DBMS > EJDB vs. Galaxybase vs. NuoDB vs. Oracle Berkeley DB vs. SpaceTime

System Properties Comparison EJDB vs. Galaxybase vs. NuoDB vs. Oracle Berkeley DB vs. SpaceTime

Editorial information provided by DB-Engines

Name

Description

Embeddable document-store database library with JSON representation of queries (in MongoDB style)

Scalable, ACID-compliant native distributed parallel graph platform

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

Widely used in-process key-value store

SpaceTime is a spatio-temporal DBMS with a focus on performance.

Primary database model

supports sorted and unsorted key sets
Native XML DBMS

in the Oracle Berkeley DB XML version

Spatial DBMS

Secondary database models

Relational DBMS

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

Score	0.27
Rank	#297	Overall
	#44	Document stores

Score	0.00
Rank	#383	Overall
	#39	Graph DBMS

Score	0.89
Rank	#198	Overall
	#92	Relational DBMS

Score	2.21
Rank	#117	Overall
	#20	Key-value stores
	#3	Native XML DBMS

Score	0.00
Rank	#383	Overall
	#7	Spatial DBMS

Website

github.com/Softmotions/ejdb

galaxybase.com

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

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

www.mireo.com/spacetime

Technical documentation

github.com/Softmotions/ejdb/blob/master/README.md

doc.nuodb.com

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

Developer

Softmotions

Chuanglin(Createlink) Technology Co., Ltd 浙江创邻科技有限公司

Dassault Systèmes

originally NuoDB, Inc.

Oracle

originally developed by Sleepycat, which was acquired by Oracle

Mireo

Initial release

2012

2017

2013

1994

2020

Current release

Nov 20, November 2021

18.1.40, May 2020

License

Commercial or Open Source

Open Source

GPLv2

commercial

limited edition free

Open Source

commercial license available

commercial

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 and Java

C++

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

C++

Server operating systems

server-less

Linux

hosted

Amazon EC2, Windows Azure, SoftLayer
Linux
OS X
Windows

AIX
Android
FreeBSD
iOS
Linux
OS X
Solaris
VxWorks
Windows

Linux

Data scheme

schema-free

Strong typed schema

yes

schema-free

yes

Typing

predefined data types such as float or date

yes

string, integer, double, bool, date, object_id

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

SQL interfaced based on SQLite is available

A subset of ANSI SQL is implemented

APIs and other access methods

in-process shared library

Browser interface
console (shell)
Graph API (Gremlin)
OpenCypher
Proprietary native API

ADO.NET
JDBC
ODBC

RESTful HTTP API

Supported programming languages

Actionscript
C
C#
C++
Go
Java
JavaScript (Node.js)
Lua
Objective-C
Pike
Python
Ruby

Go
Java
Python

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

.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

C#
C++
Python

Server-side scripts

Stored procedures

user defined procedures and functions

Java, SQL

Triggers

yes

only for the SQL API

Partitioning methods

Methods for storing different data on different nodes

none

Sharding

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

none

Fixed-grid hypercubes

Replication methods

Methods for redundantly storing data on multiple nodes

none

yes

Managed transparently by NuoDB

Source-replica replication

Real-time block device replication (DRBD)

MapReduce

Offers an API for user-defined Map/Reduce methods

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Foreign keys

Referential integrity

typically not needed, however similar functionality with collection joins possible

yes

Relationships in graphs

yes

Transaction concepts

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

ACID

tunable commit protocol

ACID

Concurrency

Support for concurrent manipulation of data

yes

Read/Write Locking

yes

MVCC

yes

Durability

Support for making data persistent

yes

In-memory capabilities

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

yes

Temporary table

yes

User concepts

Access control

Role-based access control

Standard SQL roles/ privileges, Administrative Users

yes

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