DBMS > AnzoGraph DB vs. Quasardb vs. Valentina Server vs. VelocityDB

System Properties Comparison AnzoGraph DB vs. Quasardb vs. Valentina Server vs. VelocityDB

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Editorial information provided by DB-Engines

Name

Description

Scalable graph database built for online analytics and data harmonization with MPP scaling, high-performance analytical algorithms and reasoning, and virtualization

Distributed, high-performance timeseries database

Object-relational database and reports server

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

Primary database model

Graph DBMS
RDF store

Time Series DBMS

Relational DBMS

Graph DBMS
Object oriented DBMS

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Trend Chart

Score	0.27
Rank	#302	Overall
	#24	Graph DBMS
	#13	RDF stores

Score	0.19
Rank	#327	Overall
	#30	Time Series DBMS

Score	0.18
Rank	#329	Overall
	#144	Relational DBMS

Score	0.11
Rank	#347	Overall
	#35	Graph DBMS
	#15	Object oriented DBMS

Website

cambridgesemantics.com/anzograph

quasar.ai

www.valentina-db.net

velocitydb.com

Technical documentation

docs.cambridgesemantics.com/anzograph/userdoc/home.htm

doc.quasar.ai/master

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

velocitydb.com/UserGuide

Developer

Cambridge Semantics

quasardb

Paradigma Software

VelocityDB Inc

Initial release

2018

2009

1999

2011

Current release

2.3, January 2021

3.14.1, January 2024

5.7.5

7.x

License

Commercial or Open Source

commercial

free trial version available

commercial

Free community edition, Non-profit organizations and non-commercial usage are eligible for free licenses

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

C++

Server operating systems

Linux

BSD
Linux
OS X
Windows

Linux
OS X
Windows

Any that supports .NET

Data scheme

Schema-free and OWL/RDFS-schema support

schema-free

yes

Typing

predefined data types such as float or date

yes

integer and binary

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.

Secondary indexes

yes

with tags

yes

SQL

Support of SQL

SPARQL and SPARQL* as primary query language. Cypher preview.

SQL-like query language

yes

APIs and other access methods

Apache Mule
gRPC
JDBC
Kafka
OData access for BI tools
OpenCypher
RESTful HTTP API
SPARQL

HTTP API

ODBC

.Net

Supported programming languages

C++
Java
Python

.Net
C
C#
C++
Go
Java
JavaScript (Node.js)
PHP
Python
R

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

.Net

Server-side scripts

Stored procedures

user defined functions and aggregates

yes

Triggers

yes

Callbacks are triggered when data changes

Partitioning methods

Methods for storing different data on different nodes

Automatic sharding

Sharding

consistent hashing

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

Multi-source replication in MPP-Cluster

Source-replica replication with selectable replication factor

MapReduce

Offers an API for user-defined Map/Reduce methods

Kerberos/HDFS data loading

with Hadoop integration

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency in MPP-Cluster

Immediate Consistency

Foreign keys

Referential integrity

not needed 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

by using LevelDB

yes

In-memory capabilities

Is there an option to define some or all structures to be held in-memory only.

yes

Transient mode

yes

User concepts

Access control

Access rights for users and roles

Cryptographically strong user authentication and audit trail

fine grained access rights according to SQL-standard

Based on Windows Authentication

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More resources

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