DBMS > Bangdb vs. NCache vs. OrientDB vs. RDF4J

System Properties Comparison Bangdb vs. NCache vs. OrientDB vs. RDF4J

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Editorial information provided by DB-Engines

Name

Description

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

Open-Source and Enterprise in-memory Key-Value Store

Multi-model DBMS (Document, Graph, Key/Value)

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

Key-value store

Document store
Graph DBMS
Key-value store

RDF store

Secondary database models

Spatial DBMS

Document store
Search engine

Using distributed Lucene

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

Score	0.16
Rank	#338	Overall
	#47	Document stores
	#32	Graph DBMS
	#31	Time Series DBMS

Score	0.96
Rank	#195	Overall
	#29	Key-value stores

Score	3.25
Rank	#89	Overall
	#16	Document stores
	#6	Graph DBMS
	#13	Key-value stores

Score	0.74
Rank	#222	Overall
	#9	RDF stores

Website

bangdb.com

www.alachisoft.com/ncache

orientdb.org

rdf4j.org

Technical documentation

docs.bangdb.com

www.alachisoft.com/resources/docs

www.orientdb.com/docs/last/index.html

rdf4j.org/documentation

Developer

Sachin Sinha, BangDB

Alachisoft

OrientDB LTD; CallidusCloud; SAP

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

Initial release

2012

2005

2010

2004

Current release

BangDB 2.0, October 2021

5.3.3, April 2024

3.2.29, March 2024

License

Commercial or Open Source

Open Source

BSD 3

Open Source

Enterprise Edition available

Open Source

Apache version 2

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#, .NET, .NET Core, Java

Java

Server operating systems

Linux

Linux
Windows

All OS with a Java JDK (>= JDK 6)

Linux
OS X
Unix
Windows

Data scheme

schema-free

Schema can be enforced for whole record ("schema-full") or for some fields only ("schema-hybrid")

yes

RDF Schemas

Typing

predefined data types such as float or date

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

partial

Supported data types are Lists, Queues, Hashsets, Dictionary and Counter

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

SQL-like query syntax and LINQ for searching the cache. Cache Synchronization with SQL Server using SQL dependency.

SQL-like query language, no joins

APIs and other access methods

Proprietary protocol
RESTful HTTP API

IDistributedCache
JCache
LINQ
Proprietary native API

Tinkerpop technology stack with Blueprints, Gremlin, Pipes
Java API
RESTful HTTP/JSON 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

.Net
.Net Core
C#
Java
JavaScript (Node.js)
Python
Scala

.Net
C
C#
C++
Clojure
Java
JavaScript
JavaScript (Node.js)
PHP
Python
Ruby
Scala

Java
PHP
Python

Server-side scripts

Stored procedures

support for stored procedures with SQL-Server CLR

Java, Javascript

yes

Triggers

yes, Notifications (with Streaming only)

yes

Notifications

Hooks

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

yes

Sharding

none

Replication methods

Methods for redundantly storing data on multiple nodes

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

yes, with selectable consistency level

Multi-source replication

none

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

could be achieved with distributed queries

Consistency concepts

Methods to ensure consistency in a distributed system

Tunable consistency, set CAP knob accordingly

Eventual Consistency
Immediate Consistency
Strong Eventual Consistency over WAN with Conflict Resolution using Bridge Topology

Foreign keys

Referential integrity

yes

relationship in graphs

Transaction concepts

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

ACID

optimistic locking and pessimistic locking

ACID

Isolation support depends on the API used

Concurrency

Support for concurrent manipulation of data

yes, optimistic concurrency control

yes

Durability

Support for making data persistent

yes, implements WAL (Write ahead log) as well

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

User concepts

Access control

yes (enterprise version only)

Authentication to access the cache via Active Directory/LDAP (possible roles: user, administrator)

Access rights for users and roles; record level security configurable

More information provided by the system vendor

Specific characteristics

NCache has been the market leader in .NET Distributed Caching since 2005 . NCache...
» more

Competitive advantages

NCache is 100% .NET/ .NET Core based which fully supports ASP.NET Core Sessions ,...
» more

Typical application scenarios

NCache enables industries like retail, finance, banking IoT, travel, ecommerce, healthcare...
» more

Key customers

Bank of America, Citi, Natures Way, Charter Spectrum, Barclays, Henry Schein, GBM,...
» more

Market metrics

Market Leader in .NET Distributed Caching since 2005.
» more

Licensing and pricing models

NCache Open Source is free on an as-is basis without any support. NCache Enterprise...
» more

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and for displaying vendor-provided information such as key customers, competitive advantages and market metrics.

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