DBMS > EJDB vs. MarkLogic vs. OrigoDB vs. Quasardb

System Properties Comparison EJDB vs. MarkLogic vs. OrigoDB vs. Quasardb

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Editorial information provided by DB-Engines

Name

Description

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

Operational and transactional Enterprise NoSQL database

A fully ACID in-memory object graph database

Distributed, high-performance timeseries database

Primary database model

Document store

Document store
Native XML DBMS
RDF store

as of version 7
Search engine

Document store
Object oriented DBMS

Time Series DBMS

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

Score	0.27
Rank	#297	Overall
	#44	Document stores

Score	5.92
Rank	#58	Overall
	#10	Document stores
	#1	Native XML DBMS
	#1	RDF stores
	#6	Search engines

Score	0.00
Rank	#383	Overall
	#53	Document stores
	#20	Object oriented DBMS

Score	0.14
Rank	#332	Overall
	#29	Time Series DBMS

Website

github.com/Softmotions/ejdb

www.marklogic.com

origodb.com

quasar.ai

Technical documentation

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

docs.marklogic.com

origodb.com/docs

doc.quasar.ai/master

Developer

Softmotions

MarkLogic Corp.

Robert Friberg et al

quasardb

Initial release

2012

2001

2009

under the name LiveDB

2009

Current release

11.0, December 2022

3.14.1, January 2024

License

Commercial or Open Source

Open Source

GPLv2

commercial

restricted free version is available

Open Source

commercial

Free community edition, Non-profit organizations and non-commercial usage are eligible for free licenses

Cloud-based only

Only available as a cloud service

DBaaS offerings (sponsored links)

Database as a Service

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Implementation language

C++

Server operating systems

server-less

Linux
OS X
Windows

Linux
Windows

BSD
Linux
OS X
Windows

Data scheme

schema-free

Schema can be enforced

yes

schema-free

Typing

predefined data types such as float or date

yes

string, integer, double, bool, date, object_id

yes

User defined using .NET types and collections

yes

integer and binary

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

can be achieved using .NET

Secondary indexes

yes

with tags

SQL

Support of SQL

yes

SQL92

SQL-like query language

APIs and other access methods

in-process shared library

Java API
Node.js Client API
ODBC
proprietary Optic API

Proprietary Query API, introduced with version 9
RESTful HTTP API
SPARQL
WebDAV
XDBC
XQuery
XSLT

.NET Client API
HTTP API
LINQ

HTTP API

Supported programming languages

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

C
C#
C++
Java
JavaScript (Node.js)
Perl
PHP
Python
Ruby

.Net

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

Server-side scripts

Stored procedures

yes

via XQuery or JavaScript

yes

Triggers

yes

Domain Events

Partitioning methods

Methods for storing different data on different nodes

none

Sharding

horizontal partitioning

client side managed; servers are not synchronized

Sharding

consistent hashing

Replication methods

Methods for redundantly storing data on multiple nodes

none

yes

Source-replica replication

Source-replica replication with selectable replication factor

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

via Hadoop Connector, HDFS Direct Access and in-database MapReduce jobs

with Hadoop integration

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

depending on model

Transaction concepts

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

ACID

can act as a resource manager in an XA/JTA transaction

ACID

Concurrency

Support for concurrent manipulation of data

yes

Read/Write Locking

yes

Durability

Support for making data persistent

yes

Write ahead log

yes

by using LevelDB

In-memory capabilities

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

yes, with Range Indexes

yes

Transient mode

User concepts

Access control

Role-based access control at the document and subdocument levels

Role based authorization

Cryptographically strong user authentication and audit trail

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