DBMS > Badger vs. GBase vs. Hyprcubd vs. OpenQM vs. RDF4J

System Properties Comparison Badger vs. GBase vs. Hyprcubd vs. OpenQM vs. RDF4J

Editorial information provided by DB-Engines

Name

Hyprcubd seems to be discontinued. Therefore it is excluded from the DB-Engines ranking.

Description

An embeddable, persistent, simple and fast Key-Value Store, written purely in Go.

Widely used RDBMS in China, including analytical, transactional, distributed transactional, and cloud-native data warehousing.

Serverless Time Series DBMS

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

RDF4J is a Java framework for processing RDF data, supporting both memory-based and a disk-based storage.

Primary database model

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

Score	0.22
Rank	#320	Overall
	#47	Key-value stores

Score	1.05
Rank	#186	Overall
	#86	Relational DBMS

Score	0.34
Rank	#284	Overall
	#10	Multivalue DBMS

Score	0.74
Rank	#222	Overall
	#9	RDF stores

Website

github.com/dgraph-io/badger

www.gbase.cn

hyprcubd.com (offline)

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

rdf4j.org

Technical documentation

godoc.org/github.com/dgraph-io/badger

rdf4j.org/documentation

Developer

DGraph Labs

General Data Technology Co., Ltd.

Hyprcubd, Inc.

Rocket Software, originally Martin Phillips

Since 2016 officially forked into an Eclipse project, former developer was Aduna Software.

Initial release

2017

2004

1993

2004

Current release

GBase 8a, GBase 8s, GBase 8c

3.4-12

License

Commercial or Open Source

Open Source

Apache 2.0

commercial

Open Source

GPLv2, extended commercial license available

Open Source

Eclipse Distribution License (EDL), v1.0.

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, Java, Python

Java

Server operating systems

BSD
Linux
OS X
Solaris
Windows

Linux

hosted

AIX
FreeBSD
Linux
macOS
Raspberry Pi
Solaris
Windows

Linux
OS X
Unix
Windows

Data scheme

schema-free

yes

with some exceptions

yes

RDF Schemas

Typing

predefined data types such as float or date

yes

time, int, uint, float, string

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

SQL

Support of SQL

Standard with numerous extensions

SQL-like query language

APIs and other access methods

ADO.NET
C API
JDBC
ODBC

gRPC (https)

Java API
RIO

RDF Input/Output
Sail API
SeRQL

Sesame RDF Query Language
Sesame REST HTTP Protocol
SPARQL

Supported programming languages

.Net
Basic
C
Java
Objective C
PHP
Python

Java
PHP
Python

Server-side scripts

Stored procedures

user defined functions

yes

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

none

horizontal partitioning (by range, list and hash) and vertical partitioning

yes

none

Replication methods

Methods for redundantly storing data on multiple nodes

none

yes

none

MapReduce

Offers an API for user-defined Map/Reduce methods

Consistency concepts

Methods to ensure consistency in a distributed system

none

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

Isolation support depends on the API used

Concurrency

Support for concurrent manipulation of data

yes

Durability

Support for making data persistent

yes

in-memory storage is supported as well

In-memory capabilities

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

User concepts

Access control

yes

token access

Access rights can be defined down to the item level

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