DBMS > ArcadeDB vs. OpenQM vs. Oracle Berkeley DB vs. SWC-DB vs. VelocityDB

System Properties Comparison ArcadeDB vs. OpenQM vs. Oracle Berkeley DB vs. SWC-DB vs. VelocityDB

Editorial information provided by DB-Engines

Name

Description

Fast and scalable multi-model DBMS, originally forked from OrientDB but most of the code has been rewritten

QpenQM is a high-performance, self-tuning, multi-value DBMS

Widely used in-process key-value store

A high performance, scalable Wide Column DBMS

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

Primary database model

Document store
Graph DBMS
Key-value store
Time Series DBMS

in next version

Multivalue DBMS

Key-value store

supports sorted and unsorted key sets
Native XML DBMS

in the Oracle Berkeley DB XML version

Wide column store

Graph DBMS
Object oriented DBMS

Secondary database models

Time Series DBMS

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

Score	0.02
Rank	#374	Overall
	#52	Document stores
	#38	Graph DBMS
	#56	Key-value stores
	#38	Time Series DBMS

Score	0.28
Rank	#291	Overall
	#10	Multivalue DBMS

Score	1.88
Rank	#130	Overall
	#23	Key-value stores
	#3	Native XML DBMS

Score	0.01
Rank	#378	Overall
	#13	Wide column stores

Score	0.00
Rank	#385	Overall
	#40	Graph DBMS
	#21	Object oriented DBMS

Website

arcadedb.com

www.rocketsoftware.com/products/rocket-multivalue-application-development-platform/rocket-open-qm

www.oracle.com/database/technologies/related/berkeleydb.html

github.com/kashirin-alex/swc-db
www.swcdb.org

velocitydb.com

Technical documentation

docs.arcadedb.com

docs.oracle.com/cd/E17076_05/html/index.html

velocitydb.com/UserGuide

Developer

Arcade Data

Rocket Software, originally Martin Phillips

Oracle

originally developed by Sleepycat, which was acquired by Oracle

Alex Kashirin

VelocityDB Inc

Initial release

2021

1993

1994

2020

2011

Current release

September 2021

3.4-12

18.1.40, May 2020

0.5, April 2021

7.x

License

Commercial or Open Source

Open Source

Apache Version 2.0

Open Source

GPLv2, extended commercial license available

Open Source

commercial license available

Open Source

GPL V3

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

Java

C, Java, C++ (depending on the Berkeley DB edition)

C++

Server operating systems

All OS with a Java VM

AIX
FreeBSD
Linux
macOS
Raspberry Pi
Solaris
Windows

AIX
Android
FreeBSD
iOS
Linux
OS X
Solaris
VxWorks
Windows

Linux

Any that supports .NET

Data scheme

schema-free

yes

with some exceptions

schema-free

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.

yes

only with the Berkeley DB XML edition

Secondary indexes

yes

SQL

Support of SQL

SQL-like query language, no joins

yes

SQL interfaced based on SQLite is available

SQL-like query language

APIs and other access methods

JDBC
MongoDB API
OpenCypher
PostgreSQL wire protocol
Redis API
RESTful HTTP/JSON API
TinkerPop Gremlin

Proprietary protocol
Thrift

.Net

Supported programming languages

Java

.Net
Basic
C
Java
Objective C
PHP
Python

.Net

Figaro is a .Net framework assembly that extends Berkeley DB XML into an embeddable database engine for .NET
others

Third-party libraries to manipulate Berkeley DB files are available for many languages
C
C#
C++
Java
JavaScript (Node.js)

3rd party binding
Perl
Python
Tcl

C++

.Net

Server-side scripts

Stored procedures

yes

Triggers

yes

only for the SQL API

Callbacks are triggered when data changes

Partitioning methods

Methods for storing different data on different nodes

yes

none

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

Source-replica replication

yes

Source-replica replication

MapReduce

Offers an API for user-defined Map/Reduce methods

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Foreign keys

Referential integrity

yes

relationship in graphs

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 can be defined down to the item level

Based on Windows Authentication

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