DBMS > BaseX vs. Dragonfly vs. Infobright vs. OpenQM

System Properties Comparison BaseX vs. Dragonfly vs. Infobright vs. OpenQM

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Editorial information provided by DB-Engines

Name

Description

Light-weight Native XML DBMS with support for XQuery 3.0 and interactive GUI.

A drop-in Redis replacement that scales vertically to support millions of operations per second and terabyte sized workloads, all on a single instance

High performant column-oriented DBMS for analytic workloads using MySQL or PostgreSQL as a frontend

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

Primary database model

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

Score	1.73
Rank	#142	Overall
	#4	Native XML DBMS

Score	0.41
Rank	#266	Overall
	#38	Key-value stores

Score	0.96
Rank	#194	Overall
	#91	Relational DBMS

Score	0.27
Rank	#298	Overall
	#10	Multivalue DBMS

Website

basex.org

github.com/dragonflydb/dragonfly
www.dragonflydb.io

ignitetech.com/softwarelibrary/infobrightdb

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

Technical documentation

docs.basex.org

www.dragonflydb.io/docs

Developer

BaseX GmbH

DragonflyDB team and community contributors

Ignite Technologies Inc.; formerly InfoBright Inc.

Rocket Software, originally Martin Phillips

Initial release

2007

2023

2005

1993

Current release

10.7, August 2023

1.0, March 2023

3.4-12

License

Commercial or Open Source

Open Source

BSD license

Open Source

BSL 1.1

commercial

The open source (GPLv2) version did not support inserts/updates/deletes and was discontinued with July 2016

Open Source

GPLv2, extended commercial license available

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++

Server operating systems

Linux
OS X
Windows

Linux

Linux
Windows

AIX
FreeBSD
Linux
macOS
Raspberry Pi
Solaris
Windows

Data scheme

schema-free

scheme-free

yes

with some exceptions

Typing

predefined data types such as float or date

XQuery supports types

strings, hashes, lists, sets, sorted sets, bit arrays

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

Secondary indexes

yes

Knowledge Grid Technology used instead

yes

SQL

Support of SQL

yes

APIs and other access methods

Java API
RESTful HTTP API
RESTXQ
WebDAV
XML:DB
XQJ

Proprietary protocol

RESP - REdis Serialization Protocol

ADO.NET
JDBC
ODBC

Supported programming languages

Actionscript
C
C#
Haskell
Java
JavaScript

Node.js
Lisp
Perl
PHP
Python
Qt
Rebol
Ruby
Scala
Visual Basic

C
C#
C++
Clojure
D
Dart
Elixir
Erlang
Go
Haskell
Java
JavaScript (Node.js)
Lisp
Lua
Objective-C
Perl
PHP
Python
R
Ruby
Rust
Scala
Swift
Tcl

.Net
C
C#
C++
D
Eiffel
Erlang
Haskell
Java
Objective-C
OCaml
Perl
PHP
Python
Ruby
Scheme
Tcl

.Net
Basic
C
Java
Objective C
PHP
Python

Server-side scripts

Stored procedures

yes

Lua

yes

Triggers

yes

via events

publish/subscribe channels provide some trigger functionality

yes

Partitioning methods

Methods for storing different data on different nodes

none

yes

Replication methods

Methods for redundantly storing data on multiple nodes

none

Source-replica replication

yes

MapReduce

Offers an API for user-defined Map/Reduce methods

Consistency concepts

Methods to ensure consistency in a distributed system

Eventual Consistency

Immediate Consistency

Foreign keys

Referential integrity

Transaction concepts

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

multiple readers, single writer

Atomic execution of command blocks and scripts

ACID

Concurrency

Support for concurrent manipulation of data

yes

yes, strict serializability by the server

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

Users with fine-grained authorization concept on 4 levels

Password-based authentication

fine grained access rights according to SQL-standard

exploiting MySQL or PostgreSQL frontend capabilities

Access rights can be defined down to the item level

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