DBMS > EJDB vs. GeoSpock vs. RDF4J vs. Transwarp KunDB

System Properties Comparison EJDB vs. GeoSpock vs. RDF4J vs. Transwarp KunDB

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Editorial information provided by DB-Engines

Name

GeoSpock seems to be discontinued. Therefore it will be excluded from the DB-Engines ranking.

Description

Embeddable document-store database library with JSON representation of queries (in MongoDB style)

Spatial and temporal data processing engine for extreme data scale

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

OLTP DBMS based on a distributed architecture and highly compatible with MySQL and Oracle

Primary database model

Secondary database models

Time Series DBMS

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

Score	0.27
Rank	#297	Overall
	#44	Document stores

Score	0.69
Rank	#230	Overall
	#9	RDF stores

Score	0.10
Rank	#344	Overall
	#151	Relational DBMS

Website

github.com/Softmotions/ejdb

geospock.com

rdf4j.org

www.transwarp.cn/en/product/kundb

Technical documentation

github.com/Softmotions/ejdb/blob/master/README.md

rdf4j.org/documentation

Developer

Softmotions

GeoSpock

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

Transwarp

Initial release

2012

2004

Current release

2.0, September 2019

License

Commercial or Open Source

Open Source

GPLv2

commercial

Open Source

Eclipse Distribution License (EDL), v1.0.

commercial

Cloud-based only

Only available as a cloud service

yes

DBaaS offerings (sponsored links)

Database as a Service

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Implementation language

Java, Javascript

Java

Server operating systems

server-less

hosted

Linux
OS X
Unix
Windows

Data scheme

schema-free

yes

RDF Schemas

yes

Typing

predefined data types such as float or date

yes

string, integer, double, bool, date, object_id

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

temporal, categorical

yes

SQL

Support of SQL

ANSI SQL for query only (using Presto)

yes

APIs and other access methods

in-process shared library

JDBC

Java API
RIO

RDF Input/Output
Sail API
SeRQL

Sesame RDF Query Language
Sesame REST HTTP Protocol
SPARQL

Supported programming languages

Actionscript
C
C#
C++
Go
Java
JavaScript (Node.js)
Lua
Objective-C
Pike
Python
Ruby

Java
PHP
Python

Server-side scripts

Stored procedures

yes

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

none

Automatic sharding

none

horizontal partitioning

Replication methods

Methods for redundantly storing data on multiple nodes

none

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

typically not needed, however similar functionality with collection joins possible

yes

Transaction concepts

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

ACID

Isolation support depends on the API used

ACID

Concurrency

Support for concurrent manipulation of data

yes

Read/Write Locking

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.

User concepts

Access control

Access rights for users can be defined per table

yes

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More resources

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4 September 2019, VanillaPlus

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8 October 2020, Cambridge Independent

Big data processing techniques to streamline analytics
5 October 2018, TechTarget

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provided by Google News

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