DBMS > Bangdb vs. EsgynDB vs. NuoDB vs. Oracle Coherence vs. RDF4J

System Properties Comparison Bangdb vs. EsgynDB vs. NuoDB vs. Oracle Coherence vs. RDF4J

Editorial information provided by DB-Engines

Name

Description

Converged and high performance database for device data, events, time series, document and graph

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

NuoDB is a webscale distributed database that supports SQL and ACID transactions

Oracles in-memory data grid solution

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

Primary database model

Document store
Graph DBMS
Time Series DBMS

Relational DBMS

Key-value store

RDF store

Secondary database models

Spatial DBMS

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

Score	0.08
Rank	#347	Overall
	#47	Document stores
	#34	Graph DBMS
	#31	Time Series DBMS

Score	0.16
Rank	#329	Overall
	#146	Relational DBMS

Score	0.89
Rank	#198	Overall
	#92	Relational DBMS

Score	1.92
Rank	#130	Overall
	#22	Key-value stores

Score	0.69
Rank	#230	Overall
	#9	RDF stores

Website

bangdb.com

www.esgyn.cn

www.3ds.com/nuodb-distributed-sql-database

www.oracle.com/java/coherence

rdf4j.org

Technical documentation

docs.bangdb.com

doc.nuodb.com

docs.oracle.com/en/middleware/standalone/coherence

rdf4j.org/documentation

Developer

Sachin Sinha, BangDB

Esgyn

Dassault Systèmes

originally NuoDB, Inc.

Oracle

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

Initial release

2012

2015

2013

2007

2004

Current release

BangDB 2.0, October 2021

14.1, August 2023

License

Commercial or Open Source

Open Source

BSD 3

commercial

limited edition free

commercial

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

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Implementation language

C, C++

C++, Java

C++

Java

Server operating systems

Linux

hosted

Amazon EC2, Windows Azure, SoftLayer
Linux
OS X
Windows

All OS with a Java VM

Linux
OS X
Unix
Windows

Data scheme

schema-free

yes

schema-free

yes

RDF Schemas

Typing

predefined data types such as float or date

yes: string, long, double, int, geospatial, stream, events

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

yes

secondary, composite, nested, reverse, geospatial

yes

SQL

Support of SQL

SQL like support with command line tool

yes

APIs and other access methods

Proprietary protocol
RESTful HTTP API

ADO.NET
JDBC
ODBC

JCache
JPA
RESTful HTTP API

Java API
RIO

RDF Input/Output
Sail API
SeRQL

Sesame RDF Query Language
Sesame REST HTTP Protocol
SPARQL

Supported programming languages

C
C#
C++
Java
Python

All languages supporting JDBC/ODBC/ADO.Net

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

.Net
C++
Java

Java
PHP
Python

Server-side scripts

Stored procedures

Java Stored Procedures

Java, SQL

yes

Triggers

yes, Notifications (with Streaming only)

yes

Live Events

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding (enterprise version only). P2P based virtual network overlay with consistent hashing and chord algorithm

Sharding

data is dynamically stored/cached on the nodes where it is read/written

Sharding

none

Replication methods

Methods for redundantly storing data on multiple nodes

selectable replication factor, Knob for CAP (enterprise version only)

Multi-source replication between multi datacenters

yes

Managed transparently by NuoDB

yes, with selectable consistency level

none

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

Consistency concepts

Methods to ensure consistency in a distributed system

Tunable consistency, set CAP knob accordingly

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

tunable commit protocol

configurable

ACID

Isolation support depends on the API used

Concurrency

Support for concurrent manipulation of data

yes, optimistic concurrency control

yes

MVCC

yes

Durability

Support for making data persistent

yes, implements WAL (Write ahead log) as well

yes

optionally

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, run db with in-memory only mode

yes

Temporary table

yes

User concepts

Access control

yes (enterprise version only)

fine grained access rights according to SQL-standard

Standard SQL roles/ privileges, Administrative Users

authentification to access the cache via certificates or http basic authentication

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