DBMS > EJDB vs. JaguarDB vs. OpenEdge vs. Oracle Berkeley DB vs. Sequoiadb

System Properties Comparison EJDB vs. JaguarDB vs. OpenEdge vs. Oracle Berkeley DB vs. Sequoiadb

Editorial information provided by DB-Engines

Name

Description

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

Performant, highly scalable DBMS for AI and IoT applications

Application development environment with integrated database management system

Widely used in-process key-value store

NewSQL database with distributed OLTP and SQL

Primary database model

Document store

Key-value store
Vector DBMS

Relational DBMS

Key-value store

supports sorted and unsorted key sets
Native XML DBMS

in the Oracle Berkeley DB XML version

Document store
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
	#60	Key-value stores
	#13	Vector DBMS

Score	3.51
Rank	#86	Overall
	#46	Relational DBMS

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

Score	0.45
Rank	#261	Overall
	#41	Document stores
	#122	Relational DBMS

Website

github.com/Softmotions/ejdb

www.jaguardb.com

www.progress.com/openedge

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

www.sequoiadb.com

Technical documentation

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

www.jaguardb.com/support.html

documentation.progress.com/output/ua/OpenEdge_latest

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

www.sequoiadb.com/en/index.php?m=Files&a=index

Developer

Softmotions

DataJaguar, Inc.

Progress Software Corporation

Oracle

originally developed by Sleepycat, which was acquired by Oracle

Sequoiadb Ltd.

Initial release

2012

2015

1984

1994

2013

Current release

3.3 July 2023

OpenEdge 12.2, March 2020

18.1.40, May 2020

License

Commercial or Open Source

Open Source

GPLv2

Open Source

GPL V3.0

commercial

Open Source

commercial license available

Open Source

Server: AGPL; Client: Apache V2

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++

the server part. Clients available in other languages

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

C++

Server operating systems

server-less

Linux

AIX
HP-UX
Linux
Solaris
Windows

AIX
Android
FreeBSD
iOS
Linux
OS X
Solaris
VxWorks
Windows

Linux

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

oid, date, timestamp, binary, regex

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

A subset of ANSI SQL is implemented

but no views, foreign keys, triggers

yes

close to SQL 92

yes

SQL interfaced based on SQLite is available

SQL-like query language

APIs and other access methods

in-process shared library

JDBC
ODBC

proprietary protocol using JSON

Supported programming languages

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

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

Progress proprietary ABL (Advanced Business Language)

.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
C++
Java
PHP
Python

Server-side scripts

Stored procedures

yes

JavaScript

Triggers

yes

only for the SQL API

Partitioning methods

Methods for storing different data on different nodes

none

Sharding

horizontal partitioning

since Version 11.4

none

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

none

Multi-source replication

Source-replica replication

MapReduce

Offers an API for user-defined Map/Reduce methods

Consistency concepts

Methods to ensure consistency in a distributed system

Eventual Consistency

Immediate Consistency

Eventual Consistency

Foreign keys

Referential integrity

typically not needed, however similar functionality with collection joins possible

yes

Transaction concepts

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

ACID

Document is locked during a transaction

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

User concepts

Access control

rights management via user accounts

Users and groups

simple password-based access control

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