DBMS > EsgynDB vs. KairosDB vs. OrigoDB vs. RDF4J

System Properties Comparison EsgynDB vs. KairosDB vs. OrigoDB vs. RDF4J

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Editorial information provided by DB-Engines

Name

Description

Enterprise-class SQL-on-Hadoop solution, powered by Apache Trafodion

Distributed Time Series DBMS based on Cassandra or H2

A fully ACID in-memory object graph database

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

Primary database model

Relational DBMS

Time Series DBMS

Document store
Object oriented DBMS

RDF store

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

Score	0.23
Rank	#319	Overall
	#141	Relational DBMS

Score	0.71
Rank	#230	Overall
	#20	Time Series DBMS

Score	0.03
Rank	#378	Overall
	#51	Document stores
	#18	Object oriented DBMS

Score	0.71
Rank	#231	Overall
	#9	RDF stores

Website

www.esgyn.cn

github.com/kairosdb/kairosdb

origodb.com

rdf4j.org

Technical documentation

kairosdb.github.io

origodb.com/docs

rdf4j.org/documentation

Developer

Esgyn

Robert Friberg et al

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

Initial release

2015

2013

2009

under the name LiveDB

2004

Current release

1.2.2, November 2018

License

Commercial or Open Source

commercial

Open Source

Apache 2.0

Open Source

Eclipse Distribution License (EDL), v1.0.

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++, Java

Java

Server operating systems

Linux

Linux
OS X
Windows

Linux
Windows

Linux
OS X
Unix
Windows

Data scheme

yes

schema-free

yes

RDF Schemas

Typing

predefined data types such as float or date

yes

User defined using .NET types and collections

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.

can be achieved using .NET

Secondary indexes

yes

SQL

Support of SQL

yes

APIs and other access methods

ADO.NET
JDBC
ODBC

Graphite protocol
HTTP REST
Telnet API

.NET Client API
HTTP API
LINQ

Java API
RIO

RDF Input/Output
Sail API
SeRQL

Sesame RDF Query Language
Sesame REST HTTP Protocol
SPARQL

Supported programming languages

All languages supporting JDBC/ODBC/ADO.Net

Java
JavaScript

Node.js
PHP
Python

.Net

Java
PHP
Python

Server-side scripts

Stored procedures

Java Stored Procedures

yes

Triggers

yes

Domain Events

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

based on Cassandra

horizontal partitioning

client side managed; servers are not synchronized

none

Replication methods

Methods for redundantly storing data on multiple nodes

Multi-source replication between multi datacenters

selectable replication factor

based on Cassandra

Source-replica replication

none

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Eventual Consistency

based on Cassandra
Immediate Consistency

based on Cassandra

Foreign keys

Referential integrity

yes

depending on model

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

Write ahead log

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.

yes

User concepts

Access control

fine grained access rights according to SQL-standard

simple password-based access control

Role based authorization

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More resources

Recent citations in the news

The re-emergence of time-series – O'Reilly
6 April 2013, O'Reilly Media

provided by Google News

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