DBMS > BigchainDB vs. DataFS vs. EXASOL vs. GBase vs. Oracle Berkeley DB

System Properties Comparison BigchainDB vs. DataFS vs. EXASOL vs. GBase vs. Oracle Berkeley DB

Editorial information provided by DB-Engines

Name

Description

BigchainDB is scalable blockchain database offering decentralization, immutability and native assets

All data is stored inside objects which are linked by so-called link attributes. Objects consist of classes which can be extended and de-extended at runtime. Graphs can be defined with a struct.

High-performance, in-memory, MPP database specifically designed for in-memory analytics.

Widely used RDBMS in China, including analytical, transactional, distributed transactional, and cloud-native data warehousing.

Widely used in-process key-value store

Primary database model

supports sorted and unsorted key sets
Native XML DBMS

in the Oracle Berkeley DB XML version

Secondary database models

Graph DBMS

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

Score	0.76
Rank	#216	Overall
	#36	Document stores

Score	0.02
Rank	#369	Overall
	#18	Object oriented DBMS

Score	1.66
Rank	#138	Overall
	#64	Relational DBMS

Score	1.11
Rank	#173	Overall
	#78	Relational DBMS

Score	1.88
Rank	#130	Overall
	#23	Key-value stores
	#3	Native XML DBMS

Website

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

Technical documentation

bigchaindb.readthedocs.io/en/latest

dev.mobiland.com/Overview.xsp

www.exasol.com/resources

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

Developer

Mobiland AG

Exasol

General Data Technology Co., Ltd.

Oracle

originally developed by Sleepycat, which was acquired by Oracle

Initial release

2016

2018

2000

2004

1994

Current release

1.1.263, October 2022

GBase 8a, GBase 8s, GBase 8c

18.1.40, May 2020

License

Commercial or Open Source

Open Source

AGPL v3

commercial

Open Source

commercial license available

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

Python

C, Java, Python

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

Server operating systems

Linux

Windows

Linux

AIX
Android
FreeBSD
iOS
Linux
OS X
Solaris
VxWorks
Windows

Data scheme

schema-free

Classes, Structs, and Lists are written in proprietary DataTypeDefinitionLanguage (.dtdl) and Objects consisting of those are written in proprietary DataAccessDefinitionLanguage (.dadl)

yes

schema-free

Typing

predefined data types such as float or date

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

only with the Berkeley DB XML edition

Secondary indexes

yes

SQL

Support of SQL

yes

Standard with numerous extensions

yes

SQL interfaced based on SQLite is available

APIs and other access methods

CLI Client
RESTful HTTP API

.NET Client API
Proprietary client DLL
WinRT client

.Net
JDBC
ODBC
WebSocket

ADO.NET
C API
JDBC
ODBC

Supported programming languages

Go
Haskell
Java
JavaScript
Python
Ruby

.Net
C
C#
C++
VB.Net

Java
Lua
Python
R

.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

Server-side scripts

Stored procedures

user defined functions

Triggers

no, except callback-events from server when changes happened

yes

only for the SQL API

Partitioning methods

Methods for storing different data on different nodes

Sharding

Proprietary Sharding system

Sharding

horizontal partitioning (by range, list and hash) and vertical partitioning

none

Replication methods

Methods for redundantly storing data on multiple nodes

selectable replication factor

yes

Source-replica replication

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

Hadoop integration

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Foreign keys

Referential integrity

yes

Transaction concepts

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

ACID

Concurrency

Support for concurrent manipulation of data

yes

Durability

Support for making data persistent

yes,with MongoDB ord RethinkDB

yes

In-memory capabilities

Is there an option to define some or all structures to be held in-memory only.

yes

User concepts

Access control

yes

Windows-Profile

Access rights for users, groups and roles according to SQL-standard

yes

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