DBMS > Bangdb vs. Greenplum vs. LevelDB vs. OushuDB vs. RDF4J

System Properties Comparison Bangdb vs. Greenplum vs. LevelDB vs. OushuDB vs. RDF4J

Editorial information provided by DB-Engines

Name

Description

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

Analytic Database platform built on PostgreSQL. Full name is Pivotal Greenplum Database

A logical database in Greenplum is an array of individual PostgreSQL databases working together to present a single database image.

Embeddable fast key-value storage library that provides an ordered mapping from string keys to string values

A data warehouse powered by Apache HAWQ supporting descriptive analysis and advanced machine learning

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

Secondary database models

Spatial DBMS

Document store
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	8.37
Rank	#48	Overall
	#30	Relational DBMS

Score	2.35
Rank	#111	Overall
	#19	Key-value stores

Score	0.04
Rank	#363	Overall
	#154	Relational DBMS

Score	0.69
Rank	#230	Overall
	#9	RDF stores

Website

bangdb.com

greenplum.org

github.com/google/leveldb

www.oushu.com/product/oushuDB

rdf4j.org

Technical documentation

docs.bangdb.com

docs.greenplum.org

github.com/google/leveldb/blob/main/doc/index.md

www.oushu.com/documentation

rdf4j.org/documentation

Developer

Sachin Sinha, BangDB

Pivotal Software Inc.

Google

Oushu

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

Initial release

2012

2005

2011

2004

Current release

BangDB 2.0, October 2021

7.0.0, September 2023

1.23, February 2021

4.0.1, August 2020

License

Commercial or Open Source

Open Source

BSD 3

Open Source

Apache 2.0

Open Source

BSD

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

Providers of DBaaS offerings, please contact us to be listed.

Implementation language

C, C++

C++

Java

Server operating systems

Linux

Illumos
Linux
OS X
Windows

Linux

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.

yes

since Version 4.2

Secondary indexes

yes

secondary, composite, nested, reverse, geospatial

yes

SQL

Support of SQL

SQL like support with command line tool

yes

Full-featured ANSI SQL support

APIs and other access methods

Proprietary protocol
RESTful HTTP API

JDBC
ODBC

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

C
Java
Perl
Python
R

C++
Go
Java

3rd party binding
JavaScript (Node.js)

3rd party binding
Python

3rd party binding

C
C++

Java
PHP
Python

Server-side scripts

Stored procedures

yes

Triggers

yes, Notifications (with Streaming only)

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

none

yes

none

Replication methods

Methods for redundantly storing data on multiple nodes

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

Source-replica replication

none

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

Hadoop integration

Consistency concepts

Methods to ensure consistency in a distributed system

Tunable consistency, set CAP knob accordingly

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, optimistic concurrency control

yes

Durability

Support for making data persistent

yes, implements WAL (Write ahead log) as well

yes

with automatic compression on writes

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

User concepts

Access control

yes (enterprise version only)

fine grained access rights according to SQL-standard

Kerberos, SSL and role based access

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