DBMS > Bangdb vs. jBASE vs. Oracle Berkeley DB vs. OrigoDB

System Properties Comparison Bangdb vs. jBASE vs. Oracle Berkeley DB vs. OrigoDB

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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

A robust multi-value DBMS comprising development tools and middleware

Widely used in-process key-value store

A fully ACID in-memory object graph database

Primary database model

Document store
Graph DBMS
Time Series DBMS

Multivalue DBMS

Key-value store

supports sorted and unsorted key sets
Native XML DBMS

in the Oracle Berkeley DB XML version

Document store
Object oriented DBMS

Secondary database models

Spatial DBMS

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	1.49
Rank	#156	Overall
	#3	Multivalue DBMS

Score	2.01
Rank	#126	Overall
	#21	Key-value stores
	#3	Native XML DBMS

Score	0.06
Rank	#380	Overall
	#50	Document stores
	#18	Object oriented DBMS

Website

bangdb.com

www.rocketsoftware.com/products/rocket-multivalue-application-development-platform/rocket-jbase

www.oracle.com/database/technologies/related/berkeleydb.html

origodb.com

Technical documentation

docs.bangdb.com

docs.rocketsoftware.com/bundle?labelkey=jbase_5.9

docs.oracle.com/cd/E17076_05/html/index.html

origodb.com/docs

Developer

Sachin Sinha, BangDB

Rocket Software (formerly Zumasys)

Oracle

originally developed by Sleepycat, which was acquired by Oracle

Robert Friberg et al

Initial release

2012

1991

1994

2009

under the name LiveDB

Current release

BangDB 2.0, October 2021

5.7

18.1.40, May 2020

License

Commercial or Open Source

Open Source

BSD 3

commercial

Open Source

commercial license available

Open Source

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, C++ (depending on the Berkeley DB edition)

Server operating systems

Linux

AIX
Linux
Windows

AIX
Android
FreeBSD
iOS
Linux
OS X
Solaris
VxWorks
Windows

Linux
Windows

Data scheme

schema-free

yes

Typing

predefined data types such as float or date

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

optional

User defined using .NET types and collections

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

only with the Berkeley DB XML edition

can be achieved using .NET

Secondary indexes

yes

secondary, composite, nested, reverse, geospatial

yes

SQL

Support of SQL

SQL like support with command line tool

Embedded SQL for jBASE in BASIC

yes

SQL interfaced based on SQLite is available

APIs and other access methods

Proprietary protocol
RESTful HTTP API

JDBC
ODBC
Proprietary protocol
RESTful HTTP API
SOAP-based API

.NET Client API
HTTP API
LINQ

Supported programming languages

C
C#
C++
Java
Python

.Net
Basic
Jabbascript
Java

.Net

Figaro is a .Net framework assembly that extends Berkeley DB XML into an embeddable database engine for .NET
others

Third-party libraries to manipulate Berkeley DB files are available for many languages
C
C#
C++
Java
JavaScript (Node.js)

3rd party binding
Perl
Python
Tcl

.Net

Server-side scripts

Stored procedures

yes

Triggers

yes, Notifications (with Streaming only)

yes

only for the SQL API

yes

Domain Events

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

horizontal partitioning

client side managed; servers are not synchronized

Replication methods

Methods for redundantly storing data on multiple nodes

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

yes

Source-replica replication

MapReduce

Offers an API for user-defined Map/Reduce methods

Consistency concepts

Methods to ensure consistency in a distributed system

Tunable consistency, set CAP knob accordingly

Foreign keys

Referential integrity

depending on model

Transaction concepts

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

ACID

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

Write ahead log

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)

Access rights can be defined down to the item level

Role based authorization

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