other access methods

ADO.NET
JDBC
ODBC
OLE DB
Tabular Data Stream (TDS)

HTTP REST

JDBC
ODBC

ADO.NET
GeoSPARQL
HTTP API
JDBC
Jena RDF API
ODBC
OLE DB
RDF4J API
RESTful HTTP API
Sesame REST HTTP Protocol
SOAP webservices
SPARQL 1.1
WebDAV
XPath
XQuery
XSLT

Supported programming languages

C#
C++
Delphi
Go
Java
JavaScript (Node.js)
PHP
Python
R
Ruby
Visual Basic

Go
Java
JavaScript (Node.js)
Python

Java
Python
R
Scala

.Net
C
C#
C++
Java
JavaScript
Perl
PHP
Python
Ruby
Visual Basic

Server-side scripts

Stored procedures

Transact SQL, .NET languages, R, Python and (with SQL Server 2019) Java

yes

Virtuoso PL

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

tables can be distributed across several files (horizontal partitioning); sharding through federation

Automatic sharding

yes, utilizing Spark Core

yes

Replication methods

Methods for redundantly storing data on multiple nodes

yes, but depending on the SQL-Server Edition

yes

none

Chain, star, and bi-directional replication
Multi-source replication
Source-replica replication

MapReduce

Offers an API for user-defined Map/Reduce methods

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

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

fine grained access rights according to SQL-standard

Access rights for users and organizations can be defined via Rockset console

Fine-grained Attribute-Based Access Control (ABAC) in addition to typical coarse-grained Role-Based Access Control (RBAC) according to SQL-standard. Pluggable authentication with supported standards (LDAP, Active Directory, Kerberos)

More information provided by the system vendor

Specific characteristics

Virtuoso is a modern multi-model RDBMS for managing data represented as tabular relations...
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Competitive advantages

Performance & Scale — as exemplified by DBpedia and the LOD Cloud it spawned, i.e.,...
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Typical application scenarios

Used for — Analytics/BI Conceptual Data Virtualization Enterprise Knowledge Graphs...
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Key customers

Broad use across enterprises and governments including — European Union (EU) US Government...
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Market metrics

Largest installed-base of Multi-Model RDBMS for AI-friendly Knowledge Graphs Platform...
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Licensing and pricing models

Available in both Commercial Enterprise and Open Source (GPL v2) Editions Feature...
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