DBMS > Kingbase vs. Kyligence Enterprise vs. RDF4J vs. Transwarp Hippo

System Properties Comparison Kingbase vs. Kyligence Enterprise vs. RDF4J vs. Transwarp Hippo

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Editorial information provided by DB-Engines

Name

Description

An enterprise-class RDBMS compatible with PostgreSQL and Oracle and widely used in China.

A distributed analytics engine for big data, built on top of Apache Kylin

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

Cloud-native distributed Vector DBMS that supports storage, retrieval, and management of massive vector-based datasets

Primary database model

Relational DBMS

RDF store

Vector DBMS

Secondary database models

Document store
Spatial DBMS

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

Score	0.45
Rank	#262	Overall
	#123	Relational DBMS

Score	0.40
Rank	#269	Overall
	#124	Relational DBMS

Score	0.69
Rank	#230	Overall
	#9	RDF stores

Score	0.00
Rank	#383	Overall
	#13	Vector DBMS

Website

www.kingbase.com.cn

kyligence.io/kyligence-enterprise

rdf4j.org

www.transwarp.cn/en/subproduct/hippo

Technical documentation

rdf4j.org/documentation

Developer

BeiJing KINGBASE Information technologies inc.

Kyligence, Inc.

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

Initial release

1999

2016

2004

2023

Current release

V8.0, August 2021

1.0, May 2023

License

Commercial or Open Source

commercial

Open Source

Eclipse Distribution License (EDL), v1.0.

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 and Java

Java

C++

Server operating systems

Linux
Windows

Linux

Linux
OS X
Unix
Windows

Linux
macOS

Data scheme

yes

RDF Schemas

Typing

predefined data types such as float or date

yes

Vector, Numeric and String

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

ANSI SQL for queries (using Apache Calcite)

APIs and other access methods

ADO.NET
gokb
JDBC
kdbndp
ODBC
PDI
PDO
Pro*C
psycopg2
QT

JDBC
ODBC
RESTful HTTP API

Java API
RIO

RDF Input/Output
Sail API
SeRQL

Sesame RDF Query Language
Sesame REST HTTP Protocol
SPARQL

RESTful HTTP API

Supported programming languages

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

Java
PHP
Python

C++
Java
Python

Server-side scripts

Stored procedures

user defined functions

yes

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

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

none

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

yes

none

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

Consistency concepts

Methods to ensure consistency in a distributed system

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

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

fine grained access rights according to SQL-standard

Role based access control and fine grained access rights

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