DBMS > SAP IQ vs. Stardog vs. VelocityDB vs. VoltDB

System Properties Comparison SAP IQ vs. Stardog vs. VelocityDB vs. VoltDB

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Editorial information provided by DB-Engines

Name

Description

Columnar RDBMS optimized for Big Data analytics

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

A .NET Object Database that can be embedded/distributed and extended to a graph data model (VelocityGraph)

Distributed In-Memory NewSQL RDBMS

Used for OLTP applications with a high frequency of relatively simple transactions, that can hold all their data in memory

Primary database model

Relational DBMS

column-oriented

Graph DBMS
RDF store

Graph DBMS
Object oriented DBMS

Relational DBMS

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

Score	2.64
Rank	#108	Overall
	#52	Relational DBMS

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

Score	0.11
Rank	#354	Overall
	#37	Graph DBMS
	#15	Object oriented DBMS

Score	1.47
Rank	#157	Overall
	#73	Relational DBMS

Website

www.sap.com/products/technology-platform/sybase-iq-big-data-management.html

www.stardog.com

velocitydb.com

www.voltdb.com

Technical documentation

help.sap.com/docs/SAP_IQ

docs.stardog.com

velocitydb.com/UserGuide

docs.voltdb.com

Developer

SAP, formerly Sybase

Stardog-Union

VelocityDB Inc

VoltDB Inc.

Initial release

1994

2010

2011

2010

Current release

16.1 SPS04, April 2019

7.3.0, May 2020

7.x

11.3, April 2022

License

Commercial or Open Source

commercial

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

commercial

Open Source

AGPL for Community Edition, commercial license for Enterprise, AWS, and Pro Editions

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

Java

Java, C++

Server operating systems

AIX
HP-UX
Linux
Solaris
Windows

Linux
macOS
Windows

Any that supports .NET

Linux
OS X

for development

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

yes

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

yes

only a subset of SQL 99

APIs and other access methods

ADO.NET
JDBC
ODBC
RESTful HTTP API

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

.Net

Java API
JDBC
RESTful HTTP/JSON API

Supported programming languages

C
C#
C++
Java
Perl
PHP
Python
Ruby

.Net
Clojure
Groovy
Java
JavaScript
Python
Ruby

.Net

C#
C++
Erlang

not officially supported
Go
Java
JavaScript

Node.js
PHP
Python

Server-side scripts

Stored procedures

yes

user defined functions and aggregates, HTTP Server extensions in Java

Java

Triggers

yes

via event handlers

Callbacks are triggered when data changes

Partitioning methods

Methods for storing different data on different nodes

shared disk or shared nothing architectures with SAP IQ Multiplexer

none

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

SAP/Sybase Replication Server

Multi-source replication in HA-Cluster

Multi-source replication
Source-replica replication

MapReduce

Offers an API for user-defined Map/Reduce methods

Hadoop integration

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Immediate Consistency in HA-Cluster

Immediate Consistency

Foreign keys

Referential integrity

yes

relationships in graphs

FOREIGN KEY constraints are not supported

Transaction concepts

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

ACID

Transactions are executed single-threaded within stored procedures

Concurrency

Support for concurrent manipulation of data

yes

Data access is serialized by the server

Durability

Support for making data persistent

yes

Snapshots and command logging

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 roles

Based on Windows Authentication

Users and roles with access to stored procedures

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