DBMS > EJDB vs. Infobright vs. Newts vs. Oracle Berkeley DB vs. Tkrzw

System Properties Comparison EJDB vs. Infobright vs. Newts vs. Oracle Berkeley DB vs. Tkrzw

Editorial information provided by DB-Engines

Name

Description

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

High performant column-oriented DBMS for analytic workloads using MySQL or PostgreSQL as a frontend

Time Series DBMS based on Cassandra

Widely used in-process key-value store

A concept of libraries, allowing an application program to store and query key-value pairs in a file. Successor of Tokyo Cabinet and Kyoto Cabinet

Primary database model

supports sorted and unsorted key sets
Native XML DBMS

in the Oracle Berkeley DB XML version

Key-value store

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

Score	0.31
Rank	#296	Overall
	#44	Document stores

Score	1.02
Rank	#192	Overall
	#90	Relational DBMS

Score	0.07
Rank	#375	Overall
	#41	Time Series DBMS

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

Score	0.07
Rank	#372	Overall
	#57	Key-value stores

Website

github.com/Softmotions/ejdb

ignitetech.com/softwarelibrary/infobrightdb

opennms.github.io/newts

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

dbmx.net/tkrzw

Technical documentation

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

github.com/OpenNMS/newts/wiki

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

Developer

Softmotions

Ignite Technologies Inc.; formerly InfoBright Inc.

OpenNMS Group

Oracle

originally developed by Sleepycat, which was acquired by Oracle

Mikio Hirabayashi

Initial release

2012

2005

2014

1994

2020

Current release

18.1.40, May 2020

0.9.3, August 2020

License

Commercial or Open Source

Open Source

GPLv2

commercial

The open source (GPLv2) version did not support inserts/updates/deletes and was discontinued with July 2016

Open Source

Apache 2.0

Open Source

commercial license available

Open Source

Apache Version 2.0

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

Java

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

C++

Server operating systems

server-less

Linux
Windows

Linux
OS X
Windows

AIX
Android
FreeBSD
iOS
Linux
OS X
Solaris
VxWorks
Windows

Linux
macOS

Data scheme

schema-free

yes

schema-free

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

Knowledge Grid Technology used instead

yes

SQL

Support of SQL

yes

SQL interfaced based on SQLite is available

APIs and other access methods

in-process shared library

ADO.NET
JDBC
ODBC

HTTP REST
Java API

Supported programming languages

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

.Net
C
C#
C++
D
Eiffel
Erlang
Haskell
Java
Objective-C
OCaml
Perl
PHP
Python
Ruby
Scheme
Tcl

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

C++
Java
Python
Ruby

Server-side scripts

Stored procedures

Triggers

yes

only for the SQL API

Partitioning methods

Methods for storing different data on different nodes

none

Sharding

based on Cassandra

none

Replication methods

Methods for redundantly storing data on multiple nodes

none

Source-replica replication

selectable replication factor

based on Cassandra

Source-replica replication

none

MapReduce

Offers an API for user-defined Map/Reduce methods

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Eventual Consistency

based on Cassandra
Immediate Consistency

based on Cassandra

Immediate Consistency

Foreign keys

Referential integrity

typically not needed, however similar functionality with collection joins possible

Transaction concepts

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

ACID

Concurrency

Support for concurrent manipulation of data

yes

Read/Write Locking

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

using specific database classes

User concepts

Access control

fine grained access rights according to SQL-standard

exploiting MySQL or PostgreSQL frontend capabilities

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